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Titre
Date
Durée
Stop Managing Tools, Start Managing Agents: The New RevOps Framework with Mallory Lee
16 Feb 2026
00:42:51
Is your RevOps team unified, or just a collection of scattered silos?
In this episode of AI Powered RevOps, host Sandy Robinson sits down with Mallory Lee, the VP of Revenue Operations at Zipline. With over 15 years of experience leading ops at high-growth companies like Nylas and Terminus, Mallory knows exactly what it takes to knit together marketing, sales, and customer success into a single holistic strategy.
Key Takeaways:
Unifying the Engine: Why the first step to successful RevOps is breaking down isolated department silos.
The "Twice a Day" Rule: A simple leadership framework for driving company-wide AI adoption.
Automating the Pipeline: How to use AI to handle CRM admin work so reps only have to focus on close dates and deal amounts.
The Rise of the GTM Engineer: Why this new role is critical for orchestrating complex AI systems.
AI Literacy at Home: A personal look at raising kids in the age of AI and using agents to track health and fitness.
AI-Powered RevOps: Ending "Metrics Tourism" with Oscar Armas-Luy
02 Feb 2026
00:33:30
AI-Powered RevOps: Ending "Metrics Tourism"
In this episode, Sandy Robinson sits down with Oscar Armas-Luy, VP of Revenue Operations at Garner Health. Oscar blends a Computer Science background with GTM execution to dismantle AI hype and replace it with a practical playbook for 2026.
Oscar reveals his strategy for turning Gemini Pro and Google Apps Script into a custom automation engine that eliminates hours of manual reporting and human error. If you’ve ever felt buried under dashboards that look pretty but drive zero action, this episode is your antidote.
Inside the Episode:
The "Metrics Tourism" Trap: Why "interesting" data is the enemy of actionable growth telemetry. Oscar explains how to stop reporting for reporting's sake and focus on the inputs that actually move the needle.
The AI Spreadsheet Engine: A technical deep dive into using LLMs to write code that supercharges Google Sheets and Excel. Learn how Oscar automated a 3-hour manual reporting "beast" into a 30-second refresh.
Strategic Thought Partnership: Moving beyond simple task automation. Oscar shares how he uses AI for Game Theory in vendor negotiations and to pressure-test contrarian ideas to avoid confirmation bias.
Design Risk vs. Execution Risk: A new leadership framework. Why the biggest threat to AI adoption isn't technical failure, but propagating suboptimal architecture at scale.
Episode Chapters:
[00:31] Meet Oscar Armas-Luy: From Computer Science to RevOps Leadership.
[04:23] Language as Math: Why LLMs are "Pattern Machines."
[06:03] Why Oscar has declared war on "Metrics Tourism."
[08:26] The Tech Stack: Scaling RevOps with Google Apps Script and Gemini Pro.
[14:24] Evolution of AI: Moving from task-bot to strategic thought partner.
[17:16] Negotiation Strategy: Using AI for vendor contracts and game theory.
[23:51] Vendor Reality Check: Why "Out of the Box" AI features often fail.
[28:49] Design Risk vs. Execution Risk: The new framework for AI leadership.
[31:51] Rapid Fire: Data readiness and the future of the role.
AI-Powered Outbound, “Baseball Cards,” and the SPORTS Framework (with Jeff Ignacio)
19 Jan 2026
00:29:47
SUMMARY Jeff Ignacio (Founder, RevOps Impact) joins Sandy Robinson to break down how modern RevOps teams are using AI to accelerate outbound, enrich accounts fast, and shift rep time back to customer-facing work. We cover GTM Engineering, build vs. buy (TCO + technical debt), human-in-the-loop for enterprise, and practical “start small” steps to adopt AI without breaking your systems.
SHOW NOTES • Jeff’s background: hyperscalers + startups → independent advisory (RevOps Impact) • Build vs. buy: total cost of ownership, cost/quality/speed tradeoffs, and succession planning • The SPORTS framework: Strategy → Process/Playbooks → Operating Rhythms → Targets/Thresholds/Trends → Systems • A 4-step outbound framework: company research → persona research → offer/value prop → tailored sequencing • Human-in-the-loop: when automation works vs. when review matters (enterprise/ABX) • Adoption: early wins, champions, and overcoming skepticism • Where to start: use existing vendor AI features, learn webhooks/APIs, and strengthen prompting • Rapid fire: data readiness, churn analysis, ROI (revenue attainment + CAC), future of RevOps
Leveraging AI for Business Growth with Jordan Shaheen
05 Jan 2026
00:37:26
Summary
In this episode of AI Powered RevOps, host Sandy Robinson interviews Jordan Shaheen, Head of Revenue and Strategy operations at Candid. They discuss the transformative role of AI in revenue operations, focusing on data enrichment, strategic analysis, and the integration of AI tools to enhance efficiency and decision-making. Jordan shares insights on transitioning Candid from a direct-to-consumer to a B2B model, the importance of continuous learning, and the evolving role of RevOps in leveraging AI for business growth.
