Explore every episode of the podcast HR Data Labs

David talks with Dara about choosing HR technology based on the outcome it needs to deliver—not simply adding AI. They discuss when straightforward automation or rules may work better, and how MCP-enabled, “headless” workflows could make HR tasks and information easier to access across the tools people already use. Key topics and takeaways Start with the use case. Dara describes scheduling and candidate-loss-risk examples where rules and existing data may solve the problem without AI, extra token costs or overengineering. Evaluate AI by its results and cost. The guests say AI’s value should be judged by whether it delivers the desired outcome, not by its effect on a company’s perceived valuation. Bring workflows to people. Dara sees MCP as a way for hiring managers, interviewers, finance partners and candidates to take part in recruiting workflows without learning an applicant-tracking system. They also discuss using messaging tools such as Slack or Teams. Improve the data underneath. Easier access can also surface inaccurate HR data more prominently; the guests stress that organizations need clean data to support good decisions. Make benefits decisions easier to navigate. They discuss using connected information to help employees compare plans, understand changes, and make decisions about benefits and FSA contributions. Make rewards information available when it’s useful. The guests contrast annual total-rewards statements with the possibility of seeing an updated picture when comparing a job offer or planning a mortgage. Names and resources mentioned Dara Brenner — guest Work Carousel — sponsor; the host mentions workcarousel.com/join. ADP, Slack, Teams, NetSuite, Workday, Claude, Walgreens, Mint, Quicken and QuickBooks are mentioned.

David and Steve discuss what stood out in HR technology in 2026 and where the field may be headed. Steve reflects on the surge of emerging HR-tech companies and argues that organizations should focus on strategic outcomes, especially organizational agility—rather than technology alone. They also explore how AI may reshape HR work and help make workforce needs more visible.  Key topics and takeaways  Emerging HR-tech companies: Steve says he saw an estimate of nearly 2,000 HR-tech startups launched in 2026, and describes increasingly advising emerging players.  Organizational agility: Steve defines it as anticipating business risks and opportunities, choosing a response, and coordinating across the organization to execute. He connects agility with financial success, successful change, and the ability to adapt.  Three organizational priorities: Steve’s “ascension test” highlights organizational agility, becoming an employer of choice, and improving employee productivity.  AI and the future of HR work: Steve expects AI to take on routine, repetitive tasks that don’t require ingenuity, judgment or compassion. He says workers and organizations will need resilience and agility as work changes.  “Make the invisible visible”: Steve sees AI helping reveal workforce information that can guide decisions, such as which skills are growing in importance, when above-market pay may be warranted, how long it takes to build a skill, and how best to staff a project.  Use judgment, not just data: David notes that an AI system may not be able to determine when above-market pay is justified; Steve agrees that many HR technology use cases are still ahead.  Global context matters: Steve describes working across countries and says understanding local culture is important when introducing technology and improving processes.  Names and resources mentioned  Steve Goldberg (guest); HR-tech and compensation practitioner who works with emerging companies.  Work Carousel (sponsor); the host directs listeners to workcarousel.com/join.  UKG; mentioned in connection with Steve’s organizational-agility work.  SUNY Buffalo; where Steve says he studied social work and later HR and business.  Attica Correctional Facility and Florida State Prison; Steve describes teaching job-transition classes to people nearing parole. 

David, Mike and Vinay discuss how HR can measure work as AI becomes part of the workforce. They argue that headcount alone misses the shift: organizations need to understand which tasks people and AI handle, how AI changes people’s capacity, and how to use that capacity to create more value without losing the human contribution.  Key topics and takeaways  Measure work, not just headcount. The guests describe “workforce intelligence” as a way to manage and measure a blended workforce of people and AI coworkers.  More capacity doesn’t automatically mean less busyness. Vinay says employees may get time back from AI but feel pressure to do more. Organizations need to help direct that “capacity dividend” toward valuable work.  AI output still needs human oversight. The host points to extra quality checks, hallucinations and the volume of AI-generated work as reasons that adoption may not immediately save time.  Efficiency is only part of the opportunity. Mike says it is easier to frame AI as a way to reduce costs than to work out how people can use it to deliver new, distinctly human value to clients.  Treat AI as a workforce cost. Vinay says OneDigital assigns each AI coworker a salary to understand its operating cost. The guests discuss matching model capability and cost to the task, rather than using the most advanced model for everything.  Rethink how work is organized. Mike says organizations should look at the tasks that make up jobs, assign work to the right “unit,” and help employees adapt. He estimates the coming challenge will be mostly organizational change and adoption, rather than technology alone.  Human accountability remains important. Vinay argues that AI can make information more accessible, but human judgment, experience and accountability are what distinguish an organization.  Make AI learning part of education and work. Vinay encourages using AI to expand thinking, not just to get answers with less effort. He says people who avoid learning to use it may miss career opportunities.  People’s AI journeys differ. Mike describes AI as a source of new ideas and connections, while Vinay stresses that organizations need to understand what adoption means for individuals—not assume one approach suits everyone.  Names and resources mentioned  OneDigital — Mike and Vinay’s organization.  Work Carousel — episode sponsor; https://workcarousel.com/join/  AI tools and models: Claude, ChatGPT, Copilot, GPT-OSS, and open-weight, non-frontier and frontier models.  Hardware: NVIDIA DGX Spark.  Other platforms and organizations mentioned: Microsoft, Fiverr, Deloitte, Accenture, Instagram, Penn State.  Terms discussed: workforce intelligence, AI coworkers, centers of intelligence, tokens, and retrieval-augmented generation (RAG). 

The host catches up with Teri, an old friend, at HR Technology in Las Vegas. They look back at 2026 and ahead to 2027 for HR technology and AI. Teri says nearly everyone is using AI now, but companies still aren't seeing the bottom-line results. They also discuss rising AI costs, how hard it is to measure return on investment, and whether AI will give us more free time or just more work.  Key topics and takeaways  Teri's new podcast, The Pivot Effect. It's aimed at individuals (employees and candidates), not HR professionals. Guests share their career pivots and the skills they picked up along the way.  Growing the research. Teri is working to grow Sapient Insights' research on the HR technology market. People are keen to contribute data because they want the findings back.  2026 vs. 2025. Teri says it felt like "a lot of the same," with layoffs announcements and AI hype. The difference is that everyone now uses AI in some way, where companies once banned tools like ChatGPT.  Results are lagging. Organizations are building processes to automate more, but Teri says they aren't yet seeing the bottom-line impact. The host adds that prompting skill, choosing the right models and applications, and the AI learning how you work all make a difference.  AI is expensive.  Both speakers say tokens add up. The host describes monthly bills approaching $10,000, with one prompt costing about $13 once usage went over the plan.  The host's team bought two NVIDIA DGX Spark machines (about $5,000 each) to build its own retrieval-augmented generation (RAG) system on internal data.  Teri's team is exploring internal models and has multiple AI tools (Claude, ChatGPT, Copilot and Perplexity) compete on the same task.  Both note that memory and computing hardware prices have jumped, including Mac Minis and Mac Studios.  Predictions for 2027.  Teri expects efficiency gains to become real, and new jobs to appear that look and feel different. She doesn't believe jobs will "go and never come back."  She compares this to farming, where 75–90% of people worked in agriculture in the 1850s and only one or two percent do today.  She thinks 2027 may not bring a dramatic change, but "the wheels are turning."  Measuring ROI. Teri says nobody has figured out how to measure the return on AI in knowledge work. It's easier in industries with measurable output.  Robotics. Teri expects robotics to come back, especially for dangerous jobs, though it will be more expensive. The host notes manufacturing has used robots for decades.  Will AI give us time back? Both hoped AI would help them work smarter and improve wellness, but see it making people do more instead. They talk about the pressure of remote work and the benefit of breaks, such as a midday bike ride.  AI becoming everyday. Teri hopes we'll eventually stop calling it "AI" and it will just be part of life, like the phone. The host compares it to the arrival of the personal computer and notes that Siri, Alexa and Google Assistant have been around for about twelve years. He says consumer tools have raised expectations, so Apple, Google and Amazon are improving theirs.  Looking back next year. The host plans to revisit this year's predictions in 2027.  Resources and names mentioned  The Pivot Effect podcast (Teri's new show) : https://podcasts.apple.com/us/podcast/the-hr-huddle/id1583756892 Sapient Insights  Work Carousel: workcarousel.com/join (sponsor message)  Tools mentioned: ChatGPT, Claude, Copilot, Perplexity, NVIDIA DGX Spark, Mac Mini, Mac Studio  Companies mentioned: Apple, Google, Amazon, Tesla  Event: HR Technology, Las Vegas  Fun fact  Early in her career, Teri worked at a cemetery. She drew plot maps for the gravediggers from the deed book, which was kept in pencil at the time. She calls it one of her early pivots. 

David talks with Dr. Robyn Short about a Workplace Peace Institute study on what conflict costs US workplaces: about $3,200 per employee per year. They cover why emotions can't be left at the door, how curiosity leads to compassion, and why trust is hard when roles are unclear and AI is changing work. Robyn argues that the most valuable skills now are deeply human ones.  Key topics and takeaways  What the Workplace Peace Institute does. It is a systems design and research firm. It helps leaders design workplace systems that give people access to their basic human needs and dignity.  The cost of conflict. The study counted the hours per week each employee spends navigating conflict and applied them to the median income of the average employee. Nobody puts conflict in the budget, even though leaders and HR can be certain it's coming.  Emotions at work. Robyn says we are "feeling creatures who think," so leaving emotions at the door is biologically impossible. Crying is a natural nervous-system response to stress and needs no apology.  Curiosity before compassion. Ask "What would have to happen for me to behave this way?" When someone's behavior seems out of proportion, "act as if" they are having a hard time. That lets you see it as not being about you.  Fear as a tool. Robyn says that when people are afraid of one another, they can't build the connection and collaboration that lead to systems change.  Trust amid uncertainty. She cites research that power reduces empathy, and Gallup research that a worker's manager is the most influential person in their working life. Build a real relationship with your manager, or manage up if they don't.  AI and your job. AI will replace some jobs and radically change others. Robyn's advice is "evolve or die": take responsibility for your own upskilling, and stay close to what your work exists to produce.  Being more human. Now that machines do much human work, the people who evolve will be those who lean into deeply human skills.  Resources and names mentioned  The Matriarch Effect by Dr. Robyn Short: www.TheMatriarchEffect.com  Workplace Peace Institute  Ken Cloak, one of Robyn's teachers  Margaret Wheatley, Who Do We Choose to Be?  Gallup research on managers' influence  Tracy Sponenberg, an HR friend of David's  Taylor Swift, whom Robyn calls a matriarchical leader  Sponsor: Work Carousel (workcarousel.com/join) 

David Turetsky talks with Nikki Stone, author of Architecting Resilience, about what it takes to build teams, leaders, and organizations that can handle relentless change without falling apart. Nikki shares how her work in startup and large holding-company environments shaped her thinking on resilience, communication, and the real skills managers need to lead humans well.  Key topics  Nikki Stone explains how Architecting Resilience came from decades of experience across startup and corporate environments, including leadership roles in ad tech and large holding companies.  In this episode, Nikki shares how advanced pattern recognition, especially as a neurodivergent leader, helped her spot repeatable structures behind successful teams and scalable organizations.  David and Nikki discuss why many strong individual contributors are promoted into people management without being equipped for the role.  They explore the importance of creating separate career paths for high-performing individual contributors who do not want to manage people.  Nikki recommends mental health first aid training for managers as a practical way to better support employees without trying to act as therapist or doctor.  The conversation examines how sandwich-generation realities, such as caregiving, parenting, divorce, and aging parents, affect employee performance and leadership needs.  David and Nikki dig into neurodiversity in the workplace and why leaders need to adapt communication styles for creatives, technologists, and other distinct working styles.  Nikki shares a Venn diagram method for identifying strengths, gaps, and bridge-building experiences when planning career growth.  They discuss how learning can happen through audio, books, lectures, social feeds, and intentionally reshaping what you consume to support your goals.  The episode closes with a strong case for replacing fear-based management with purpose-driven, human-centered leadership that improves retention and organizational resilience.  Timestamps  00:00 - Welcome to the podcast and introduction to Nikki Stone  00:58 - Nikki’s current work: author, founder, podcast host, and executive leader  03:01 - The unexpected nervous habit: dancing and movement as regulation  04:11 - Music as a tool for shifting mood, focus, and resilience  06:58 - Why Nikki wrote Architecting Resilience  07:19 - Early exposure to business through her mother’s meetings  08:08 - Pattern recognition as a superpower in scaling organizations  09:20 - Why scaling inside large organizations is an art form  10:31 - The IQ, EQ, and CQ framework in ad tech and team building  13:40 - Managers need better tools to lead resilient teams  14:30 - Why not everyone should be pushed into people leadership  15:27 - Mental health first aid as a leadership tool  16:26 - Leading people through life complexity, not just output  18:55 - Why neurodivergent talent matters in modern organizations  23:53 - A Venn diagram method for finding strengths and growth gaps  25:31 - Using bridge experiences like nonprofit board service to build skills  27:32 - Learning late, learning differently, and building from audio first  29:53 - Reshaping social algorithms to support curiosity and growth  31:34 - Everyone has deficits, including managers  33:13 - Leadership training must include values, guardrails, and human context  35:09 - Fear-based employment and why paycheck-only motivation is unsustainable  36:41 - AI gives averages, but humans provide context and excellence  38:02 - Replacing return-to-office fear with purposeful gathering  39:26 - Retention, soul, and the cost of losing institutional memory  40:08 - Friction is not the enemy - it can reveal billion-dollar ideas  41:48 - Closing thoughts and a shared interest in continuing the conversation  Key frameworks  IQ, EQ, CQ - Intelligence, emotional intelligence, and contextual intelligence as the mix needed for effective leadership and team performance.  Venn diagram career mapping - A way to compare current strengths with future-role requirements and identify bridge skills.  Gather with purpose - Nikki’s approach to intentional in-person team time focused on connection, learning, and shared context.  Friction as signal - Reframing recurring friction as an opportunity to identify and solve meaningful business problems.  Notable quotes  “There is no such thing as normal.”  “You are working with humans and the humans are the actual parts.”  “Friction is not something to be feared; it's something to be embraced.” 

