In this new series, host Albert Lawrence will be joined by AI experts – technologists and business leaders alike to explore what generative AI can and can’t do, how it actually gets built, responsible ways to put it into practice, and the real world business problems and solutions we’ll encounter along the way.

Data driven decision making exceeds any intuition in fantasy football (or any other sport). When you get your data ready the right way, you can use AI model so gain powerful insights. Insights that can help you drive growth—or win at fantasy football. In this episode, ESPN host Mike Greenberg joins podcast host Albert Lawrence and Elizabeth O'Brien, Senior Executive of Sports and Entertainment Sponsorship Marketing at IBM, to discuss the importance of making game decisions based on data and how generative AI is changing the game in the fantasy football space. Learn about the powerful AI models co-created by IBM and ESPN that transform football data into insights to help fantasy team owners set their lineups.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

When you are expected to modernize millions of lines of code fast, AI code generation may seem like a great idea. But to effectively use generative AI, developers need a fundamental understanding of code and programming principles. Listen to host Albert Lawrence, Miha Kralj, Global Senior Partner of IBM Hybrid Cloud Services, and David Levy, Advisory Technology Engineer at IBM Client Engineering, as they explore the use of AI models in application development and application modernization as well as the potential pitfalls to avoid.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Can using generative AI and natural language processing make AI agents really be empathetic, personal and proactive? Can they answer the questions that we have without human agent intervention? Listen to host Albert Lawrence, Jeannie Walters, customer experience speaker and trainer, and Morgan Carroll, senior AI engineer at IBM, as they discuss the use of virtual agents, artificial intelligence and generative AI in customer service. Learn why transparency and honesty are important when using AI assistants and chatbots, and how best you can use data and AI to predict and prevent customer issues.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Want to know how generative AI and artificial intelligence can bring the human back into human resources and help both the employers and the candidates. Listen to host Albert Lawrence, Jon Lester, VP of HR Technology, data and AI at IBM, and David Levy, Advisory Technology Engineer at IBM, as they discuss the different ways AI adoption can help optimize the hiring process—automating tasks, providing insights and offering recommendations to hiring managers. And learn more about the different outcomes AI orchestration helps deliver, including improved candidate experience, reduced time to hire and increased quality of hire.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

AI adoption requires a platform approach, with the data , AI models, and AI governance working together seamlessly. So, successful generative AI adoption means integrating data silos, managing your AI infrastructure effectively and choosing the right cloud deployment options. In this episode, our host Albert Lawrence and guests Hillery Hunter, CTO for IBM Infrastructure and GM of Innovation, and Ash Minhas, Engagement Leader at IBM Innovation Studio, explore the link between hybrid cloud and AI and discover how the right tech foundation can help take your AI workloads to the next level.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Artificial Intelligence (AI) can free up time and make work easier, automating repetitive tasks so we can focus on creative and strategic work – we hear it all the time. But how exactly do we use AI assistants and virtual agents , and chatbots to achieve greater efficiency and productivity using generative AI? Listen to podcast host Albert Lawrence in conversation with Jessica Rockwood, VP of Client Engineering at IBM, and Morgan Carroll, Senior AI Engineer in Client Engineering at IBM as they explore the potential of AI in transforming the way we work and discover the role AI integration and the right AI models play in successful AI adoption.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Generative AI is expensive, and it gets even more expensive as you scale. Find out about the hidden costs of AI, like AI integration, data, and AI security with host Albert Lawrence, Rebecca Gott, IBM Distinguished Engineer and CTO of Power Platform, and Penny Madsen, IDC Senior Research Director of Cloud and Edge Services. Listen to see how you can make your AI project returns justify the cost, and how an AI center of excellence can help. 

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Virtual agents have been part of our lives for a long time, but can they replace humans as they become faster and more accurate with generative AI? Listen to host Albert Lawrence discuss the evolution of AI agents with Susan Emerson, Vice President of Product, AI and Data at Salesforce and Nick Renotte, Chief AI Engineer at IBM Client Engineering.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Gen AI is changing life for everyone, even for those creating it, aka developers. In this episode, host Albert Lawrence and IBM Developer Advocate JJ Asghar discuss why “open” is so important, AI security, governance, and how to get started as an AI developer. Should you build your own foundation model? Are open-source AI models more secure? Listen for more advice on how to get the most from AI models.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

There's a vanguard leading the charge to make AI accessible to all, and others are still catching up. Yet, amidst this progress, a concerning reality exists: a gender gap is forming in the field of AI. Listen to Reshma Saujani, Founder & CEO of Girls Who Code, talk about “aspirational AI” and what we can do to close the gap.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity

Building an AI pilot is relatively easy, but implementing it in a real-life environment is much, much harder. In real life, costs, data quality and user experience become difficult to control. Listen to guests Anupam Singh, VP of Engineering at Roblox and Nick Renotte, Chief AI Engineer at IBM, talk about why 4 out of 5 of AI pilots fail and how you can avoid yours being one of them.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity

While 81% of executives stress the importance of secure and trustworthy AI, only 24% of AI projects are secure. Is it ever ok to prioritize innovation over security when it comes to AI? Listen to Chris Thompson, Global Head of IBM X-Force Red, and Moumita Saha, Senior Security Architect at AWS talk about the generative AI attack surfaces, risks and how we can secure AI models.  