Takeaways
AI is a lever for RevOps leaders to drive strategy.
Transitioning from direct-to-consumer to B2B requires operational rigor.
Data enrichment and analysis are key to developing customer profiles.
AI tools can augment human processes, not replace them.
Continuous learning is crucial for adapting to AI advancements.
Voice-to-action tools enhance field reps' efficiency.
AI can improve decision-making confidence and reduce clerical work.
RevOps teams benefit from generalists who can adapt to AI.
AI tools should be tested at scale for real impact.
Leadership buy-in is essential for successful AI integration.
In this episode of AI Powered RevOps, Sandy Robinson interviews Prudhvi Raju, who shares his insights on the intersection of analytics and revenue strategy. Prudhvi discusses his journey in revenue operations, the role of AI in enhancing decision-making, and the importance of leveraging data for informed business strategies. He emphasizes the need for clean data, the integration of AI tools, and the evolution of CRM systems in the future of RevOps. The conversation also touches on the significance of involving sales teams in the development of AI initiatives and the necessity of building internal tools to streamline processes.
Takeaways
Prudhvi emphasizes the importance of clean data for effective AI implementation.
AI can significantly reduce the time needed for tasks like account research.
Involving sales teams in the development of AI tools is crucial for adoption.
RevOps is evolving towards a data-led process rather than an operational one.
Building internal tools can enhance efficiency and reduce reliance on external vendors.
AI should be viewed as a support system for RevOps professionals.
The future of CRM will likely involve more integrated and flexible systems.
Feedback from users is essential in shaping AI tools and initiatives.
RevOps leaders must adapt to the changing landscape of technology and data.
Collaboration across departments is key to successful RevOps strategies.
Sound bites
"The possibilities are infinite."
"AI will do it in a minute or two."
"AI is always going to be a tool."
Chapters
00:00 Introduction to RevOps and AI
02:49 Prudhvi's Journey in Revenue Operations
05:55 The Role of AI in RevOps
08:46 Building a Central Intelligence System for Revenue
Guest: Amani Phipps, Director of Business Operations and Analytics at Bonusly
In this episode of AI-Powered RevOps, Sandy and Amani Phipps discuss the transformative role of AI in revenue operations. Amani shares his journey from finance to business operations, emphasizing the importance of an AI-first approach in modern organizations. They explore practical steps for integrating AI tools, the challenges faced during implementation, and the significance of data cleanliness and feedback mechanisms. Amani highlights the need for leadership buy-in and the evolving nature of RevOps in the age of AI, encouraging listeners to start small and embrace change.
Takeaways:
AI is a teammate that needs feedback and training.
Start small with AI applications in daily tasks.
Data cleanliness is crucial for effective AI use.
Leadership buy-in is essential for AI adoption.
AI can automate repetitive tasks and enhance efficiency.
Continuous improvement is key in AI implementation.
Feedback mechanisms help refine AI tools.
AI will transform the future of RevOps.
Embrace change and be open to new tools.
AI is here to stay and will evolve with the industry.
Transforming RevOps with AI: Amani Phipps' Insights
AI-Powered RevOps is where real talk meets real-world execution in an AI-powered world. Host Sandy Robinson sits down with operators, enablement leaders, GTM owners, and vendors to unpack what’s actually working (and what isn’t) when it comes to building an AI-powered revenue engine, without losing your mind in the process.
On this show, you’ll hear:
• How teams are really using AI in RevOps and enablement • Experiments, playbooks, and the messy lessons learned along the way • Alignment, change management, and leadership in the middle of constant change • Success stories, major flops, and unapologetic hot takes • Deep dives on tools and workflows from practitioners, vendors, and operators in the trenches • Every episode closes with 5 rapid-fire questions pulled from what everyone is asking in RevOps right now
No BS and no scripts. Just candid conversations designed to leave you with ideas to try tomorrow, solutions to nagging problems, insights on tools, and guidance on how to keep your revenue engine (and your sanity)running. Expect a few laughs, plenty of honesty, and seriously actionable ideas.