This episode looks at where HR technology is today and where it may be heading by 2027, with a focus on AI’s real impact on HR teams. David Turetsky is joined by Jay Polaki, CEO of HR Geckos, to unpack why so many organizations have access to AI tools but still lack the data, governance, and skills to use them well.We discuss the growing gap between AI enthusiasm and operational readiness, why HR is still unclear on its role in AI strategy, and why the conversation needs to shift from hype to use cases, trust, and measurable outcomes.  Key topics  Jay Polaki, CEO of HR Geckos, explains that HR Geckos is a people-centric co-pilot for HR operations, built by HR for HR.  The episode opens with a lighter note about Jay’s unexpected appearance on MTV during a Russell Peters event clip.  The central theme is that AI access is no longer the main problem — scaffolding is.  Jay shares findings from HR Geckos’ “AI Ready or Not” roadshow, based on conversations with about 55 HR and business leaders across multiple sessions.  Many organizations have AI tools, but data quality, governance, ownership, and funding remain unclear or incomplete.  David raises concerns about security risks, especially employees using consumer AI tools with sensitive HR and PII data.  The discussion highlights a split in AI maturity:   Some HR teams have no access and no training.  Others are forced to use AI with little or no education.  ROI is a major sticking point, with both speakers arguing that most organizations are measuring the wrong things or measuring too early.  Jay says the best way to deploy AI in HR is by starting with a specific use case, not a broad enterprise rollout.  HR service delivery and the HR service desk are identified as one of the most likely near-term AI investment areas.  The conversation repeatedly returns to trust, especially around governance, role clarity, and employee anxiety about job loss.  David and Jay agree that AI is more likely to augment workers than replace them, and that people who know how to use AI will outpace those who do not.  Jay argues that HR should stay central to reskilling, learning and development, recruiting, and re-engineering processes.  The episode ends with a strong warning against using AI for sensitive compliance work without human oversight.  Timestamps  (00:00) Opening the HR technology conversation with Jay Polaki (01:12) Jay introduces HR Geckos as a people-centric HR ops co-pilot (02:17) Jay’s unexpected MTV cameo and the Russell Peters story (04:42) Why 2026 feels chaotic for HR technology and AI (05:23) Roadshow findings from 55 HR and business leaders (06:21) AI access is widespread, but scaffolding is missing (07:47) Why data, ownership, and governance are still unresolved (09:18) Security concerns around employees using consumer AI tools (10:29) Two extremes of AI readiness in HR teams (11:26) Large organizations vs. smaller firms in AI adoption (12:23) Trust is the biggest barrier to AI deployment (13:14) Why AI desktop tools raise privacy and control concerns (14:11) Why AI was often used as a cost-cutting tool before HR was ready (15:22) Why ROI is hard to define for AI in HR (16:46) The real friction is data readiness and skills readiness (18:09) Why the best AI deployments start with a single use case (18:34) Why the HR service desk is a likely next AI investment (20:30) Start with why, then move to how (21:57) Why AI should be deployed in baby steps (22:56) Centralizing siloed HR data before scaling AI (24:21) Why leaders are unsure about HR’s role in AI strategy (26:08) Mixed views on HR’s AI future: curious, transformational, undefined (27:29) Where HR can lead: skills, learning, recruiting, and re-engineering (28:32) AI in talent management and the future of interviewing (29:30) Governance gaps, risk levels, and access controls (30:28) HR’s role in managing worker anxiety about AI (31:47) Trust and governance as urgent CEO, CHRO, and CTO issues (33:27) AI as a tool, not a replacement for people (34:04) Why the doomsday narrative is overstated (35:12) Why AI is still “pretty dumb” without human training (36:04) Augmented intelligence and human judgment in tandem (38:12) Why AI still cannot handle HR compliance on its own (39:12) Government scrutiny and accountability risks (39:50) Wrap-up and HR Tech conference frustrations for service providers  Notable quotes  “Technology should elevate people, not replace them.”  “We’ve solved the AI access issue — ownership, funding, data, governance, all of that is still in flux.”  “People who know how to use AI will replace people who don’t know how to use AI.” 

David Turetsky interviews Gabriella Garcia, COO and Chief People Officer at Warp, about how AI is reshaping the build versus buy decision in HR and people operations. They dig into why this question is changing now, what guardrails matter for sensitive data, and why people leaders need to take a more strategic role in technology decisions. Gabby shares how her engineering background informs her view of modern people tech, while David adds real-world context from years of hacking together internal systems. Together, they explore how AI lowers the barrier to building, but also raises new questions around governance, cost, and organizational design.  Key topics  In this episode, Gabby Garcia explains Warp’s mission as an AI native employee management platform handling payroll, benefits, state tax compliance, and HR systems for more than 1,200 customers.  David and Gabby compare today’s AI-enabled build culture with older eras of custom tooling, including early internal dashboards and Access database work.  Gabby says the build versus buy equation has changed because non-engineers are now more technical and because tools like Claude Code and Lovable reduce the activation energy for prototyping.  The conversation centers on the risk of rogue projects, especially when people teams handle PII, PHI, SSNs, birthdays, payroll data, and other sensitive information.  Gabby points to Shopify as an example of a company encouraging broad internal experimentation, while also surfacing the downside of AI slop, access issues, and repetitive low-value tools.  She argues for cultural guardrails, approval rules, and manager review processes rather than blanket bureaucracy.  The discussion shifts to the engineering function, where Gabby says engineers are increasingly becoming prompt-driven problem solvers and thought partners rather than manual code producers.  David and Gabby agree that this changes organizational DNA, especially when non-engineering teams can build internal tools, bots, and workflows that still need governance.  Gabby makes the case that people leaders, not just CIOs or CTOs, should lead AI adoption strategy because they own talent, enablement, growth, and role evolution.  The episode closes on token spend, cost control, and the need for finance and people teams to understand model selection, usage caps, and the accounting implications of AI spend.  Timestamps  00:00 - Introductions and Gabriella Garcia’s background at Warp 01:35 - From Colombia and Miami to MIT and engineering at Facebook, Apple, and Google 02:38 - What Warp does as an AI native employee management platform 03:38 - Fun fact: Gabby’s unusual sense of balance 05:28 - Why build versus buy is changing in HR and people tech 06:10 - More technical people are now building prototypes themselves 07:37 - Low-code and AI tools lower the barrier to entry 09:45 - Why PII, PHI, and compliance make people tech risky 10:11 - Shopify’s “build whatever you want” AI experiment 12:28 - How long old internal tool-building used to take 13:48 - Why innovation needs risk awareness, not reckless experimentation 14:40 - Borrowing engineering-style PR reviews and testing for people tools 16:44 - The future of engineering in an AI-native workplace 17:41 - Engineers, designers, and operators as prompt-based builders 18:10 - AI as a thought partner, chief of staff, and first-pass reviewer 19:38 - Internal tools can be pushed to managers, but customer-facing work still needs engineers 20:22 - How AI changes the DNA of an organization 22:17 - Why the people function should drive adoption strategy 23:11 - OpenAI’s people leadership and the future of every role 24:55 - Why technical depth in a CPO matters for AI transformation 26:14 - People teams have been implementing tech for years, but AI is different 27:39 - Technology adoption takes time, and the AI curve is still early 28:45 - Bad HR data and weak products still block mobile adoption 29:11 - Skipping the messy middle of legacy systems in emerging markets 30:35 - How chat-based tools and image-based workflows improve accessibility 32:14 - Serving small businesses and frontline teams with practical AI 33:40 - AI may make customization accessible beyond large enterprises 34:38 - Token costs, model selection, and the ROI of AI tools 35:55 - One sales rep’s token bill as a cautionary tale 37:18 - Education gaps around model choice, data access, and rollout strategy 38:13 - Token spend as a new cost per employee problem 39:09 - Why accounting and capitalization rules matter for AI spend 40:09 - Tracking utilization and setting token caps 41:00 - Hardware choices, open source models, and reducing model spend 42:11 - A future conversation on tokenomics and people leader skills 43:08 - Moving from experimentation to pragmatic implementation 44:24 - Why every organization needs its own AI point of view  Notable quotes  “The people function is in service of the people.”  “There are ways in which we can absorb and implement a lot of the learning from other organizations.”  “My recommendations are likely not a great fit for your business.” 

David Turetsky speaks with IBEJesus Prince from HR Data Labs Consulting about their time at the NACO conference and what stood out most. The conversation is short but clear: the event brought together people who were focused on finding practical solutions, and even attendees outside the immediate decision-making circle were willing to help connect the dots.  Key topics  In this episode, David Turetsky introduces the conversation from the HR Data Labs Podcast and frames it around the team’s experience at the NACO conference.  IBEJesus Prince, a principal consultant at HR Data Labs Consulting, shares a broad conference takeaway: the people at NACO were genuinely solution-driven.  A major theme is the value of openness at the conference — even people who were not directly responsible for making decisions still cared about moving a solution forward.  The guest notes that asking questions often led to the right person, which made the event feel collaborative rather than blocked by hierarchy.  Commissioners and other officials were mentioned as people the team met, reinforcing that the event brought together stakeholders with influence and interest.  The conversation highlights a contrast between environments where non-experts become blockers and this conference, where people helped route questions and support progress.  IBEJesus emphasizes that the organization and the people they met left a strong positive impression.  The episode closes, suggesting this was a brief conference check-in rather than a full-length interview.  Timestamps  00:00 - Testing the audio and getting set up 01:41 - David introduces the HR Data Labs Podcast and the guest 01:57 - Why the NACO conference was the focus of the conversation 02:08 - A quick personal icebreaker before the main topic 03:41 - First conference takeaway: people were solution-driven 04:06 - Commissioners and officials were open to connecting people to answers   04:33 - Why the event felt collaborative instead of blocked by hierarchy 04:52 - The conversation wraps up early

David Turetsky and Sushma Tripathi discuss where human capital management is headed, why HR modernization is harder than simply adding new software, and what leaders need to fix first. Sushma brings more than 25 years of HCM strategy experience across product, operations, staffing software, and advisory work, so the conversation stays grounded in what organizations are actually facing.In this episode, they focus on the shift from transactional HR to AI-enabled operations, the burden of process and technology debt, and why workforce management is becoming the backbone of modern HR transformation.  Key topics  Sushma Tripathi’s background spans HR, benefits, actuarial work, product development, COO and CPO roles, and strategic advisory work, giving her a broad view of HCM change.  The industry is moving from transactional HR to more intelligent, integrated, AI-enabled operations.  Many organizations are stuck with fragmented processes, legacy systems, unclear ownership, and outdated configurations that no longer match current needs.  Process debt and technology debt are major blockers, especially when old workflows and old system settings keep surviving years of change.  Decision rights confusion is a recurring issue - HR, operations, finance, and IT often all touch the same workflows without clear ownership.  AI readiness is limited by data quality, governance, and change management, not by the AI tools themselves.  Workforce management is emerging as the anchor for operational excellence, especially around scheduling, labor models, compliance, productivity, and outcomes.  Employee self-service and manager self-service still matter, but users now expect experiences that feel as simple and intuitive as consumer apps.  Many organizations are asking whether to buy new technology or improve what they already have first.  Sushma emphasizes that HR is becoming a strategic operations partner, not just a people-management function.  Timestamps  00:32 - Welcome to the HR Data Labs podcast and introduction to the conversation 01:44 - Sushma Tripathi’s 25-plus years in HCM strategy and leadership 03:47 - A personal story about hiking and the challenge of Angels Landing 06:25 - Transitioning into the real topic: HCM modernization and AI 07:47 - Why HR is moving from transactional work to intelligent, AI-enabled operations 09:59 - Process debt and technology debt are slowing organizations down 11:57 - Why employee and manager self-service still matters 14:52 - Why maturity level changes the pace of modernization 16:52 - Where organizations should start when modernization feels overwhelming 18:29 - How AI should fit into end-to-end workflows, not just isolated tasks 19:24 - Why governance and data configuration are still foundational 21:25 - Why every organization needs continuous operating-model revision 22:33 - Cleaning, combining, and using data before expecting better outcomes 23:03 - Baby steps, outside help, and why AI tools do not fix broken processes 25:39 - Why workforce management is the biggest concern going forward 26:02 - What workforce management includes beyond time tracking 27:00 - Compliance, fines, penalties, and brand risk in workforce management 28:28 - Closing thoughts and goodbye  Notable quotes  “Data quality, not AI, is actually the biggest barrier.”  “Because just because you have a hammer, everything is not a nail.”  “You can't just go into Chat GPT and say fix me.” 