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. 

Can AI agents can make you better at your job? Listen to Ethan Mollick, Co-Director of Generative AI Lab at Wharton, for tips on how to use AI agents to be more creative and efficient.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Grammy Award-Winning Artist NE-YO and Ed Ulbrich, Chief Content Officer of Metaphysic, talk about AI ethics and risks when using AI to create art and entertain. Is AI in art about scaling and amplifying creativity, or just laziness? Can we maintain the artist to person connection when using their likeness to perform? Either way, AI is being used in art like any other technological tool, and we need the guardrails to keep what’s good.

What if instead of focusing on productivity, we used AI technology to solve our most pressing, human problems like where to find medicine or how to avoid the collapse of the banking system in Ukraine? Listen to James Hodson, Co-Founder and CEO of AI for Good, talk about how AI technology can positively transform communities, but only if we provide the necessary infrastructure and education to get people on board.    

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

The Mayo Clinic used years of data from 600,000 patients to build an AI model that can detect and predict what doctors sometimes cannot. Dr. Guru Kowlgi, a cardiac electrophysiologist at the Clinic, joins us to discuss the complexity of data curation for AI modeling and how that curation is tied to trust.

How is generative AI changing the world of marketing personalization? Gen AI is a major component in marketing automation today, and it’s important to learn how this form of AI can be used to personalize marketing content without creeping out consumers. In this episode, Emily McReynolds, head of global AI strategy at Adobe, and Pierre Charchaflian, VP senior partner and marketing practice global leader at IBM, talk about how gen AI is changing the game when it comes to personalized marketing content.

Jim "Bones" Mackay has caddied for the best golfers in the world. In his time caddying at the Augusta National tournament, he has seen and overseen thousands of winning shots across the famed Masters course. He has provided some of his firsthand insights, alongside the data collected from 180,000 historical shots over nine years of play, to help the tournament field an AI-driven app. Thanks to the app, fans worldwide can virtually stand on the green alongside the greats and gain insights into the tournament—shot by shot. In this episode, MacKay joins IBM’s Monica Ellingson to share his perspective on the story unfolding at the Masters. Together, they discuss how data-driven analysis and AI-based predictions transform the way players, caddies and fans approach the game.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. 

There’s a reason over 70% of Fortune 500 enterprises rely on mainframes to support their core operations. Despite being around since the 1950s, mainframes are not relics of the past, but rather a vital component of AI strategy and implementation. In this episode, Donna Dillenberger, IBM Fellow and CTO of Hybrid Cloud Systems Research, and Rosalind Radcliffe, IBM fellow and CTO for IBM CIO Platform Transformation, discuss how mainframes can be the nerve center that powers AI. They also talk about what it’s like to be a woman working in infrastructure and AI, and provide advice for women looking to break into the industry.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

The rise of agentic AI is significantly expanding and widening the attack surface for cybersecurity threats. As AI systems become more capable of autonomous decision-making and action, they simultaneously introduce newer vulnerabilities across workflows, data pipelines and third-party integrations. In this episode, Wendi Whitmore, Senior Vice President of Unit 42 at Palo Alto Networks, shares her views on how agentic AI is redefining the cybersecurity game for both sides: attackers and defenders. Attackers have already started leveraging agentic AI to make the cyberattack process faster and more efficient. Now, the onus is on cyber defenders to quickly harness agentic AI and build security controls that not just match but outpower the speed, sophistication and scale of new age, AI-driven cyberthreats.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. 

In this episode of the AI in Action podcast, our host, David Levy, is joined by Steve Moss, Director of watsonx Americas at IBM, to discuss HR, agentic AI, and the real-world impact of IBM’s transformation journey.  

Dive into this insightful conversation to get an insider’s look at how IBM has integrated AI agents into the HR workflow—and how you can harness their power, too. Agentic AI drives strategic shifts, boosts productivity and scales teams effectively. Learn what it takes to advance from traditional AI to agentic AI in HR and beyond.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. 

Inside IBM's Client Zero journey: https://ibm.biz/BdbW4b

AI will transform investment management over the next 5–10 years. How ready are you for this change?   

Find the answer in the new AI in Action podcast episode, where we discuss AI in finance with Ron Insana, CEO of iFi AI and longtime CNBC contributor. 