Sandy Robinson has spent over 20 years leading Revenue Operations and Enablement in SaaS and other industries, in small startups, growing scale-ups, and mature or even public companies. From building sales operations foundations and leading cross-functional GTM teams, to designing revenue engines built for scale and aligning marketing, sales, and customer success around the full customer journey. Her focus has always been on turning messy, real-world challenges into practical playbooks, empowering teams through training and change management, and challenging the status quo when it gets in the way of growth. A few years ago, she completed her Master’s degree in Education in Training and Development. Sandy wanted to do this podcast because she is in student mode, and she wanted to share her learnings with others. She has always had a passion for continuous learning, and now that focus is on AI in RevOps.
If you’re ready for clarity, a few laughs, and a steady stream of actionable ideas, hit follow on AI-Powered RevOps and queue up the first episode.
AI in Enterprise B2B Sales: RevOps, MEDDPICC, Forecasting, and the Future of AI with Roi Carmel
16 Mar 2026
00:46:50
Show Notes: In this episode of AI-Powered RevOps, Sandy Robinson sits down with Roi Carmel, CEO and co-founder of Spotlight.ai, to talk about the future of AI in enterprise B2B sales and what it means for RevOps leaders, sales teams, and go-to-market organizations.
Roi shares how his background in high-growth SaaS companies led him to build Spotlight.ai, a platform focused on helping enterprise revenue teams turn buyer interactions into decisions and action. Sandy and Roi break down one of the biggest challenges in today’s market: too many companies are chasing AI tools for sales and RevOps without first identifying the real business problem.
This conversation explores how to evaluate AI for RevOps, what it actually means to be AI-ready, and why automating a broken sales process can make the problem worse. Roi explains why teams should start with bottlenecks, align on business goals, and measure AI success against the exact operational metric they want to improve.
They also dive into MEDDPICC, forecast accuracy, deal qualification, sales productivity, and the balance between AI automation and human-led selling. Roi shares his framework: Listen, Understand, Decide, Act, and explains how enterprise sellers will increasingly shift from executors to orchestrators as AI takes over more administrative and analytical work.
This episode is packed with practical insight for RevOps professionals, CROs, sales leaders, revenue leaders, and anyone navigating the fast-changing world of AI in B2B sales.
In this episode:
How RevOps teams should evaluate AI tools
Why shiny-object syndrome creates bad AI decisions
What “AI-ready” really means
How AI can improve qualification, forecasting, and execution
Why human sellers still matter in enterprise sales
The future of AI agents in sales workflows
About Roi Carmel: Roi Carmel is the CEO and co-founder of Spotlight.ai, an autonomous enterprise sales platform helping revenue teams improve qualification, value selling, and sales execution with AI.
Timestamps: 00:00 Intro 01:23 Roi’s background 04:35 Archery, discipline, and repetition 07:39 AI hype in RevOps 14:32 What AI-ready looks like 20:17 What teams miss in AI evaluation 30:22 The future of enterprise sales 38:09 Rapid-fire AI questions 41:41 Spotlight.ai overview 45:23 Final thoughts
Keywords: AI Powered RevOps, Roi Carmel, Spotlight.ai, AI in sales, AI in RevOps, enterprise B2B sales, RevOps, MEDDPICC, forecast accuracy, revenue operations, sales productivity, GTM strategy, AI agents, sales automation
Navigating AI in Revenue Operations with Olga Traskova
02 Mar 2026
00:45:11
Summary
In this episode of AI Powered Rev Ops, Sandy Robinson interviews Olga Traskova, VP of Revenue Operations at BirdEye. They discuss the evolution of AI in revenue operations, focusing on practical strategies for implementing AI to enhance productivity and efficiency. Olga shares her journey in the field, the phases of AI adoption, and the importance of mutual action plans in sales processes. The conversation also touches on leadership expectations, budgeting for AI tools, and the future of AI in revenue operations.
Takeaways
AI can reshape how teams operate.
Data cleanliness is crucial for effective AI use.
Mutual action plans are essential for sales success.
AI adoption occurs in phases: personal productivity, workflow acceleration, and operating systems.
AI can help analyze deal performance and risks.
Leadership expects quick decision-making with AI.