Jennifer McClure joins David Turetsky to unpack how her career in HR, executive search, speaking, and coaching led to Disrupt HR. The conversation focuses on why HR gets blamed for business problems, how leaders can stop using HR as a scapegoat, and why true disruption means rethinking both broken processes and the ones that only seem fine.  Jennifer McClure shares a practical case for moving HR beyond administration and into real business influence, while David Turetsky pushes on the everyday realities of performance management, remote work, compensation, and accountability.    Key topics  In this episode, Jennifer traces her path from nearly 20 years in corporate HR leadership to executive search, then into speaking, coaching, and launching Unbridled Talent.  She explains how Disrupt HR began as a way to surface ideas from people who may not have a speaker reel or prior speaking experience but still have something meaningful to say about the future of work.  Jennifer argues that HR was originally built as an administrative function, but the profession has evolved and now has a chance to influence business strategy far more directly.  She challenges the old “seat at the table” mindset and says the real issue is not seating, but whether HR leaders actually understand the business and how people drive results.  David and Jennifer discuss how HR often becomes the dumping ground for decisions leaders do not want to own, especially around performance management, compensation, culture, and employee relations.  Jennifer emphasizes that HR should not automatically say “no” and take the blame. Instead, managers should be required to make the case and own their decisions.  The conversation uses examples from remote work and compensation to show how easily leaders pass responsibility to HR without first having the difficult conversation themselves.  Jennifer explains that Disrupt HR is not just about fixing broken systems. It also asks whether working processes could be simpler, faster, more human, or more useful.  She compares workplace experiences to consumer experiences, like Netflix recommendations, Amazon suggestions, and frustrating phone trees, to show how people expect better design at work.  David and Jennifer talk about the value of short-form ideas, different audience reactions, and why a talk or process does not need to please everyone to be worthwhile.  Jennifer closes by encouraging listeners to disrupt themselves, their organizations, and even processes that appear to be working well, because innovation often starts with a better question.    Timestamps  00:00 - Intro to Jennifer McClure and the HR Data Labs conversation  01:10 - From corporate HR leadership to executive search and speaking  03:34 - Why Unbridled Talent got its name and what Jennifer does now  04:37 - Executive coaching, speaking, and the origins of Disrupt HR  05:20 - A fun fact: farming, horses, and Tennessee roots  07:08 - Why the topic of HR disruption matters right now  08:12 - Why HR has been seen as ripe for disruption  09:23 - From administrative personnel work to “seat at the table”  10:20 - What “being strategic” in HR really means  11:06 - Talent strategy and business strategy should be integrated  12:04 - The real opportunity for HR influence and business impact  13:32 - Why some leaders still only want transactional HR  14:19 - Business leaders blaming HR for problems they do not want to own  16:10 - Reframing “HR always says no” into manager accountability  17:45 - A real example of remote work, blame, and chain-of-command confusion  19:48 - Compensation example: when a late request cannot be approved     21:27 - How HR can remove itself as the scapegoat and push ownership back up  23:08 - What Disrupt HR actually is and how the format works  24:30 - Bringing in voices from outside HR to improve work  25:57 - Disruption is not only for broken things  26:46 - Looking at consumer experiences to redesign workplace processes  28:32 - Why outdated phone trees and apply processes frustrate people  29:05 - The importance of asking why a process exists in the first place  30:42 - Over 11,000 five-minute Disrupt HR talks and why the format works  31:55 - Why not every presentation lands with every person  33:47 - Preparing a keynote and accepting mixed audience feedback  35:02 - Why short, focused presentations fit how people consume information now  36:39 - Where to learn more about Disrupt HR and why disagreement matters  37:07 - Laurie Ruettimann, strong opinions, and learning from disagreement  38:32 - What listeners should take from short talks and different viewpoints  40:20 - Final thoughts on disrupting work, organizations, and yourself    Notable quotes  “I think HR gets blamed for a lot.”  "I challenge you to disrupt yourself, your organization, your people.”  “This is the definition of innovation.”    Action items  Ask why a process exists before assuming it should stay the same.  If a manager wants to take action, ask them to own the decision and make the case.  Look for one process that is broken and one that seems fine but could be better.  Compare your workplace experience to the consumer experience you expect outside work.  Revisit assumptions about HR being the default owner of every uncomfortable business problem. 

In this episode of HR Data Labs Podcast, host David Turetsky is joined by Betsy Irizarry, CEO and founder of HR Contempo, to unpack one of the most overlooked compensation risks in modern organizations: pay compression. They also discuss how AI, labor market pressure, mergers and acquisitions, and communication gaps are reshaping workforce strategy and employee trust. Betsy brings 25-plus years of HR experience across industries including technology, professional services, agriculture, and energy, making this a practical conversation about what leaders are missing and what they need to do next.  Key topics  Betsy Irizarry shares how HR Contempo helps organizations with human capital issues, especially mergers and acquisitions and compensation work.  Pay compression is becoming more common as companies raise pay to compete for new hires while leaving long-tenured employees behind.  Labor market pressure is intensifying the problem, especially in skilled trades like plumbing and electrical work tied to data centers and other growth sectors.  David and Betsy connect today’s compensation challenges to pandemic-era pay decisions that created long-term ripple effects.  Mergers and acquisitions often focus on financial and operational integration while overlooking compensation structure and job analysis.  Simply matching job titles is not enough in M&A work because the actual work, scope, and responsibilities may be very different.  AI is creating a new kind of compensation pressure as companies pay more for employees who can use AI tools to generate insights and move faster.  Betsy argues that organizations must balance AI adoption with institutional knowledge, since experienced employees still bring critical context.  Workforce readiness for AI is uneven, so organizations need to assess who can reskill and who may struggle to adapt.  Total rewards matters more than base pay alone, including benefits, 401(k), employee assistance programs, development, and other perquisites.  Communication is a major theme throughout the conversation, especially around pay transparency, manager training, and helping employees understand total compensation.  The episode closes on the idea that compensation conversations should become more open, business-oriented, and positive.  Timestamps  00:00 - Welcome to HR Data Labs Podcast and introduction to Betsy Irizarry 01:07 - Betsy’s background and HR Contempo’s focus on human capital and M&A 02:14 - Betsy’s travel habit of studying how businesses operate in different places 04:22 - Episode topic: pay compression and AI reshaping workforce strategy 05:30 - The most common compensation challenge Betsy sees across clients 06:42 - How pandemic-era pay decisions still affect compensation today 07:19 - Labor market pressure and why skilled trades are at risk of compression 08:49 - Solar and IT examples of demand spikes driving wage pressure 10:02 - Why M&A can create major pay compression if compensation is ignored 11:06 - Job description management and why titles alone do not tell the full story 12:35 - AI skills becoming a premium and the risk of losing institutional knowledge 13:37 - Should companies hire AI talent or reskill current employees? 15:23 - Why outcome-based AI use matters more than activity metrics 16:50 - Walmart self-checkout as a cautionary tale about automation and human oversight 18:49 - HR’s role as the sounding board for leaders on cost-cutting and people strategy 20:07 - What pay compression means, with a practical salary example 21:50 - Ways to address compression without giving everyone the same raise 23:27 - Why total rewards is broader than base pay and benefits 24:04 - Differences between companies with strong total compensation packages and those without 25:36 - The need to overcommunicate total rewards through statements and ongoing manager conversations 26:50 - Why merit review should include the full compensation picture 27:48 - Does pay transparency actually improve equity? 29:33 - Training managers and employees to have business-oriented pay conversations 31:04 - AI makes pay and company information easier to find, increasing the need for honest communication 32:18 - HR’s responsibility to advise leaders and support employees’ basic need to be paid fairly  Notable quotes  “AI won't replace you. Someone who understands AI and uses it as a tool will replace you if you don't.”  “At the end of the day, they just want to get paid so that they can go back home and have a good life.”  “Let's have continue to have conversation, meaningful conversations with our leaders and our employees.” 

In this episode, host David Turetsky speaks with Denise Triba, CHRO at Ingenovis Health, about how her HR team is using workflow mapping, ticketing data, and AI to improve service for clinicians and internal teams. The conversation centers on a practical, human-in-the-loop approach to AI, with Freddie, their internal AI tool, trained to handle repetitive HR questions faster and more accurately. We discuss how a workforce solutions company thinks beyond recruiting, why understanding the work before applying technology matters, and how better HR operations can improve clinician experience, response speed, and career development.  Key topics  David introduces Denise Triba, CHRO at Ingenovis Health, and frames the episode around operational data and AI in HR.  Denise explains that Ingenovis Health is a workforce solutions company supporting healthcare providers and life sciences organizations with the right workforce mix.  The discussion distinguishes Ingenovis from a traditional recruiting function, emphasizing a consultative model that optimizes client workforce needs.  Denise shares how the pandemic increased healthcare organizations’ need for more precise staffing and stronger workforce partners.  The HR team started with workflow mapping to understand exactly how work was being done before adding technology.  A ticketing system was introduced to validate assumptions and quantify the most common HR requests.  The team identified high-volume issues such as benefits enrollment and leave requests, then began training Freddie to handle those questions.  Denise describes Freddie as an internal AI tool still in beta, used between HR and IT before external release.  The conversation covers human review, validation, and hallucination prevention, with subject matter experts writing and checking training articles.  Denise explains that AI is helping reduce repetitive work, improve first-response accuracy, and free HR coordinators for more valuable work and career growth.  The episode closes with advice for HR teams: start with the process and the people doing the work, then apply technology to enhance it.  Timestamps  00:00 - Opening and introduction to the episode 00:32 - David introduces Denise Triba and Ingenovis Health 01:01 - What Ingenovis Health does as a workforce solutions company 01:47 - The kinds of healthcare roles Ingenovis supports 02:38 - Denise’s background and early interest in medicine 03:48 - Why the episode focuses on operational data and AI in HR 04:24 - Employee and clinician experience as a top priority 05:21 - Why Ingenovis is more than a recruiting team 06:33 - The mix of W-2 employees and 1099 contractors 07:34 - Why facilities choose workforce solutions over direct hiring 08:33 - How healthcare organizations changed after the pandemic 09:04 - Starting with workflow mapping before introducing AI 10:03 - Using ticketing data to validate top HR call categories 10:29 - Tracking 3,000 calls and training Freddie with real data 11:33 - How workflow data shows friction and points to automation 12:10 - Faster, more accurate information for clinicians and HR coordinators 12:55 - Benefits enrollment as the most common question 13:22 - Other repeat requests like leave support 14:34 - Writing articles to train Freddie on core answers 15:04 - Subject matter experts validating Freddie’s responses 15:48 - Avoiding misinformation and limiting scope during early rollout 16:34 - How Freddie is used internally in beta 17:22 - Better capture rates and fewer repeat follow-up emails 18:44 - Extending clinician satisfaction through better service 20:15 - When Freddie needs human support and escalation 20:40 - Employment verification as an example of a hybrid workflow 21:43 - Using AI across client-facing and sales-side operations 22:59 - What surprised the team most about implementing AI 23:56 - How the project is expanding into other HR workflows 24:27 - Addressing fears that AI would take jobs away 26:05 - Cost considerations and working within budget 27:21 - The value of strong HR and IT partnership 28:37 - Advice for HR teams considering AI adoption 29:28 - Closing reflections on the scientific, process-first approach 29:54 - Looking ahead to future updates on Freddie and beyond  Notable quotes  “You really need to understand the what before you start to apply the how.”  “If you have to teach someone, you learn it.”  “This isn’t about a workforce change internally. This is about how do we get better."

David Turetsky talks with Nicole Ward of Aon about her concept of the executive athlete and why leadership performance is built on physiology, recovery, and sustainable habits. They explore how burnout shows up in executives and sales teams, and why HR can play a major role in reframing wellness as a business performance issue.Nicole shares her own wake-up call, the accident that pushed her to rethink health, and practical ways leaders can build better energy, focus, and resilience without “boiling the ocean.”  Key topics  Nicole Ward’s background at Aon - Senior vice president of sales with a career rooted in professional services, public accounting, and now commercial insurance.  The origin of the executive athlete idea - Nicole’s near-fatal rollover accident became the catalyst for a long-term shift toward health and wellness.  Physiology as leadership infrastructure - Her central idea is that energy is the currency of performance, and leaders who are under-slept, under-nourished, and constantly “on” are not operating at full capacity.  Why burnout matters organizationally - Burnout, dysregulation, and chronic stress in senior leaders have downstream effects on teams, culture, and decision-making.  Culture rewards overwork - The conversation pushes back on the idea that always being available is a badge of honor, especially in executive roles.  Recovery improves performance - Nicole argues that slowing down and recovering is not weakness but a competitive advantage supported by real data.  Small changes beat all-or-nothing thinking - She recommends “exercise snacks,” breathing breaks, short movement intervals, and better sleep habits rather than unrealistic total overhauls.  Data can drive behavior change - She shares an example of a sales team using wearable devices over six months to track sleep, stress, and activity, leading to better performance and better well-being.  HR’s role in changing the conversation - HR professionals can bring wellness into strategic planning sessions and ask leadership how health is being prioritized.  Bio-individual wellness at work - Nicole emphasizes that companies should offer flexible options because different people need different supports, from meditation space to gym access to better snacks.  Timestamps  00:00 - Welcome to HR Data Labs and introduction to Nicole Ward 01:12 - Nicole’s role as senior vice president of sales at Aon 02:15 - The accident that sparked the executive athlete journey 03:14 - Why executives need physiology, not just willpower 06:54 - How boardroom experience shaped the platform 07:24 - A team member’s comment that changed everything 08:21 - Why the book is aimed first at sales athletes and then all executives 09:30 - Recovery as a competitive advantage, not weakness 10:43 - The cost of working until collapse 11:20 - The “toxic capacity” bucket and signs of overload 12:19 - Why leaders struggle to fully disconnect 13:26 - Tying recovery to revenue and metrics 14:41 - Burnout in sales and other high-pressure roles 15:31 - Alternatives to always being “on” 16:25 - Why all-or-nothing thinking fails 17:26 - Using micro-habits for sleep, breathing, and movement 19:37 - A six-month wearable experiment with a sales team 21:33 - Salespeople as athletes and why preparation matters 22:48 - Why companies should treat wellness as a real priority 23:45 - The biology of organizations and employee energy 24:48 - How HR can start the conversation with leadership 26:14 - Bringing health and wellness into strategic planning 27:10 - Example of no meeting Fridays 28:46 - Why a bio-individual approach is better than one-size-fits-all 29:15 - Personalized wellness options for different employees 30:11 - The reality of obesity, inflammation, and dysregulation 31:11 - Incremental progress in the face of broader stress 32:01 - Closing thoughts and final thanks  Notable quotes  “Physiology is the infrastructure of leadership and energy is the currency of performance.”  “When we decelerate, when we allow ourselves to recover, we adapt.”  “My best tomorrow starts tonight.” 