With more than 4 decades of experience, Ron has seen major shifts in the financial services industry. And now with generative AI (gen AI), he’s witnessing finance undergo another massive transformation. 

Tune in to explore how gen AI is revolutionizing financial services, enhancing productivity and reshaping the investment management landscape. Learn how you can harness AI to future-proof your finance organization. 

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. 

AI news is moving fast. Keep your business ahead with updates about AI advancements, strategies and expert perspectives → https://ibm.biz/BdnXVJ

AI is changing the dynamics of every field—and sales is no exception. But what does that look like in action?

In this episode, Morgan Ingram, founder and CEO of AMP Creative, explains how AI substantially increases the active selling time of sales professionals by automating the grunt work.

For example, AI slashes the proposal creation time from hours to minutes. And that’s not it—AI also helps craft sharper, more personalized sales messages that improve response rates and drive higher revenue.

Watch the full discussion on how you can AI-optimize your sales workflow, empowering sellers to focus on what matters—closing deals and boosting the bottom line.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

In today’s dynamic and fast-paced world, focusing solely on productivity won’t cut it. C-suite leaders need to step up and drive strategic business transformation with the power of AI agents.

Joining us on the AI in Action podcast this time is none other than Allie K. Miller, CEO of Open Machine. In the episode, Allie shares powerful insights on how agentic AI is revolutionizing business operations—and what C-suite leaders must do to stay ahead of the curve.

Watch the full discussion to learn why agentic AI isn’t an upgrade—but a game-changer. Also, while employees must upskill to thrive in the AI era, leaders have a greater responsibility: adopting AI agents without disrupting the balance between technology and humans.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Finding a house that matches your budget and style doesn’t have to be a struggle. All you need is the right AI tool that can open the door to your dream abode. And that’s precisely what Redfin is offering with their AI-driven real estate solutions.

In this episode of the AI in Action podcast, Ariel Dos Santos, SVP of Product and Design at Redfin, shares how they’re using AI to transform the house-hunting process. Redfin is tapping into vast amounts of data to understand buyers’ preferences and provide tailored recommendations, making it easier for people to make their next big move.

Tune in for a detailed insight into Redfin’s AI vision—and how it’s going to make the home search process smarter, smoother and a lot more fun.

Operational disruptions don’t come unannounced. There are always early warning signs—if only you have the right observability solution to catch them before they snowball into costly outages.

In this episode of the AI in Action podcast, Vikram Murali, VP of Software Development for IBM Automation, explains how continuous observability has taken the baton from traditional monitoring, giving a new meaning to operational resilience.

Observability has transformed reactive measures into proactive steps, leading to more seamless operations and fewer costly disruptions. Catch the full discussion to learn how you can run your business smoothly by tapping into the combined power of observability, automation and remediation.

0:00 Intro

03:35 How do AI solutions affect observability?

07:35 How much visibility does observability provide?

12:26 The difference between good and bad observability tools

20:21 Choosing the right data for the observability tool

23:42 Balancing power and control in agentic frameworks

26:33 Getting started with observability

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

The data flood is real. And you can either use it to power your decisions or drown in it and lose your way.

In this episode of the AI in Action podcast, Cassie Kozyrkov, CEO of Koyzr, explains the concept of decision intelligence, which is based on data, AI and human insight.

Cassie emphasizes that while most organizations are busy collecting vast amounts of information, this effort is only valuable when the data leads to better choices or smarter decisions.

And this is where decision intelligence comes into play. It helps leaders make sense of data, use generative AI wisely, and base decisions on what truly matters. Catch the full discussion to learn how you can do data-driven decision-making and create real impact within your business.

0:01 Intro

06:13 Data usage matters more than data size

11:03 How to separate good data from bad

16:12 Handling irrationality in human decisions

20:49 Data choices reflect personal priorities

26:50 Our experiences shape AI bias

30:13 Should we limit data collection?

AI is using more energy than ever, but it’s also making us more productive and efficient. So how can we dial down energy consumption without losing the momentum?

Let’s find out from Joseph Majkut, Director of the Energy Security and Climate Change Program at the Center for Strategic and International Studies (CSIS).

In this episode of AI in Action, Joseph talks about the critical intersection of AI and energy, explaining the impact of AI on power grids and discussing the potential solutions for efficient power generation.

Watch the full episode to discover how AI poses both challenges and opportunities for energy consumption, focusing on generative AI data centers, energy efficiency, and the role of nuclear power.

Timestamps:

0:00 Intro

06:18 AI demand versus energy supply

09:18 Easing energy demand through infrastructure and operations

12:44 Reframing energy use in AI workflows

15:46 The most compelling aspect of how AI meets energy

19:13 Advice for leaders on using AI without overloading the grid

Is generative AI just a productivity hack—or your team’s secret to loving work again? Deborah Lovich, Managing Director and Senior Partner, Boston Consulting Group, believes that when AI is used to decrease the grind and increase the joy, employees embrace it instead of resisting.