AI will replace roles that do not adapt to its use.
The future of revenue operations will involve AI agents working alongside humans.
AI tools can enhance sales efficiency and forecasting accuracy.
Understanding the costs associated with AI tools is vital.
Olga's Sound Bites:
"Move beyond the AI hype."
"Garbage in, garbage out."
"AI will be replacing people."
Chapters
00:00 Introduction to AI in Revenue Operations
01:41 Olga Traskova's Journey in Revenue Operations
AI, Revenue Operations, Olga Traskova, Mutual Action Plans, Sales Automation, AI Strategy, Go-To-Market, Data Cleanliness, AI Adoption, Sales Efficiency
AI for RevOps: Practical Lessons from Zapier’s GTM Team w-Lindsay Rothlisberger
13 Apr 2026
00:47:04
Summary
In this episode of AI-Powered RevOps, Sandy talks with Lindsay Rothlisberger, who leads GTM Strategy Ops and AI at Zapier, about how RevOps teams can apply AI in practical ways across marketing, sales, CS, enablement, and analytics. They dig into CRM data quality, pipeline risk, coaching bots, renewal strategy, self-service reporting, and why the best AI use cases often start at customer transition points.
Key Takeaways
Start AI where customer transitions break down, especially handoffs between marketing, sales, onboarding, and customer success.
Treat AI workflows like products: launch, learn, improve the data behind them, and keep refining the output.
Strong AI use cases in RevOps include coaching bots, call prep, lead classification, renewal strategy, and self-service reporting.
Context is the real advantage in RevOps, and AI becomes far more useful when teams package business logic and definitions into the workflow.
Planning in AI-heavy environments has to stay flexible, with clear tradeoffs and a process for changing priorities quickly.
Chapters
00:05 Welcome and episode setup 01:29 Lindsay’s path from marketing ops to RevOps at Zapier 04:40 Fun fact: Bravo, Real Housewives, and work-life balance 06:04 How Zapier got started with AI internally 07:18 Early use cases: call prep, coaching bots, and chat analysis 09:11 Build vs. buy and embedding AI into workflows 10:27 RevOps team structure and AI use cases across functions 14:36 Using AI to improve customer transitions and renewals 20:10 Why context is RevOps’ biggest AI advantage 22:14 Cursor, Databricks MCP, and self-service analytics 27:15 Deterministic workflows vs. adaptive agents 30:07 Planning, operating models, and changing priorities fast 34:05 Data quality guardrails and avoiding “garbage in, garbage out” 36:06 Cross-functional AI work and enabling self-service 41:48 Coaching, enablement, and AI role play 44:03 Rapid fire: where RevOps should start with AI 47:31 Lindsay’s advice: build something and learn by doing
How Hassan Irshad Uses Claude to Drive Real AI-Powered RevOps ROI
30 Mar 2026
00:47:13
Show Notes:
In this episode of AI-Powered RevOps, Sandy Robinson sits down with Hassan Irshad, Head of RevOps at Unify and founder of Revfinity, to talk about how RevOps teams can actually use Claude in the real world.
This conversation goes beyond AI hype and into practical application: win-loss analysis, closed-lost review, meeting prep, forecasting, pipeline inspection, and using AI to free up time for more strategic work. Sandy and Hassan also dig into a critical truth for RevOps teams: AI only works as well as the data, process, and context underneath it.
If you’re a RevOps leader, GTM operator, sales ops pro, Salesforce admin, or GTM engineer trying to figure out where AI fits, this episode is packed with actionable ideas you can use right now.
Chapters:
00:28 – Intro to Hassan Irshad
01:16 – Hassan’s RevOps background
02:49 – Fun fact: DJing house music
04:06 – What pulled Hassan into AI
06:25 – Why Claude clicked for RevOps
09:13 – Real use cases: win-loss and closed-lost analysis
11:46 – Conversational intelligence, Attention, and MCP
13:41 – Why context and guardrails matter
17:04 – “AI layered on trash is just beautiful looking trash”
20:02 – What AI-powered RevOps actually means
22:41 – Daily workflow automation and prioritization
23:47 – Meeting prep agents and proving ROI
28:45 – Where companies overcomplicate AI adoption
30:51 – Using Claude as a thought partner
32:18 – Using Claude for board-level presentations
34:12 – Biggest mistakes in operationalizing AI
37:40 – How AI will change the RevOps role
42:06 – Advice for teams getting started
43:25 – Rapid fire: where to start, ROI, and replacement fears
45:24 – Final takeaway: start small and iterate
What you’ll hear in this episode:
- Why RevOps is uniquely positioned to lead AI across GTM
- How Hassan is using Claude for practical RevOps workflows
- Why context from CRM, Slack, and conversational intelligence matters
- How to measure AI ROI in time saved and dollars created
- Why strong foundations still matter more than ever
- What the RevOps role may look like over the next 12–24 months
About the guest:
Hassan Irshad is Head of RevOps at Unify and founder of Revfinity. He has spent nearly a decade building revenue operations across high-growth companies, with prior leadership roles including FundraiseUp, Zipco, and ADP.