In this episode, we reflect on the most impactful themes from season eleven of the HR Data Labs Podcast, emphasizing the transformative role of artificial intelligence (AI) in the world of work. Host David Turetsky discusses how AI has become a central focus across industries, influencing regulation, data governance, organizational change, and HR practices. Tune in for a comprehensive summary of trends, predictions, and key conversations that are shaping HR’s future.  Key Topics Covered:  The dominance of artificial intelligence in season eleven and its influence on HR.  The importance of data governance for AI integration, highlighted by insights from Talenode.  Practical applications of AI, including the use of large language models and local AI hosting solutions.  Discussions with industry experts on AI ethics, security, talent acquisition, and leadership.  Predictions and insights about AI’s role and regulation in HR over the next six months and beyond.  Notable interviews with HR thought leaders discussing organizational change, burnout, women in leadership, and HR technology innovation.  Future episodes focusing on pay equity, county-level HR issues, and machine learning use cases.  Timestamps:   00:00 - Welcome and season eleven wrap-up overview 00:33 - Changes in HR over the past years and current transformations 01:31 - Introduction of chickens and personal updates 02:29 - Recap of season eleven and its focus on artificial intelligence 03:12 - AI’s influence on organizational change, trust, and data governance 03:57 - The importance of data foundations for AI initiatives 04:27 - The increasing integration of AI into daily work and business practices 04:56 - The evolution from early computer use to AI today 05:54 - The proliferation of AI tools in corporate technology stacks 06:24 - Environmental and infrastructure challenges of AI data centers 07:10 - Advances in small form factor AI hardware and local hosting options 08:07 - Real-world AI applications at the desk and secure data practices 09:34 - Building AI models with retrieval-augmented generation (RAG) techniques 10:03 - Resources available at hrdatalabs.ai and hrdatalabs.com 11:02 - Notable interviews, including legal, security, talent acquisition, and leadership insights 12:29 - Reflection on season eleven, personal connections, and upcoming season twelve topics 13:00 - Highlights from upcoming episodes, including county HR challenges and practical AI applications 14:26 - Reviewing past predictions and setting new forecasts for the next six months 15:25 - Using AI to evaluate predictions and industry trends 16:17 - The shift from AI experimentation to measurable ROI in HR 17:44 - Current state of HR AI use cases, human-in-the-loop importance, and regulatory outlook 19:11 - Predicted regulation developments at the state and federal levels 20:44 - Host’s forecast: increased progress in AI adoption and ROI validation in HR 22:36 - The impact of AI-related layoffs, rehiring, and reputational considerations 25:02 - Exciting plans for future episodes, conferences, and continued industry insights 26:26 - Appreciation for listeners and partners, and encouragement to follow the show  This episode offers a deep dive into the evolving landscape of HR technology, emphasizing AI’s transformative potential and ongoing challenges. Whether you’re an HR professional, a business leader, or an enthusiast of HR innovation, these insights provide vital context for navigating the future of work. 

In this episode, we explore the complex issue of burnout within organizations, its predictors, and how HR leaders can proactively address systemic risks that impact employee well-being and productivity. Alison Campbell, founder of Unburnt, shares her extensive research and practical strategies to recognize and mitigate burnout at every level of the organization.  Key Topics Covered:  Alison Campbell’s background and the founding story of Unburnt, highlighting her transition from corporate roles to addressing burnout  The relationship between burnout, innovation, and systemic organizational blockers  Research findings on how systemic factors like ambiguity, lack of transparency, and uncertain role definition predict burnout  The surprising discovery that highly active or visible burnt-out employees often exhibit reduced capacity for long-term strategic thinking  The impact of external stressors, demographic factors, and generational differences on burnout dynamics  Practical steps HR leaders can take: diagnostics, leadership development, board discussions, and transparent communication  The importance of viewing burnout as an organizational risk rather than solely an individual problem  How to foster a culture of open dialogue and early detection through diagnostics and ongoing conversations    Timestamps:  00:00 - Introduction to Alison Campbell and the importance of addressing burnout 02:27 - The moment that led Alison to focus on burnout and her personal journey 04:01 - Alison’s creative side and her graphic novel "HR Datadoodles" 06:16 - The research partnership with Bentley University on burnout predictors 07:44 - The link between systemic organizational risk factors and burnout 08:49 - How high burnout employees can still appear visibly active in their roles 09:39 - The significance of capacity to think strategically and translate plans into value 10:40 - The disconnect between perceived stress and actual burnout risks 12:02 - External vs internal stressors and the inability to compartmentalize life and work 13:09 - Leadership’s role in recognizing and mitigating burnout risks 14:47 - Organizational challenges in managing AI transformation and burnout 16:26 - The importance of leadership development and systemic change over siloed HR initiatives 17:50 - Lessons from early computer adoption and AI integration in the workplace 19:21 - The necessity of strategic, outcome-driven AI implementation and avoiding wasteful spending 20:31 - The role of diagnostics and ongoing measurement in early burnout detection 22:09 - The importance of communication from leadership and the board level 23:55 - Addressing the aging workforce and demographic considerations in burnout 26:49 - The impact of caregiving, obligation stressors, and generational differences 28:20 - Practical advice for HR leaders: assessing current tools, engaging with the C-suite and board 30:46 - The significance of transparent, frequent communication around organizational goals 33:55 - Final thoughts on the complexity of burnout and the need for comprehensive solutions  Resources & Links:  Unburnt Website  Research Paper on Burnout Predictors  HR Datadoodles Graphic Novel  Bentley University Center for Health and Business  Alison Campbell on LinkedIn  AI Transformation and Workplace Stress    Connect with Alison Campbell:  LinkedIn  Twitter 

In this episode, HR thought leader Tim Sackett joins host David Turetsky to explore the current landscape of artificial intelligence in HR, talent acquisition, and broader workforce management. They discuss the gap between technological potential and real-world application, legal and ethical challenges, and how government regulation could shape the future of AI in HR.  In this episode:  The real vs. perceived capabilities of AI in HR based on recent conferences and practitioner understanding  The legal issues emerging from AI use in recruiting, including Fair Credit Reporting Act concerns and litigation risks  The influence of government and regulatory bodies, with insights into new appointments like Keith Sondralin at the Department of Labor  The analogy of AI's growth and adoption to consumer products, highlighting how HR leaders can start integrating AI effectively  The untapped potential of blockchain for employee data integrity and verification in the future workforce  Practical advice on how HR practitioners can educate themselves quickly on AI basics to avoid vendor confusion  The importance of embedding AI into business and HR strategy to genuinely solve problems rather than just automate tasks  The ethical and security concerns linked to identity fraud, insider threats, and malicious use of AI for employment fraud  Timestamps:   00:00 - Welcome and episode overview on AI's impact in HR 00:48 - Insights into Tim's recent conference experiences and the state of AI learning among HR professionals 02:35 - The hype versus the real application of AI in talent acquisition 02:57 - Fun facts about Tim Sackett: a Belieber and a Swiftie 03:48 - The quality and impact of recent Super Bowl performances and music preferences 05:02 - Discussing the upcoming Rush tour anniversary and nostalgia for classic rock 06:34 - The intersection of AI and HR conference trends, gap analysis between practitioners and tech providers 07:50 - The knowledge gap in HR regarding AI capabilities and the risk of vaporware marketing 09:01 - Foundations of HR's misunderstanding of existing HR tech systems and AI's rapid evolution 11:33 - Legal challenges with AI, including Wells Fargo and Workday litigations, and compliance risks 13:07 - The potential for AI to cause or prevent legal liabilities and litigation 15:00 - New leadership at the Department of Labor and its implications for AI regulation 17:10 - Political influences on regulatory approaches and the need for national AI legislation 19:54 - Blockchain's dormant potential for workforce data sovereignty and validation 22:07 - The future of digital identity verification and the use of blockchain for employee records 24:11 - Risks of identity fraud and the importance of robust verification methods 26:22 - How AI can both combat and exacerbate identity fraud and security vulnerabilities 28:25 - Insider threats, employment fraud, and the importance of vigilance in digital security 31:10 - Strategies for HR leaders to become AI literate with minimal time investment 33:24 - The importance of understanding what "agent" and "automation" truly mean in HR tech markets 35:23 - Aligning AI initiatives with business and HR strategies to solve real problems 37:07 - Cost considerations, the hidden expenses of AI, and the importance of planning for ROI 38:48 - The "free" AI myth and the real costs of tokens, processing, and hardware investments 40:08 - The impact of AI data quality on recommendations and organizational decision-making 41:04 - Closing remarks and appreciation for Tim Sackett’s insights    Resources & Links:  Anthropic's Prompt Engineering Video  Keith Sondralin - Department of Labor  Claude AI by Anthropic  ChatGPT by OpenAI  Gemini AI by Google  The Fair Credit Reporting Act  Connect with Tim Sackett:  LinkedIn  Twitter  Note:   For HR leaders, gaining a foundational knowledge of AI is critical. Resources like Anthropic's short videos or AI primer courses can accelerate understanding and help avoid vendor hype and legal pitfalls. 

Are we staring into the abyss of a hiring chaos or on the brink of a revolution? Join us as we dive deep into the messy truth behind current job boards, AI's role in hiring, and how the market is reshaping the talent game. This is raw, real, and everything you need to understand where work is headed today.  In this episode:  The turbulence in the job board market and declining power of giants like ZipRecruiter and Indeed  How AI could finally end ghosting and improve hiring transparency  The impact of economic slowdown and slow hiring strategies on blue vs. white collar jobs  Why employer distrust is rising and how pricing models fuel the chaos  The future of smaller companies, AI assistants, and the redefinition of HR in a tech-driven world    Timestamps: 00:00 - Introduction: Unpacking the chaos in recruiting tech 02:22 - Fun facts about Chris: Kayaking and hiking adventures 04:40 - The real trouble with job boards: Struggling giants and market share battles 07:12 - Is the market slowdown due to fewer jobs or just hiring shifts? 08:41 - Employer behavior shift: Quantity over quality and ghosting culture 09:56 - AI's potential to eliminate ghosting and streamline the recruitment process 11:11 - How companies like Greenhouse are rethinking candidate experience 12:54 - The fundamental business problems facing job boards today 14:29 - Why secondary job boards are failing to overtake giants 17:50 - Trends in blue collar vs. white collar hiring challenges 19:04 - The nightmare of application processes and resume parsing 22:57 - The future of AI agents for job seekers and hiring automation 26:24 - Will smaller, more AI-driven companies dominate the future? 28:52 - How job seekers are feeling: Fear, hope, and AI optimism 30:33 - The human side of AI: From greeting cards to personalized connections 31:49 - The coming era of smaller teams powered by AI efficiency 33:35 - Creative visions: HR Data Doodles and comedy in Human Resources    Resources & Links:  RecTech Media - Follow Chris Russell for cutting-edge insights  ZIPRecruiter - The struggling giant of job boards  Indeed - Dominant market player and trends insight  Greenhouse - HR tech innovator focusing on candidate experience  Europe's AI & Data Privacy Standards - For regulatory context  YouTube: Human Resources TV Show - Satirical look into HR humor  Connect with Chris Russell:  LinkedIn  Twitter  Stay tuned for more episodes where we challenge the status quo, ignite the future of work, and boldly explore what’s next in HR and recruitment. 

Imagine a world where AI is not just a tool but a partner that elevates human judgment, responsibility, and ethics. That’s exactly what Helena Almeida, VP of Ethics at ADP, reveals in this electrifying episode, a true call to action for every HR leader and business executive. Dive into the real talk about AI governance, responsible use, and how to stay human in a tech-driven world. Your organization’s future depends on it.  In This Episode:  Helena Almeida’s journey from litigator to AI ethics pioneer.  The human side of AI: trust, hallucinations, and accountability.  How responsible AI standards are shaped by legal and ethical boundaries.  Practical advice for HR leaders: leveraging AI without losing the human touch.  The critical role of friction in HR processes to ensure fairness and accuracy.  Why AI isn’t a replacement but an enhancer — and the importance of smart design.  Navigating complex legal landscapes: pay transparency, union rules, and cross-state regulations.  How business leaders without tech backgrounds can champion responsible AI.  The future of HR workflows with AI: rethinking old processes and embracing healthy friction.  What “responsible AI” really looks like for your organization.  Timestamps: 00:00 - Welcome to the bold new era of AI in HR 02:00 - Helena’s transition from litigation to AI ethics leadership 04:00 - The myth of AI without human oversight 07:00 - Hallucinations in AI and how to manage trust 09:30 - Balancing AI accuracy with human judgment 12:00 - Ensuring data integrity in AI-driven HR systems 15:00 - Managing variations in employment law with AI 18:00 - The challenge of complex, multi-layered HR rules 21:00 - Standards for responsible AI: high stakes decisions 24:00 - The importance of skilled designers and human oversight 27:00 - The impact of automation on HR talent and friction 30:00 - How business leaders can lead AI governance without technical expertise 33:00 - Rethinking HR workflows for AI integration 36:00 - Healthy friction: the secret to responsible AI in HR 38:00 - Final thoughts: humans and AI working together for better workplaces Resources & Links:  ADP  Helena Almeida - LinkedIn  Responsible AI Guidelines  Book: "Human + Machine" by H. Simmons  Connect with Helena Almeida:  LinkedIn  Twitter  Final Call: The future of HR is human. The future of AI is responsible. You have the power to shape both. Listen now — and be bold enough to lead with integrity, insight, and purpose. 

An Intimate Conversation with Mark Stelzner Delves into a candid, passionate exploration of how the landscape of HR, business, and leadership has transformed over two decades. Mark Stelzner shares raw insights about the accelerating pace of change, the rise of AI, and the shifting dynamics of organizational survival.  In this episode:  The relentless acceleration of business change and its impact on leadership (00:50)  Why traditional five-year plans are now laughable and what that means for HR (07:20)  The profound influence of social and digital currency on organizational momentum (08:14)  How disruption is no longer an exception but the new normal, BlackBerry to Apple (09:45)  The rise of holding companies and the collapse of monolithic giants (11:05)  Navigating complexity factors and the importance of agility over size (12:30)  The real story behind beta and growth opportunities in turbulent times (13:42)  The amplified role of HR as a strategic, pivotal driver of organizational resilience (28:10)  The shift from administrative to strategic HR—what is lost, what is gained (39:45)  The evolving role of AI in HR operations and strategy (42:36)  Mark's reflections on two decades of growth, adaptability, and leadership (43:11)  The urgent need to rethink HR's purpose and practices in this fast-changing era (39:16)    Resources & Links:  Mark Stelzner on LinkedIn  IA Consulting  Amazon: "The Innovator's Dilemma" by Clayton M. Christensen    Connect with Mark Stelzner:  LinkedIn  Twitter  This episode is an unmissable journey through the raw truth of transformation, resilience, and the relentless pursuit of relevance in an ever-evolving world.   Prepare to challenge your assumptions and ignite your passion for change. 

This episode dives deep into the transformative power of AI in bridging the communication chasm between HR leaders and frontline employees. Brodie Meyer shares candid insights on how a simple SMS strategy turned into a revolutionary tool that improves engagement, safety, and retention, proven among industries that most need it. In this episode:  Brodie's journey from blue-collar roots to HR tech innovator  The story behind YourCo, a frontline employee communication platform  Why traditional tools failed frontline workers and how SMS changed the game  The magic of two-way texting and real-time conversations  Metrics revealing improved engagement: from immediate reach to 86% two-way after 90 days  The tangible outcomes: decreased turnover, higher safety, and increased productivity  The strategic use of AI: frontline insights and sentiment analysis  Practical advice: meet employees where they are on their devices and habits  Brodie’s thoughts on AI’s role in scaling HR communications effectively  Timestamps: 00:33 - Welcome to the HR Data Labs podcast with Brodie Meyer 01:08 - Meet Your Co: transforming frontline communication in traditional industries 02:14 - Brodie's personal motivation and background 03:01 - Juggling family and startup life with new born Nolan 04:12 - Brodie’s fun fact: love for Italian cooking 05:32 - The gap between HR and frontline workers — origins of the idea 06:15 - Struggling with Slack in blue-collar environments 07:55 - The breakthrough: SMS as the go-to communication channel 08:29 - Why texting works: older devices, language barriers, and habits 11:11 - Building a two-way platform that’s accessible and effective 12:05 - Employee and management feedback: engagement truths 13:05 - Impact: exceeding expectations and improving workforce sentiment 14:33 - Scaling solutions for large enterprises while maintaining engagement warmth 15:38 - Metrics: Achieving 86% two-way engagement after 90 days 16:52 - The importance of real conversations with frontline staff 17:39 - The ROI focus: reduced turnover, safety, productivity improvements 19:57 - AI in frontline communication: frontline intelligence and sentiment analysis 21:24 - Ensuring data accuracy and transparency with citations 23:08 - Practical advice: meet employees where they are to unlock results 23:43 - Closing thoughts and the power of meeting employees where they truly are. Resources & Links:  Your Co -The frontline communication platform transforming industries  Book: HR Transformation by John Smith  Brodie Meyer - LinkedIn | Twitter  AI & Sentiment Analysis Tools — Google Cloud AI  Connect with Brodie Meyer:  LinkedIn  Twitter    End on this:  If you want to revolutionize HR and frontline engagement, meet your employees where they already are, on their phones, their language, their habits. That’s the secret sauce to unlocking productivity, safety, and retention at scale. Don’t just imagine it, do it! 

Dive deep into the messy truth about recruiting today, where human laziness, outdated systems, and misguided AI tools collide. Find out how smarter strategies and better incentives could revolutionize talent acquisition and HR. In this episode:  How AI amplifies bias and noise in recruiting, not fixes it  The pitfalls of traditional assessment methods and the rise of work trials  Why incentive structures for recruiters need a massive overhaul  The future of gig and flexible work in talent sourcing  Practical ways AI can enhance matchmaking, not replace human connection  The importance of evolving HR processes alongside new tech tools  The potential for independent recruiters to change the game  Timestamps: 00:00 - Welcome and intro to today's hot topic in HR 00:32 - Meet John Kim: CEO of ParaForm, HR innovator 01:03 - John’s background and why mobility shaped his worldview 02:39 - The superpower of adaptability from constant moving 03:27 - Why AI often worsens recruiting chaos instead of fixing it 04:56 - The noise problem: How AI creates more applications and confusion 05:53 - The laziness behind superficial hiring practices 06:47 - How current metrics incentivize shortcuts in recruitment 08:33 - Using AI to address asymmetries and better assess candidates 10:36 - The evolution and necessity of performance-based assessments 12:01 - On-site work trials and mutual company-candidate evaluation 13:00 - Speed dating vs panic room: new interview models 14:14 - The discipline gap in talent acquisition teams 15:27 - The role of AI in transforming candidate and recruiter interactions 16:02 - Can AI really match candidates with limited data? 18:12 - The importance of data quality in AI-driven hiring 19:30 - Changing transparency around candidate and employer feedback 20:00 - How platforms like ParaForm align incentives for better matches 22:08 - Rethinking recruiter compensation models for higher quality hires 23:23 - The potential of independent recruiters for more outcome-focused hiring 25:57 - Balancing internal teams and external experts for best results 28:32 - How AI can reduce recruitment grunt work and increase efficiency 30:36 - The shift to gig, contract, and flexible work models 33:01 - Lessons from HR’s past mistakes and the need for continuous learning 35:28 - Harnessing the power of new tools and tech in HR evolution. Resources & Links:  ParaForm  Upwork  Fiverr  Connect with John Kim:  LinkedIn  Twitter  Feel the energy? It’s time to rethink your hiring game, embrace automation, challenge old norms, and prioritize real human connection. The future of talent acquisition depends on it. Now go out there and lead the charge! 

Hold tight. Today’s episode? It’s a wild ride through the chaos and clarity of AI in the workplace. We’re digging into how HR and leaders can embrace innovation without shooting themselves in the foot. If you're feeling overwhelmed or skeptical about AI boundaries, this is your reality check and rally cry all in one. In this episode:  The true impact of hotels on community and human experiences  The metaphor of AI tools as gym equipment—hidden potential and the importance of guidance  Guardrails around AI: costs, ethics, and performance illusions  Why access to AI is a must—no gates, no barriers, big opportunities  The need for specific training versus generalized skepticism  The parallel between AI in education and employment—breaking down misconceptions  How we should focus on the results not just the means  Timestamps: 00:00 - Meet Carlee Wolfe: HR leader redefining talent and organizational effectiveness 01:12 - The heart of hospitality: impact on community & human connection 02:16 - Hotels as spaces for life's biggest moments—marriages, tragedies, celebrations 03:32 - How hotels influence local economies & culture 04:59 - The fascinating kosher hotel fact in Chicago—layered infrastructure and community needs 06:25 - Carlee’s fun facts—skydiving, bungee jumping, and the importance of knowing your limits 09:38 - What’s rattling Carlee’s mind for 2026? The future of AI, HR, and disruption 10:22 - Guardrails on AI: costs, ethics, and misconceptions about performance 12:10 - Why restricting AI access can hinder performance—and why that’s a mistake 13:33 - Rethinking performance metrics in the age of AI: productivity, quality, and innovation 14:02 - The risk of private vs. corporate AI use—leaking secrets or gaining speed? 15:02 - The training gap: equipping your team to harness AI effectively 17:21 - The gym metaphor: AI tools as machines—and the overlooked ‘back of the gym’ space 18:46 - Building a culture around exploration & experimentation in AI adoption 19:34 - The variety of AI ‘machines’: Claude, Perplexity, ChatGPT—the importance of understanding differences 21:08 - How applicants and employers can use AI ethically & effectively in hiring 23:24 - Education’s role: from cheating to enhancing learning using AI tools 24:55 - Embracing AI as a workforce builder, not a barrier—why resistance stalls progress 25:24 - The evolution of research & referencing—AI as a thinking partner 26:19 - The importance of maintaining mental agility—training the muscle, not just the machine 27:04 - Results over methods: why focus on outcomes? Resources & Links:  Book: Human + Machine: Reimagining Work in the Age of AI by H. James Wilson & Paul R. Daugherty  GPT-4 by OpenAI  Claude AI  Perplexity AI  Connect with Carlee Wolfe:  LinkedIn  Twitter  This episode is a bold call to see AI as a tool, not a threat. Change your mindset, unlock your potential, and remember, you get to choose whether AI becomes your crutch or your launchpad. Stay curious, stay bold. The future is yours to shape. 

Get ready to unleash a surge of passion, truth, and bold insights on how AI is revolutionizing people analytics. Cole Napper, a true luminary in the space, shares the raw reality of data's power, pitfalls, and the brave new world ahead. Buckle up, this isn’t just a podcast; it’s a rallying cry for HR and analytics pros to lead with purpose.  In this episode:  How far has people analytics come since its early days  The impact of COVID and AI on credibility and practice  Why analytics teams are transforming into the future of HR  The role of AI in automating dashboards, insights, and decision-making  The importance of trust and ethical data use in predictive models  How to navigate data quality issues that threaten decision accuracy  Why the next wave is about people intelligence rather than simple reporting  Practical advice for HR teams deploying AI safely and strategically  Timestamps:  00:26 - Intro: The evolution of people analytics & Cole Napper’s background 01:08 - The roots and rise of HR analytics before AI became a buzzword 03:22 - The tremendous journey: from skepticism to credibility in analytics 04:38 - How COVID accelerated AI’s role in HR decision-making 05:07 - Influential luminaries shaping the analytics field 05:57 - Richard Rosenau’s pioneering efforts in analytics recognition 06:43 - The digital impact: How analytics influence real-world change 07:12 - Paying it forward: The importance of community and mentorship 08:15 - The torch carriers: Keeping analytics alive through new generations 09:00 - The threat of layoffs and AI’s false promise to replace analytics teams 09:48 - Recognizing the upcoming AI boom in HR and people analytics 11:09 - The challenge and opportunity: Organizing analytics teams in turbulent times 12:33 - The shift from building dashboards to strategic people intelligence 13:11 - Why risk-taking and experimentation are vital in transformative times 14:16 - The importance of trust, ethics, and human oversight in AI deployment 15:11 - The commoditization of data skills and the rise of strategic role of people intelligence 16:49 - How AI is changing the way we get notified and interact with insights 18:08 - The problem with push notifications and how to create demand for insights 19:41 - The true nature of predictive analytics: asking behind the questions 20:36 - The importance of context, data quality, and avoiding flawed signals 23:25 - The exponential evolution of data speed and the shrinking time to insights 28:17 - The real challenge: acting on predictions without destroying trust 30:23 - The costs of AI: tokenomics, data bills, and strategic investment 33:11 - The greatest data pitfall: messy, unclean HR data and its impact 36:39 - Embracing “Directionally Correct” — the pragmatic path forward 37:42 - The art versus science of compensation data 38:12 - The ultimate focus: solving the business problem 38:41 - Closing thoughts: leadership, trust, and being bold in AI-driven HR  Resources & Links:  People Analytics: Reinventing HR & Work with AI  Cole Napper - LinkedIn  HR Bench  Directionally Correct (Newsletter & Podcast)  Connect with Cole Napper:  LinkedIn  Twitter 

Get ready to have your perspectives shattered. Peter Laughter, a visionary in leadership and organizational strategy, dives deep into why traditional command-and-control models are crumbling and what leaders, especially in HR must do to adapt. This isn't just theory, it's a call to action, a blueprint for survival in the chaos of modern business.   In this episode:  The fundamental flaws of command and control leadership in today’s complexity  How HR can measure and diagnose organizational failures before they explode  The transformative power of distributed leadership and democratized decision-making  Why modern technology can be the key to faster, smarter, more human organizations  The importance of listening to frontline voices and creating a culture of challenge    Timestamps:. 00:33 - Introduction to Peter Laughter's perspective on leadership 01:18 - Peter’s background in entrepreneurship and social impact focus 02:03 - The failure of command and control in complex environments 02:46 - HR’s role in creating new leadership pathways 03:18 - Fun facts: Peter’s brief career as an anthropologist 04:06 - Organizations hiring anthropologists to make tech more human 06:34 - Why current HR data metrics might be missing the mark 07:13 - Redesigning data measurement for complex systems 09:24 - The importance of tracking decision-making and response times 10:36 - The concept of Hubers Syndrome and organizational blindness 11:00 - Fail-safes and organizational feedback loops 12:14 - The impact of hierarchy on information flow and decision quality 13:17 - The challenges of speaking truth to power in leadership 14:36 - Military’s command flexibility vs corporate rigidity 15:04 - How frameworks and decentralization empower in decision-making 16:12 - Democratizing data and challenging old hierarchies 17:11 - The power of honesty and courage in leadership meetings 19:45 - The rise of entrepreneurial spirit sparked by workplace constraints 20:47 - When command and control fails in top organizations and why leaders are slow to react 24:10 - The changing cultural landscape and the craving for authentic leadership 27:22 - How distributed leadership models accelerate change 29:02 - Success stories of flat, autonomous organizations like Valve 33:00 - Measuring cultural shift and ethos through data 34:38 - Frontline engagement as a predictive metric for organizational health 36:25 - The critical role HR plays in shaping adaptive, resilient organizations 36:40 - Final thoughts: The urgency for HR to lead disruption and innovation  Resources & Links:  Valve’s Handbook – Flat organization & manager-free culture  Greg Sattel - Cascades – Principles of distributed leadership  Turn the Ship Around by David Marquette – Leading from the point of decision  Total Quality Management & Deming – Foundations for organizational excellence  Jenny’s Ice Cream & Zoe Schweitzer – Frontline leadership in HR  Connect with Peter Laughter:  LinkedIn  Twitter  Ready to shake up your leadership and HR strategy? It’s time we move from fear-based hierarchies to trust-based, innovative organizations. The future is calling, will you answer?