AI, RevOps, and the Operating Model Problem with Anne Pao
11 May 2026
00:59:06
Summary:
In this episode of AI-Powered RevOps, Sandy Robinson sits down with Anne Pao, founder and CEO of Ignite, to talk about what RevOps leaders need to get right as AI and automation reshape go-to-market teams. From AI governance and process mapping to enablement, ROI, build-versus-buy decisions, and the future of RevOps, Anne shares practical advice for operators trying to move beyond shiny tools and toward real business impact.
Key Takeaways:
AI will not fix broken processes. RevOps teams need strong documentation, process mapping, and clear ownership before layering in automation.
Governance matters. Teams using AI without enterprise controls, security standards, or data boundaries create risk across customer data and GTM systems.
Enablement is not optional. AI adoption requires reinforcement, workflow change, and clear communication about how people’s day-to-day work will change.
ROI should go beyond hours saved. The real question is whether AI meaningfully improves funnel outcomes, conversion, revenue, or customer impact.
RevOps leaders who rely only on system ownership may be at risk, but those with judgment, discernment, and cross-functional alignment skills will become even more valuable.
Chapters:
00:26 Welcome to AI-Powered RevOps 01:24 Anne Pao’s background and work with Ignite 02:20 Why fractional RevOps matters for growth-stage companies 03:51 Anne’s fun fact: food writing and restaurant reviews 05:22 How 20+ years in growth, analytics, and operations shaped Anne’s RevOps perspective 10:39 What feels different about today’s AI wave 11:23 AI sprawl, security, and governance risks 14:24 How companies should approach AI strategy and ownership 17:16 What RevOps needs to get right before AI and automation 19:08 Practical AI use cases: discovery playbooks and RFP workflows 22:37 Build versus buy decisions in an AI-powered GTM world 26:27 AI use cases creating practical value today 29:35 Common mistakes teams make when adopting AI 31:43 Why enablement is critical to AI adoption 36:56 Measuring ROI from AI in RevOps 41:23 Storypath.ai and AI-assisted revenue storytelling 48:01 How AI may reshape RevOps over the next few years 54:25 Rapid-fire questions on AI in RevOps 58:06 Anne’s final thoughts on humans, judgment, and the future of RevOps
revenue operations, AI in RevOps, go-to-market strategy, GTM operations, AI automation, AI governance, RevOps enablement, process mapping, sales operations, customer success operations, AI adoption, revenue architecture, build versus buy, AI ROI, enterprise AI, GTM enablement, sales funnel optimization, RevOps leadership
In this episode of AI-Powered RevOps, Sandy Robinson sits down with Teri Long, VP of Global GTM and Partner Enablement at GoTo, to break down where AI is actually creating real impact inside revenue teams. From call intelligence and AI role play to manager coaching, partner enablement, and RevOps alignment, Teri shares how leading organizations move beyond shiny objects and use AI to improve execution, win rates, and revenue outcomes. If you're trying to scale enablement, drive adoption, and make AI useful—not just visible—this conversation is packed with practical takeaways.