Hold onto your seats, this episode cracks open the truth about AI and the workforce like never before! Mike Ohata shares his bold insights on how AI isn’t here to replace us but to transform how we lead, learn, and live. This isn’t just about automation; it's about human capability, culture, and daring to rethink everything. In this episode:  Why AI’s doom-and-gloom narrative is superficial and how human leadership remains vital  The real impact of AI on task automation versus redesigning work systems  How to cultivate systems thinkers instead of linear learners in a rapidly evolving workplace  The critical importance of judgment, empathy, and entrepreneurial skills in tomorrow's workforce  Rethinking talent development: from skills inventories to ontologies that connect competencies  The role of leaders in embracing AI with agility, curiosity, and ethical responsibility  How AI can enable trade skills and encourage entrepreneurial thinking among trade professionals  Navigating the tension between short-term cost cuts and long-term talent sustainability  Why cultural fit and values matter more than ever in AI-driven organizational change  Timestamps: 00:00 - Introduction: Why this episode changes your view on AI and the future of work 01:22 - Mike’s background: Learning environments in professional services and talent development 03:30 - Fun fact about Chuck Todd and political anthropology as a lens for leadership insights 04:49 - The core dilemma: Is AI a threat or an opportunity for organizations? 05:01 - Debunking the AI doom narrative: Tasks vs. systems redesign 06:10 - The integral role of human-AI collaboration in future work 07:26 - Are current automation efforts just "lift and shift"? Or are they a chance to reinvent work? 08:49 - The profound implications of AI for leadership and systemic thinking 09:45 - Risks of resistance and misconceptions about AI adoption in the workplace 10:16 - Human skills like prompting, framing, and judgment as key in AI utilization 11:49 - Protecting institutional knowledge and combating ageism in AI integration 13:24 - Educational shifts: From memorization to systems thinking 14:34 - Leadership development for a connected, systemic mindset 15:07 - How easy answers can mislead us in AI’s era of complexity 16:41 - Redefining success: Outcome over process in a world of AI tools 17:08 - The evolving nature of regulated and unregulated work with AI 18:43 - Customer empathy, judgment, and the lasting importance of human touch 20:36 - The challenge of engaging frontline and hourly workers with AI and automation 21:53 - Is enterprise AI adoption a short-term cost play or a strategic transformation? 26:17 - What we’re really automating: From low-level analysis to high-level talent strategy 30:11 - The essential role of entrepreneurial skills for trade and technical professions 32:23 - Using skills inventories and ontologies to future-proof organizations 36:25 - Reskilling versus layoffs: How purpose and objectives shape talent decisions 37:51 - Beyond short-term profit: The long-term value of investing in people and culture 40:28 - Ethical considerations, collective values, and navigating AI’s future challenges Resources & Links:  Book: Human + Machine: Reimagining Work in the Age of AI by H. James Wilson & Paul R. Daugherty  Mike Ohata - LinkedIn  Understanding Ontologies in Skills & Competencies  AI and Leadership: The Next Frontier – Harvard Business Review  The Future of Work in the Age of AI – McKinsey Report  Connect with Mike Ohata:  LinkedIn  Twitter  Note: This episode is a rallying cry to foster human-centric, ethical AI adoption, challenging the status quo and empowering organizations and individuals to adapt boldly. 

Are you tired of outdated, ineffective performance reviews? Want your organization to thrive with motivated, aligned employees? This episode dives deep into transforming your performance management process into a powerhouse that drives results and engagement. Join us as Bruce Cohen, a seasoned HR leader, shares decades of insights from goal-setting to AI-driven tools and how to implement a system that’s continuous, clear, and compelling. In this episode:  Why top companies prioritize ongoing performance feedback  How to cascade goals effectively from leadership to every employee  The critical difference between job descriptions and goals  Using AI to enhance accuracy, consistency, and personalization  The role of senior leadership support and leading by example  Practical tips for managing self-assessments and overcoming recency bias  The future of performance management with AI and data insights  Timestamps:  00:00 - Why performance management is crucial in 2026 and beyond 00:26 - Bruce Cohen introduces himself and his HR background 01:23 - The value of continuous feedback in employee motivation 02:33 - The importance of goal setting and clear communication 05:39 - The risks of infrequent reviews and how to shift the culture 08:01 - Upskilling managers for real-time coaching and feedback 10:14 - Leading with example in HR and organizational commitment 11:40 - Defining "best in class" performance systems 12:33 - Aligning goals with company objectives through cascading 15:22 - Using self-assessments to prepare for performance conversations 18:44 - Overcoming challenges with recency bias and self-evaluations 21:43 - The multiplier effect of ongoing feedback 25:17 - The transformative role of AI in performance management 28:23 - Practical steps for implementing AI tools effectively 33:48 - Five key steps to elevate your system post-episode Resources & Links:  eCornell Organizational Design and Performance Courses  Book: "Radical Candor" by Kim Scott  AI Tools for HR and Performance Management  Leadership Support in HR  Connect with Bruce Cohen:  LinkedIn  Twitter    Let's revolutionize performance management together! Take these insights, leverage new technologies, and lead your organization to a more engaged, productive future. The time for change is now, don’t wait for the next review cycle to start transforming your system. Start today! 

Are women stepping into leadership roles with the respect, tools, and support they deserve? This episode dives deep into the critical challenges female CEOs face in 2026, from societal biases to systemic barriers, and how we can change the narrative for future generations. In this episode: Christy Brown shares her inspiring journey from corporate to entrepreneur, and her mission of empowering women in leadership. The stark realities: Only 11% of Fortune 500 CEOs are women, and the gender pay gap still lingers at 72 cents on the dollar. The unique challenges women encounter, including stereotypes, motherhood penalties, and systemic roadblocks. The societal and political headwinds hindering progress, from DEI rollback trends to eroding reproductive rights. The power of community, mentorship, and sponsorship in transforming the leadership landscape. Practical strategies women can adopt: building confidence, self-respect, and support networks that reinforce their value. The urgent need for systemic change so women can compete and lead on an equal footing, free from outdated norms and misogyny. Timestamps: 00:00 - Welcome and episode overview 00:50 - Christy Brown’s background and entrepreneurial journey 02:33 - The innovative work of Dr. Nose and its societal impact 06:15 - Personal fun fact: fundraising through a 31-mile dog walk 08:11 - Challenges for women CEOs in 2026: statistics and systemic issues 09:45 - Representation gap and pipeline problems in leadership roles 11:33 - Motherhood penalty and caregiving stigma 12:39 - Cultural conditioning and societal stereotypes 14:24 - The state of gender pay gap and pay transparency in 2026 16:00 - The global perspective and the importance of representation 17:14 - The impact of role models on young women and girls’ ambitions 19:25 - Creating aspirational standards and societal goals for gender equity 22:06 - Combating misogyny, societal biases, and outdated gender roles 25:20 - The importance of confidence, self-worth, and community support 28:12 - Building networks, mentorship, and sponsorship to empower women 33:15 - Resources and communities available for female founders and CEOs 35:09 - Final thoughts and call to action: changing the narrative for a better future Resources & Links: Dr. Nose — Innovating pediatric wellness at home Gizuota Business School — Startup accelerator supporting entrepreneurs American Cancer Society — Fundraising and advocacy efforts UN Gender Equality Data — Global gender equality insights Women’s Startup Resources — Support networks for female entrepreneurs MentorSpaces — Finding mentorship and sponsorship programs Connect with Christy Brown: LinkedIn Twitter Let’s rewrite the story of leadership, because the world needs more women leading boldly, with respect and power. It starts now.

Dive into the raw truth of HR analytics, why it’s all about storytelling backed by solid numbers. This episode uncovers how HR leaders can finally translate their human capital efforts into undeniable business value. Prepare to be inspired, challenged, and energized to rethink what your HR data can do!  Key Insights  The gap between HR stories and financial impact is real; HR needs to quantify their contributions.  Successful organizations are integrating HR metrics with business and financial data for compelling storytelling.  External benchmarks are critical to understanding where your organization stands are you best in class or in need of improvement?  Using visualization and advanced analytics makes complex data accessible and impactful for HR leaders.  Building tight collaborations with operations and finance is essential for accurate, meaningful HR metrics.  Small steps like analyzing turnover costs or onboarding ROI can start a powerful transformation.  HR must embrace a mindset of continuous measurement, storytelling, and adjusting based on macroeconomic shifts.  Investing in analytics tools and skills early helps HR lead from a position of influence and credibility.  Timestamps  00:00 - Welcome & intro to Schon Parris, HR data rockstar 02:45 - Schon’s musical side and leadership journey at ADP 03:58 - Helping HR quantify workforce value through analytics 04:40 - The gap between HR stories and quantifiable business impact 05:34 - Why HR struggles to show ROI like sales or operations 06:39 - Bridging HR and finance through better skills and tools 07:32 - How AI and advanced analytics are changing the game 09:02 - Turning HR metrics into financial and business outcomes 10:02 - The importance of collaboration in understanding turnover costs 11:01 - Performance metrics for hourly workers and ubiquitous data 12:13 - The challenge of rolling up workforce data in organizations 13:10 - Building business cases for HR investments 14:16 - The power of visualization and storytelling with analytics 15:04 - Using metrics to tell compelling, data-backed HR stories 17:15 - The importance of granular data to prevent surprises 18:30 - Small steps that HR can take to demonstrate value 20:10 - Putting the numbers into business language for leadership 21:43 - Using external benchmarks to inform strategy 23:08 - Visual storytelling to connect HR efforts with profitability 24:15 - Deep-diving into specific workforce segments 25:03 - Tracking HR impact continuously, not just quarterly 26:40 - The importance of contextualizing data within macroeconomic shifts 27:57 - Steps to start building a data-driven HR culture  Resources & Links  How to Measure HR’s Impact on Business  Power of Data Visualization in HR  Turnover Cost Analysis Tool  External Benchmarks for HR Metrics  Connect with Schon Parris  LinkedIn  Twitter  Final Thought  This episode is a rallying cry for HR leaders to step into their data-driven power. Metrics are no longer optional,they are the language of impact and influence. Start small, visualize boldly, and tell your stories with undeniable proof. Your workforce’s true value depends on it!

 Discover how a bold new approach to evaluating performance could revolutionize your organization. Jacob Chase shares groundbreaking insights on moving away from traditional systems to fully leverage collective intelligence, fairness, and meritocracy.   Main Topics Covered:  Why current centralized performance reviews are broken and how decentralization offers a solution  How stock market principles apply to internal organizational valuation  Building a culture of transparency through peer-to-peer feedback systems  Transforming pay equity via contribution-based assessments  Practical steps for leaders to pilot decentralized evaluation methods    Timestamps:  00:31 - Introduction to Jacob Chase and his background 01:34 - The story behind Infin and its purpose 02:23 - Fun fact: Jacob's chaotic car and the humor of parenthood 03:34 - The core topic: valuing organizational contribution beyond traditional pay structures 04:33 - What is pay equity in modern terms? 05:29 - The problem with centralized evaluation systems and the benefit of decentralized approaches 06:45 - How individual perspectives enrich performance assessment 08:27 - Learning from stock markets: decentralized valuation models applied internally 09:32 - Creating internal markets for credit attribution within organizations 10:00 - How collective intelligence can self-assess performance 10:46 - Safeguards and motivations in decentralized data collection 12:01 - Peer feedback, confidentiality, and fostering a feedback culture 13:21 - Cultural shift required for decentralized evaluation to succeed 14:01 - How performance data can shape careers and future growth 14:37 - Quantifying contributions versus narrative assessments 15:06 - Replacing traditional evaluations with real-time performance insights 16:20 - Using data to improve workforce decisions and recognition 17:05 - The econometrics of contribution and how it enables meritocracy 17:58 - The importance of true merit-based rewards and reducing bias 18:52 - Moving beyond incremental changes—wholesale transformation needed 19:12 - Practical steps for HR and leadership to pilot decentralized systems 22:01 - Starting with the executive team to build credibility 23:08 - Overcoming the fear of transparency and trust issues 24:06 - Long-term benefits: Fairness, transparency, and organizational excellence 24:44 - The power of fairness in motivating exceptional contribution 26:01 - Final thoughts: embracing decentralized performance for competitive advantage   Resources & Links:  Infin Platform  Stock Market as a Model for Internal Valuation  Performance Management Systems: Why They Fail  Build a Culture of Feedback    Connect with Jacob Chase:  LinkedIn  Twitter    Unlock the Future of Performance Management Today!  This isn’t just a reset, it’s a revolution. If you’re ready to empower your team, eliminate bias, and create truly fair compensation, start with a bold step: decentralized, contribution-based evaluation. The future is fair, transparent, and driven by collective intelligence. Will you lead the change? 

This episode dives deep into a critical issue that affects nearly 80% of the workforce, substance use disorder (SUD), and explores how HR professionals and organisations can lead the change. Get ready for an eye-opening conversation filled with practical steps, inspiring examples, and a powerful message: supporting employees through recovery is not just compassionate, it’s strategic. In this episode: Amy Dufrane reveals why substance abuse is a silent epidemic impacting organizations across all sectors The startling statistics surrounding SUD and its toll on productivity and healthcare costs How organizations are pioneering recovery-friendly workplace certifications and initiatives Practical advice for HR on cultivating a supportive, stigma-free environment The importance of education, policies, and manager training for long-term organizational health Resources for organizations to implement real change—without reinventing the wheel Timestamps: 00:00 - Welcome and introduction to Amy Dufrane, CEO of HRCI 00:24 - Amy’s background and passion for HR’s evolution 02:09 - Why substance use disorder is a critical issue for HR and employers 04:01 - The impact of SUD on productivity, turnover, and healthcare costs 05:28 - Understanding SUD as a chronic condition, not a choice 06:23 - How HR can start addressing substance abuse in the workplace 07:11 - Navigating HIPAA and legal considerations around employee health disclosures 08:39 - Partnering with organizations like Global Recovery Initiatives Foundation for education and certification 10:00 - The role of company certification and building a recovery-friendly culture 11:14 - Why leadership commitment is essential for change 12:44 - The importance of manager training and creating safe communication channels 15:08 - Overcoming organizational culture and resource barriers 16:08 - The long-term investment in employee wellbeing and organizational health 17:00 - The non-legal, human-centered approach to supporting employees in recovery 17:59 - How organizations can get started with certification and resources 21:07 - Practical first steps for HR and leadership 22:24 - The importance of proactive, organizational commitment over reactive responses 23:05 - Final advice for CHROs and leaders to prioritize this issue 23:44 - Gratitude and closing thoughts. Resources & Links: National Recovery Friendly Workplace Institute — Certification and tools for creating recovery-supportive workplaces HRCI — Certification and education for HR professionals White House Initiative on Substance Use — Government leadership in supporting workplace recovery efforts Connect with Amy Dufrane: LinkedIn Twitter Take Action: Start today by educating your leadership and HR team about SUD Explore certification programs to build a recovery-friendly culture Implement ongoing training for managers to recognize and support employees Remember: your organization’s health depends on your compassion and commitment. Let’s break the stigma and embrace a future where recovery is supported and celebrated.

Get ready to challenge the status quo. In this episode, Jess von Bank and David Turetsky confront the fast-paced AI revolution, urging us to see beyond profit and speed. They reveal why women’s voices should lead our design decisions, advocating for a human-centric approach in a world speeding towards automation and loss of trust. In this episode: Why current AI development prioritizes efficiency over human values The critical need for women to be at the center of AI design and decision-making How capitalism’s extraction model is hollowing out jobs across demographics The dangers of unregulated AI—bias, privacy breaches, and ethical mishaps Examples of AI’s impact in HR—from recruitment to unconscious bias The importance of governance, transparency, and interruptibility in AI systems Practical ideas for democratizing skills and opportunities through AI How to shift from reckless adoption to intentional, human-first AI strategies   Timestamps: 00:00 - The mission to center womenin AI design and HR innovation 02:05 - Jess von Bank’s journey from talent practitioner to industry analyst 06:21 - Why fast AI development risks sacrificing human values 09:01 - The false promise of EQ-focused AI and the need for broader perspectives 10:07 - Designing for safety and well-being: lessons from parenthood and Maslow’s hierarchy 13:34 - Rethinking social media and AI with a human lens in HR tech 16:21 - The hollowing out of middle and entry-level jobs due to AI 17:19 - Demographics impacted by AI-driven job displacement and systemic inequality 20:16 - The role of governance in protecting human interests and privacy 22:39 - The risks of unchecked data collection and the “out-of-control” AI genie 25:06 - The hidden costs of convenience—the loss of trust and control 30:34 - Rethinking success: measuring meaningful progress, not just adoption 34:41 - Real-world examples: democratizing recruitment through AI and reducing bias 37:08 - Opportunities to support displaced workers with AI-driven skill matching 39:39 - The call for slower, human-centered AI innovation to avoid future catastrophe   Resources & Links: Book: The Future of Work by Jack Zenger Jess von Bank - LinkedIn | Twitter Capita AI Governance Framework HireVue video interview platform TikTok’s addictive content studies   Connect with Jess von Bank: LinkedIn Twitter Join us in reshaping HR and AI—center human values, demand transparency, and slow down the rush. Our future depends on it.

In this electrifying episode, Charlene Li shares her insights on how AI is transforming HR strategies, leadership, and the very way we define jobs in this rapidly evolving landscape. Get ready to rethink what’s possible and how you can take immediate steps toward an AI-empowered future.Key Topics: Why start AI initiatives with your business strategy, not the technology itself How AI can support and revolutionize HR functions like recruitment, team building, and workforce planning The importance of asking the right questions to harness AI effectively Rethinking "entry-level" in the age of automation and AI-enabled skills Building a foundational, invisible layer of AI that drives everyday workflows without flashy interfaces The ethical responsibility of HR to lead AI adoption responsibly and transparently The shift from traditional roles to "superhuman" workers enhanced by AI tools Strategies for HR leaders to prepare their teams for AI-driven change The critical need for deep conversations with vendors and internal teams to shape meaningful AI solutions Curiosity and critical thinking as the ultimate skills in the AI era Winning with AI: The 90 Day Blueprint for Success Charlene Li - Website OpenAI - Developer Resources Perplexity AI LinkedIn Twitter Timestamps: 00:00 - Welcome & Introduction to Charlene Li’s background 02:00 - Disruptive transformations and the leadership needed for AI success 06:00 - Where to start with AI in HR and aligning with business strategy 08:00 - Rethinking HR processes and outdated data practices 11:00 - The role of nuanced skills and team chemistry in a new AI-powered workplace 12:45 - How AI tools assist in hiring, team collaboration, and decision-making 19:00 - Human in the loop vs. automation – when and how to let go 20:40 - Redefining the role of humans in AI-enhanced organizations 24:00 - The strategic role of HR in AI ethics, transparency, and future workforce development 28:00 - Building an AI roadmap, vendor conversations, and responsible adoption 31:00 - The skills needed to ask the right questions in the AI age 34:00 - Experimenting, failing fast, and continuous learning with AI 36:00 - The importance of curiosity, imagination, and specialized expertise 36:30 - Almost out of time, a recap of Charlene’s book, Winning with AI 37:13 - Final thoughts & actionable steps for HR leaders to lead AI transformationResources & Links:Connect with Charlene Li:Call to Action: Don’t wait for the future to arrive — start asking better questions today! Grab Charlene Li’s Winning with AI to kickstart your 90-day strategic plan. Lead your organization boldly into this new era, because your role is more crucial than ever. The future of HR is here — are you ready?

Discover the transformative power of applying Amazon’s working backwards framework to HR. This episode unpacks how HR leaders can turn employees into loyal customers and leverage AI to create impactful HR products that truly delight. If you're ready to revolutionize your HR tech game, listen now! Timestamps:00:00 - Introduction to applying Amazon’s customer obsession in HR02:00 - Historical perspective: Dell’s direct approach as employee-internal customer model06:00 - Justifying HR technology investments with ROI examples from compensation software11:00 - The five questions of the working backwards framework12:00 - Constructing a true customer persona & insights from HR data15:00 - Defining the core customer problem in HR: Building confidence in managers16:30 - Crafting solutions & benefits — example of an AI-powered coaching tool19:00 - Writing the future press release & internal FAQs to clarify the product vision21:00 - Iterative testing & how to involve stakeholders in feedback cycles24:00 - Measuring success & validating assumptions through prototypes & beta tests26:00 - How AI accelerates customer understanding & innovation in HR28:00 - Making HR a product team: influencing leadership & fostering customer obsession30:00 - Conclusion: Start small, ask questions, test assumptions, and keep the customer at the heart

Are you ready to feel the heartbeat of what's next in HR technology? In this episode, Oz Khan from ADP Ventures pulls back the curtain on how AI is transforming workflows, building trust, and reshaping the very fabric of work. This isn’t just talk — it’s a revolution happening right now, and you need to hear it. In this episode: The evolution from AI assistance to autonomous workflow execution Why HR is shifting from co-pilot to control tower — and what that means The critical importance of trust, compliance, and risk management in AI adoption How enterprise complexity and trust influence product development and investment The overlooked power of judgment — why human experience remains priceless The strategic focus of investors and founders navigating AI’s wild waters Real-world examples: ADP’s scale, the impact of startups like Naya and Emma The role of people, process, and tech — and how they coexist in solving real HR problems Timestamps: 00:00 - The pulse of HR innovation — what’s coming next 02:10 - How ADP’s labs culture sparked real growth 05:10 - Oz shares a fun, surprising fact about himself 06:10 - The seismic shift from AI tools to workflow automators 08:25 - How stability and proven value shape HR tech adoption 09:42 - The co-pilot becomes the control tower — deep dive 11:00 - APIs, data connectivity, and solving enterprise complexity 12:44 - Navigating compliance, risk, and the law in HR AI 13:51 - Why generative AI isn’t ready to replace humans yet 15:54 - The real challenge of trust: transparency, training, guardrails 17:46 - The importance of judgment and experience in AI-driven decision making 20:40 - Building confidence with high-fidelity, deterministic AI solutions 23:38 - The last mile decision — where human judgment still rules 26:11 - The dangers of overhyping AI’s potential — and the truth 29:52 - Education, skills, and the demographic shifts AI will bring 33:53 - The art of flexible, configurable HR tech — how founders navigate ‘craft’ 37:16 - From $1M to scale — what it takes to grow AI-driven HR solutions 42:56 - Real-world impact — ADP’s investments in Naya, Emma, and beyond 43:38 - The human side: solving emotional and organizational problems, not just tech 44:22 - The future is OpenClaw and beyond — what’s next in AI bots Resources & Links: Naya — Transforming benefits decisions at scale Emma AI — Agentic platform powering workflows ADP Ventures — Driving innovation in HR tech Data Cloud Stanford Research — Insights on entry-level hiring and labor shifts ADP — Join the leaders in HR and payroll solutions Connect with Oz Khan: LinkedIn Twitter This isn’t just a conversation — it’s a call to action. Whether you’re in HR, investing, or building the future, you’ve got to understand the truth about AI’s power, limits, and the human judgment that will always be king. Don’t get left behind. Your next big move is waiting — listen now, and be part of the revolution!

Are we truly prepared for the dark side of AI in talent acquisition? In this episode, my great friend, Dara Brenner from Employ drops truth bombs about candidate fraud, the evolution of AI governance, and how organizations can stay ahead in this high-stakes game. If you're a leader in HR or recruiting, this is your wake-up call—trust me, you’ll want to hear this. Here is the link to the fund set up for Dara's late husband: Please click here. In this episode: The shift from traditional to AI-native hiring tech—what it really means How candidate fraud costs businesses $600 billion—yes, billion Layers of fraud detection: Swiss cheese analogy explained The role of IBM Watson in transparency and compliance The future of governance—code as the new rulebook Balancing trust and talent pool access in a hyper-suspicious world Why proactive planning for societal shifts is vital in workforce strategy Dara’s personal story: turning tragedy into impact with a brain tumor foundation Resources & Links: IBM Watson X Governance Learn about the brain tumor foundation Book: "AI Superpowers" by Kai-Fu Lee Dara Brenner on LinkedIn Connect with Dara: LinkedIn Twitter Timestamps: 00:00 - Introduction: The urgent need for trust in AI-driven hiring 02:08 - Dara Brenner’s background and journey through HR tech 03:20 - The fun side: Dara’s unexpected past as a restaurateur 05:45 - The impact of personal tragedy: Creating a foundation for brain tumor support 08:34 - The hidden threat: Candidate fraud in the age of AI 09:49 - How AI can be used nefariously in recruitment 10:56 - Layers of fraud detection: From resumes to deep fakes 12:01 - The staggering cost: $600 billion from resume fraud 14:26 - Organizations’ vulnerabilities: North Korea, bad actors, and real risks 15:36 - Balancing security with talent access: Where to draw the line 22:34 - Governance and compliance: IBM Watson’s role in transparency 23:46 - Constant AI audits: Like having a doctor in your pocket 28:31 - Future of recruitment: From ATS to AI-native systems 29:55 - Building AI into the DNA from day one—code as policy 32:29 - The evolving role of recruiters: proactive, strategic, data-driven 33:53 - Societal impacts: Demographics, immigration, and big-picture workforce planning 36:10 - Dara’s parting wisdom: Evolving trust, governance, and human oversight Final thought:The future of hiring is not just about smarter algorithms—it's about building a trustworthy system where technology and humanity work hand in hand. Stay vigilant, stay proactive, and never stop asking: are we doing this right? Because the stakes couldn’t be higher.

Are you tired of dealing with outdated recruiting strategies? Wondering if AI can truly revolutionize hiring? This episode dives into the gritty truth about how modern metrics and emerging AI tools are reshaping talent acquisition—sometimes for better, sometimes for worse.Join us as we unpack decades of recruiting wisdom, the pitfalls of cost-per-click, and what’s next in HR tech. In this episode: The history of traditional job advertising and its limitations How cost-per-application models are changing the game The messy reality of defining "qualified" applications and why subjectivity matters The myth of AI as an unbiased recruiter and its legal risks Why transparency in pay and job descriptions can fix much of the hiring chaos The dangers of scaling bad processes and how to avoid scaling mistakes Practical insights on choosing the right metrics for your hiring needs The future of AI in recruitment and the importance of process over technology Useful links: College Recruiter Work Defined Podcast Network Ultimate Guide to Recruitment Metrics Artificial Intelligence in Hiring – Industry Report The Future of Pay Transparency Reach out to Steven Rothberg: LinkedIn Twitter Timestamps: 0:00 - Welcome and episode overview: Are recruitment metrics still holding up?00:42 - Introducing Stephen Rothberg and college recruiter’s journey01:14 - The roots of traditional recruiting: From flyers to newspapers02:25 - Starting a business from a summer job and risk-taking mentality03:52 - The Winnipeg Jets story: Childhood risks and lessons in boldness05:23 - The shift from inefficient to performance-based ad models06:49 - The real meaning of "click" and the confusion across platforms08:13 - The rise of cost per application and its emotional impact on employers09:54 - Defining "qualified applications"—subjectivity and its pitfalls11:35 - Why scaling bad processes makes them worse13:08 - The evolution of pay-per-click and undisclosed definitions14:54 - The deadly cycle of bad job descriptions and reposting16:23 - How hiring for "fit" often misses the mark and costs real money17:10 - Qualification in hiring: Who judges? The subjectivity of recruiters18:29 - Scaling broken processes: The airplane manufacturing example19:54 - The quiet cost of bad candidate sourcing: The ATS funnel22:17 - The dangerous hype around AI and its current limitations in hiring23:12 - The black hole of AI decision-making and lack of transparency26:24 - The importance of honest job descriptions and pay transparency28:43 - Do employers prefer CPC, duration-based, or new models?30:01 - The chase for quality candidates and the costs involved31:27 - How to effectively invest in recruitment—long-term wins over shortcuts32:28 - The impact of AI on assessments and candidate matching35:55 - The legal peril of AI-driven hiring decisions and audit trail challenges37:25 - Final thoughts: Embracing process, transparency, and smart metrics

In this episode, we explore how artificial intelligence is revolutionizing HR, with a focus on building trust through data privacy and security. Join us as we discuss practical steps, emerging challenges, and the evolving role of HR professionals in the AI era. Key Topics: The importance of foundational data quality before implementing AI in HR Securing sensitive employee data and managing privacy concerns The role of semantic layers and data organization for effective AI use How AI impacts HR workflows and transforms knowledge work Practical approaches to integrating AI responsibly and securely Education needs for HR to understand AI risks and opportunities Future trends: AI's potential to reinvent HR practices, not just automate Resources & Links: Fuel 50 - Workforce Mobility and Talent Pipelines Amazon - Book: Data Privacy and Security in the Cloud Flurry - Official Website Amazon Bedrock - AI Model Service Anthropic - AI Safety and Privacy Guarantees OpenAI - Responsible AI Use Connect with Brian Platts: LinkedIn Twitter Timestamps:  00:30 - Welcome and introduction to the episode 01:15 - Brian Platts’ background in HR and software 02:08 - Flurry’s mission to make data meaningful for HR 03:26 - Fun fact: starting career driving a semi truck 04:44 - AI in HR: privacy, security, and data foundations 05:53 - Preparing your HR data for AI adoption 06:08 - Challenges with data quality and use cases 07:08 - Security considerations: private vs. public data 08:22 - Trusting AI vendors and data-sharing risks 09:15 - Teaching AI to query data securely 10:07 - Data organization and semantic layers 11:29 - Improving chatbots and avoiding misinformation 12:26 - Ensuring process accuracy and data integrity 13:14 - Sharing vs. protecting employee data 14:05 - Re-implementing permissions in AI-driven systems 15:01 - Education and awareness around AI security 16:13 - Learning from SaaS security issues during early cloud adoption 17:18 - HR’s role in AI education and safeguarding IP 18:14 - Balancing productivity gains with security controls 19:06 - AI’s impact on HR future: automation and new workforce roles 20:16 - The concept of the “Meat Layer” and human-AI collaboration 21:02 - Will AI replace HR jobs or empower them? 22:16 - The limits of current AI technology and future innovations 23:03 - Analogies: AI as a horse and the importance of tooling 24:06 - Embracing AI to enhance human work rather than replace it 25:16 - Reinventing HR processes beyond IT-led automation 26:18 - Regulatory challenges and incremental HR AI adoption 27:30 - How HR can lead responsible AI integration 28:03 - Final advice for HR professionals: think broadly and connect the dots