Key Takeaways
• Start with the highest-friction point in seller or partner workflows—not with AI for AI’s sake • Call intelligence, coaching insights, and AI role play are some of the fastest paths to measurable impact • RevOps and Enablement must work together: RevOps owns the data foundation, Enablement drives behavior change • Test, learn, and validate is the framework for successful AI adoption and continuous improvement • Real AI ROI shows up in ramp time, win rates, coaching effectiveness, and seller productivity
Chapters
00:22 – Meet Teri Long: GTM Enablement, AI, and Revenue Execution 04:30 – How Teri Started Using AI in Enablement 08:15 – Where AI Creates Real Value vs. Shiny Objects 13:40 – Call Intelligence, Buyer Insights, and Coaching at Scale 20:05 – RevOps + Enablement: Why Alignment Matters 27:10 – Quick Wins: Where Revenue Teams Should Start with AI 33:18 – Driving AI Adoption and Building Internal Champions 40:12 – AI for Partner Enablement and Scaling Through Ecosystems 47:25 – The Future of Enablement Leaders in the Next 12–18 Months 54:10 – Rapid Fire: AI Questions Every RevOps Leader Is Asking 01:02:30 – Final Advice: Start with the Problem, Not the Tool
Why RevOps Needs an AI Intelligence Layer, Not More Automation
26 May 2026
00:52:03
Episode Summary
Sandy Robinson talks with Sahil Aggarwal, co-founder and CEO of Rattle and Von, about what AI can actually change for revenue teams. Sahil argues that RevOps, sales, and GTM leaders are still in the experimentation phase, and that the real productivity gains will come from AI intelligence layers that understand business context, connect across the GTM stack, and help teams make faster, better decisions.
Key Takeaways
AI has not yet delivered true productivity gains in revenue teams the way it has in engineering.
RevOps should focus less on disconnected agents and more on operationalizing intelligence across the GTM stack.
CRM is still the system of record, but the intelligence layer may become the more valuable operating layer.
Bad data should not delay AI adoption; AI can help improve GTM data when connected to calls, emails, CRM, and other systems.
RevOps is best positioned to own GTM AI strategy because the function lives closest to process, data, and execution.
Chapters 00:32 Welcome to AI-Powered RevOps 01:24 Sahil’s Background and the Evolution from Rattle to Von 04:59 The Core Problem: Helping Sales Teams Sell 07:28 Why AI Became a Real Opportunity for GTM 09:46 Why AI Experimentation Has Not Yet Become Productivity 11:41 The Horseless Carriage Problem in AI 16:31 Build vs. Buy for RevOps AI 18:23 What Von Is Building for Revenue Teams 22:53 AI, Data Hygiene, and Fixing the Data Foundation 25:47 The Future of CRM and the GTM Tech Stack 30:08 How Teams Use AI to Operationalize Revenue Work 35:11 Why Internal AI Builds Often Fail 38:20 AI, Headcount, and Revenue Productivity 41:49 How AI Could Change the AE Role 44:51 Why Von Is Named After John von Neumann 45:35 Rapid Fire: RevOps, CRM, AI Strategy, and Salesforce Headless 360 49:21 Advice for RevOps and Enablement Leaders 50:42 How to Connect with Sahil
AI-Native RevOps: Turning CRM Data, Signals, and AI Workflows Into Operating Leverage
28 Jun 2026
00:53:52
Episode Summary
Sandy Robinson sits down with Corey Schwitz, CEO and founder of Skydog Ops, to unpack what it really takes to move AI from hype into operational execution across RevOps, CRM, and GTM. Corey shares where companies are actually starting, why proactive AI matters more than another dashboard, and how RevOps leaders can build AI-native systems that reduce manual work, surface better signals, and help teams take smarter action.
Key Takeaways
AI-native CRM is not just automation — it is about making GTM systems proactive.
RevOps teams should start with practical use cases like chat-to-CRM, data entry automation, call data updates, lead scoring, deal signals, and company intelligence.
The biggest AI risk is not moving too fast — it is waiting too long to operationalize.
CRM hygiene is still a leadership and culture issue, even when AI makes updates easier.
RevOps must think beyond technical execution and operate more like business strategists.
Chapters 00:22 Meet Corey Schwitz and Skydog Ops 03:22 Corey’s Broadway background and path into tech 05:04 Why CRM data is still such a mess 07:33 What AI should update automatically vs. what needs approval 11:26 Why most GTM teams are still early with AI 14:22 Seven practical AI use cases for sales and customer success 16:25 What AI-native CRM and GTM systems really mean 18:35 Proactive AI vs. manual data entry 21:04 Avoiding “just another tab” in the GTM tech stack 23:02 Slack, Teams, Salesforce, and CRM workflow challenges 27:02 Common mistakes companies make with AI implementation 31:48 Where AI should take action first 34:34 Using signals, Clay, and company intelligence to support sellers 42:33 What is realistic for pipeline discipline and CRM hygiene 47:49 Rapid-fire AI questions for RevOps and GTM teams 51:41 Corey’s advice: think like a CEO 53:04 How to connect with Corey and Skydog