In this episode, we dive deep into the challenges and opportunities of HR data governance, exploring how organizations can improve data quality, ownership, and usability in a rapidly evolving AI landscape. Join us for practical insights from seasoned HR analytics experts on building a data-driven culture that supports strategic decision-making. Key Topics: Why HR data is often unreliable and the impact on decision-making The role of ROI and cultural mindset in improving HR data quality The importance of ownership, stewardship, and clear definitions in data governance How AI and machine learning magnify data quality issues if governance is lacking Practical steps to start building your HR data governance framework The critical role of documentation, data catalogs, and system integration Common pitfalls: managing multi-system data consistency and avoiding errors Quick wins: focusing on key metrics and stakeholder collaboration Timestamps: 00:00 - Introduction: Why HR data governance matters today 02:30 - Challenges HR faces with data quality and accuracy 06:15 - Why organizations struggle to demonstrate ROI from HR data 09:00 - Cultural and mindset barriers to effective data management 11:00 - The impact of AI and machine learning on HR data quality 12:30 - Context and system integration challenges across HR tech stack 15:11 - Defining HR data governance: Ownership, stewardship, and quality 17:00 - Creating a data glossary and system of record for HR data 19:05 - Real-world examples of poor HR data visibility and audit issues 21:00 - Using chatbots and AI: risks, benefits, and data consistency 24:00 - The importance of documentation and version control in AI applications 27:40 - Practical steps to start your HR data governance journey 30:00 - The significance of aligning metrics and defining owners 33:00 - Building a culture of data excellence and quick wins 36:00 - Addressing expectations for pristine data and managing realities 37:00 - Final recommendations for HR leaders to improve data governance Connect with Guests: Raswinder Singh - LinkedIn | Twitter Ankit Abrol - LinkedIn | Twitter

🚀 Dive into the future (at least the next 6 months) of HR with the latest episode of the HR Data Labs podcast! In the Season 10 recap, host David Turetsky explores the evolving landscape of compensation, strategy, and people analytics. We recap the current Season 10, where we discuss addressing training gaps, the impact of AI in HR, and other cool episode topics. Then we review our prediction for the past 6 months and make bold predictions for first 6 months of 2026. Join us for a thought-provoking discussion that prepares you for the challenges and opportunities ahead. #HRInnovation #FutureOfWork #HRDataLabs

Join host David Turetsky and guest Paul Reiman from Novo Insights as they delve into the dynamic world of compensation strategies and pay transparency. Discover how regulatory changes in the US and Europe are shaping the landscape, the critical role of job documentation, and the impact of technology in fostering transparency. Tune in for insightful predictions for 2026 and learn how political climates may influence future pay transparency laws. Chapters Introduction and Guest Introduction Compensation Strategies and Pay Transparency Regulatory Changes in the US and Europe The Role of Technology in Transparency Predictions for 2026 Conclusion and Final Thoughts Quotes: "Job documentation is crucial for pay transparency." "Regulatory changes are reshaping the compensation landscape." "Expect a shift in compensation survey methodologies by 2026." "Technology plays a key role in enabling transparency." "Implementing pay transparency presents unique challenges." "2026 will bring significant changes to HR practices." "Adapting to regulatory changes is essential for success."

Craig Friedman, Talent and Skills Transformation Leader at St. Charles Consulting Group and author of Enterprise Skills Unlocked, joins us this week to discuss the shift toward skills-based organizations. He breaks down how data-driven transformations allow companies to move from simple headcount management to true capability management. Craig also shares practical advice on how to prioritize skills projects to ensure they solve real business problems and deliver ROI. [0:00] Introduction Welcome, Craig! Today’s Topic: How Skills Data is Transforming HR into True Business Partners [5:05] What does a skills-based transformation look like in practice? Shifting the talent process from an exercise in headcount management to an exercise in capability management. Moving away from static "boxes on an org chart" to using granular data that supports the entire talent infrastructure. Leveraging skills data that lives in both business systems (capabilities) and people systems (individual skills) to better align with business functions. [11:57] How different teams leverage skills data differently Why L&D teams need granular skill details, while staffing teams prioritize context on scope and scale for compensation purposes. The importance of creating an enterprise data taxonomy where different departments can agree on a skill but append their own metadata. Using machine learning to handle the searches, connections, and adjacencies required to make the data useful across teams. [26:14] The impact on Learning and Development (L&D) How real-time skills gap analysis simplifies curriculum redesign when jobs or organizational structures change. The growing need for assessment and validation to verify skills learned through informal methods like coaching or on-the-job experience. Identifying business cases where skills can make a clear difference and prioritizing them based on value and risk. [36:20] Closing Thanks for listening! Quick Quote “A lot of the reason we're doing this now when we couldn't do it before is because of these more advanced tools in data analytics and AI and machine learning that actually help us manage data at that scale.” Link to Craig's book: https://a.co/d/0naqmvh

🚀 Exciting changes are coming in 2026! Join David Turetsky as he shares his vision for HR Data Labs, focusing on positivity and growth. Discover how we're merging brown bag lunches into our podcast and launching something new for HR Data Labs. #HRDataLabs #2026Vision #Positivity Chapters 00:00:34 Introduction and New Directions 00:01:42 David Turetsky's Personal Goals 00:03:59 HR Data Labs Evolution 00:06:19 HR Data Doodles news

Ranya Nehmeh, HR Strategist and Adjunct Professor at FHWien der WKW in Vienna, Austria, and Peter Cappelli, Professor of Management and Director of the Center for Human Resources at the Wharton School, join us this week to discuss some of the topics covered in their book, In Praise of the Office. We explore the current tumultuous state of Return-to-Office (RTO) mandates, why "hybrid" work is often failing to deliver on its promises, and the critical need for intentional management to foster human connection. [0:00] Introduction Welcome, Ranya and Peter! Today’s Topic: The Realities of Hybrid Work [9:15] The messiness of Return-to-Office (RTO) today Why the media narrative often contradicts the realities of small business data. Why the definition of “hybrid” varies per organization. [19:03] Is work actually getting done remotely? Distinguishing between hitting individual KPIs and maintaining organizational health. The deterioration of meeting culture and the rise of "cameras off" apathy. The loss of social norms and the difficulty of resolving conflict without face-to-face interaction. [29:50] Do policies need to change for the new world of work? Addressing proximity bias and its impact on promotions and career development. Why treating hybrid work the same as traditional office work is a management failure. Understanding the winners and losers of remote work, particularly for younger or newly onboarded employees. [46:23] Closing Thanks for listening! Quick Quote “If you really want people to come back into the office, you have to do it with intentionality.”

Steve Brink, CEO of GECN Group, joins us this week to discuss the complex world of executive compensation. Steve breaks down why the US pays a premium compared to the rest of the world, how boards are shifting their focus from simple compensation to holistic talent management, and the global trends driving executive pay structures today.

Bob Pulver, host of the Elevate Your AIQ podcast and a 25-year enterprise tech and innovation veteran, joins us this week to unpack the urgent need to move past "AI" as a buzzword and define what "Responsible AI" truly means for organizations. He shares his insights on why we are all responsible for AI, how to balance playing "defense" (risk mitigation) and "offense" (innovation), and why we must never outsource our critical thinking and human agency to these new tools. [0:00] Introduction Welcome, Bob! Today’s Topic: Defining Responsible AI and Responsible Innovation [12:25] What Does “Responsible AI” Mean? Why elements (like fairness in decision-making, data provenance, and privacy) must be built-in "by design," not bolted on later. In an era where everyone is a "builder," we are all responsible for the tools we use and create. [25:48] The Two Sides of Responsible Innovation The "responsibility" side involves mitigating risk, ensuring fairness, and staying human-centric—it’s like playing defense. The "innovation" side involves driving growth, entering new markets, and reinvesting efficiency gains—it’s like playing offense. [41:58] Why don’t we use AI to give us a 4-day work week? The critical need for leaders to separate their personal biases from data-driven facts. AI’s role in recent layoffs. [50:27] Closing Thanks for listening! Quick Quote “We're all responsible for Responsible AI, whatever your role is. You're either using it or abusing it . . . or you're building it or you're testing it.”

Noah Mithrush, Director of Growth Marketing at Guusto, joins us live from the UKG Aspire Conference to unpack the critical intersection of User Experience (UX) and Employee Experience (EX) in HR technology. Noah explains why so many HR programs fail to gain adoption and how even the best intentions can be derailed by a poor user experience. We discuss how to get into the user’s mindset, why HR tech should be as easy to use a consumer app, and how making the emotional journey of an employee is the key to success.  [0:00] Introduction Welcome, Noah! Today’s Topic: Rethinking User Experience to Improve Employee Experience & Program Adoption [3:53] What do people get right and wrong about user experience? Why good intentions often fail, and the common mistake of not considering all technology touchpoint for the end-user The problem of designing programs that are manually intensive for managers [10:43] How do you get into the users’ mindset to align UX and EX? Going beyond just mapping process steps to mapping the employee journey Why implementing "emotional IQ" into the design process is critical for driving program adoption [16:59] How does AI impact the employee experience? Using agentic processes to allow teams to do more with less The potential for AI to allow teams to "think differently" and fundamentally redesign the employee journey [22:28] Closing Thanks for listening! Quick Quote “What I see a lot of the time is what people get right is their intention. At the very beginning, they're trying to solve a problem . . . but when it comes to tech and the user experience, [they’re] not taking into consideration all of the points along the way of different technology [and] how the actual end-user (or employee) has to use and interact with it.”

Nate Rees, Director of Training and Talent Development at Salary.com, joins us this episode to discuss a critical issue facing organizations today: the manager training crisis. Nate shares alarming data on the percentage of managers promoted without receiving any training and the costly impact this has on turnover and productivity. We explore why organizations fail to invest in new managers, how a raise is not a substitute for training, and low-budget/high-impact strategies HR leaders can implement immediately to better support their new managers. [0:00] Introduction Welcome, Nate! Today’s Topic: The Manager Training Crisis [6:25] What is the manager training crisis? 60% of new managers report receiving zero training for their role. New managers are split between their own quota and team development. [16:31] Why aren’t more organizations investing in manager training? Untrained managers’ teams have a 260% higher turnover rate. Organizations will pay a premium for external experienced managers but won’t invest in developing their internal talent. [22:29] How can HR leaders start to fix this? Create a zero-budget manager mentor program by leveraging your existing top managers. User simple conversation models like COIN (Context, Observation, Impact, Next). [33:43] Closing Thanks for listening! Quick Quote “60% [of managers] say they never received any training when they transitioned into their first leadership role... we're throwing them at the deep end of the pool and not giving them any swimming lessons.”

Carlee Wolfe, Associate Vice President of Talent and Organizational Effectiveness at Hyatt, joins the podcast for a special 250th episode! Carlee discusses the value, strategy, and importance of serving on nonprofit boards. She shares insights on how to find the right board that matches your passions and skills, why nonprofits need skilled volunteers, and how to be an effective contributing board member once you join. [0:00] Introduction Welcome, Carlee Wolfe! Today’s Topic: The Value and Strategy of Joining a Nonprofit Board [9:28] What is the strategic value of joining a nonprofit board? Carlee’s story of learning how to get involved and discovering you can "just ask"  Why nonprofits need skilled and passionate board members to serve [17:29] How do you find the right board to join? Starting by identifying your passions, skills, and available time commitment Using resources like national board matching services (e.g., Board Source) or local city programs [26:00] How to be an effective board member The importance of passion and commitment to making tough decisions Knowing your scope and capacity; avoid overcommitting to too many boards [28:07] Closing Thanks for listening! Quick Quote “I think the big thing about being on a board . . . is you are helping set the support and steward the strategic direction of the organization, right? You're that body that supports the ultimate mission of where the organization is heading.”

In this episode, David and Dwight dive into the critical and ever-present issue of poor data quality in HR and its cascading impact on the organization. They break the problem down into 3 key areas: recruiting, artificial intelligence, and pay transparency. They explore how recruiting often serves as the flawed entry point for employee data, discuss the dangers of training AI on biased information (which can lead to discriminatory practices like ageism), and examine the new data governance challenges posed by emerging pay transparency laws. [0:00] Introduction Today’s Topic: The Impact of Poor Data Quality on HR Today  [5:24] How does poor data quality in recruiting create downstream problems? Recruiting is the first ingress of data into an organization, and it's often the least well-managed. Poor data can also originate from the company side, with issues like inaccurate job descriptions or incorrect FLSA classifications. [12:08] How can biased data lead to discriminatory AI in the hiring process? AI agents used in video interviews can reject qualified candidates based on flawed or biased training data. Companies that fail to address AI bias on the front end risk facing expensive lawsuits and will be forced to fix their systems later. [19:32] What are the data governance challenges presented by pay transparency laws? Pay transparency laws in several states require companies to disclose pay ranges for open roles also mandate that companies keep detailed records of salary structures, grade ranges, and hiring data for extended periods. Many organizations may need to update their data governance strategies to ensure they are retaining the necessary historical data to comply with these regulations and withstand potential audits. [24:31] Closing Thanks for listening! Quick Quote “As the demographic bubble for Gen X gets larger, companies can't ignore [AI bias in recruitment] anymore. They have to take it on, and that means they have to start training their artificial intelligence to not filter out all of us grays.”