Hence, Deborah encourages businesses to develop AI tools with employees, equip managers to lead AI adoption and customize AI learning opportunities. The result? Motivated teams, lower churn and bigger profits.

Catch the full discussion to learn how you can transform work by putting your people at the center of all AI initiatives.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

AI in retail is no longer a buzzword. It’s a reality, and Tractor Supply Company has been one of the pioneers in driving it forward.

In this conversation, Glenn Allison, VP of AI platforms at Tractor Supply Company, explains how AI communicators, mobile apps and computer vision are making life easier for teams and creating a truly AI-enabled customer experience.

Watch the episode to witness generative AI in action. Discover how it’s reshaping workflows, powering decisions and fueling innovation across retail.

Timestamps:

0:00 Intro

03:34 Balancing AI innovation and operations

06:09 AI agents transforming retail

12:54 Scaling up for AI

17:25 Continuous learning in the age of AI

19:56 Boosting ROI through AI

22:40 The workforce response to AI

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. 

AI news is moving fast. Keep your business ahead with updates about AI advancements, strategies and expert perspectives → https://ibm.biz/BdnXVJ

#AIinRetail #TractorSupply #ArtificialIntelligence #CustomerExperience #Innovation #GlennAllison #DavidLevy

AI and robotics are revolutionizing industrial work and automation by enhancing efficiency, reducing costs and safeguarding human workers from hazardous tasks.

In this episode, Aaron Saunders, CTO of Boston Dynamics, delves into the transformative potential of AI-powered robotics, highlighting how robots are becoming safer, more cost-effective and widely accessible through Robotics as a Service (RaaS).

He shares real-world applications of industrial robotics, insights into ROI and the shift from deterministic systems to open-ended technologies, while also addressing key challenges, such as managing expectations and ensuring data privacy. 

Timestamps:

0:00 Intro

03:03 The future of robots with generative AI

07:22 Beyond warehouses: New uses for AI robots

12:29 ROI from AI-powered robotics

15:13 The next phase of AI and robotics

18:41 Guidance for CTOs on AI and robotics

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. 

AI news is moving fast. Keep your business ahead with updates about AI advancements, strategies and expert perspectives → https://ibm.biz/BdnXVJ

#AI #Robotics #IndustrialAutomation #RoboticsasAService #ReturnOnInvestment #SafetyInAutomation #FutureTech #AaronSaunders #DavidLevy 

Explore the podcast → https://ibm.biz/Bdbvh4

AI can drive transformation or create new vulnerabilities. The difference lies in how we lead. In this episode of AI in Action, former CISA Director Jen Easterly joins David Levy to discuss the intersection of AI governance and cybersecurity, and how leadership and accountability shape both.

Watch the episode to understand how security guardrails, robust systems, and a culture that values safety as much as speed can help organizations innovate boldly yet responsibly. Because real AI-based innovation isn’t just smart. It’s also safe.

Timestamps:

0:00 Intro

0:55 Jen Easterly’s journey from national security to AI governance

2:28 How imagination shapes innovation and risk

4:06 Innovation under pressure in the field

7:04 The power of data and information-driven defense

8:25 Agentic AI is transforming both defense and attack

9:45 Making security part of software design

13:50 Accountability and leadership in AI governance

17:39 Creating a culture that values safety and innovation

24:17 Collaboration, resilience and the future of AI security

28:04 Emerging AI threats and the evolving security landscape

30:12 Key takeaways on leadership, accountability and trust

AI news is moving fast. Keep your business ahead with updates about AI advancements, strategies and expert perspectives → https://ibm.biz/BdbSUv

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Explore the podcast → https://ibm.biz/BdbYhM

Learn about AI agents for procurement → https://ibm.biz/BdbYhS

Procurement is stepping into the future with AI. In this AI in Action episode, expert Daniel Barnes chats with David Levy about how agentic AI is shaking up procurement, which has long been stuck in spreadsheets and slow processes.

Watch the episode to understand how AI is pulling insights from contracts, vendor documents and other datasets, empowering procurement teams to make smarter, faster decisions. Also, learn how some companies are stumbling by trying to AI everything at once. Companies need to understand that the smart move is to start small and then scale up.

0:00 - Intro

02:14 - Data management in procurement

08:45 - How agentic AI has changed procurement

13:10 - How AI and data are redefining vendor evaluation

17:17 - Getting CPOs started with the right technology

23:54 - The rise of agentic negotiators

26:37 - Risks of ignoring AI-driven procurement opportunities

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Most companies struggle with AI. And it’s usually not because the technology doesn’t work, but because the right adoption approach isn’t followed.

As Conor Grennan, Chief AI Architect at New York University, puts it, treating AI like a digital transformation initiative is a recipe for failure. What actually works is when leaders move beyond rolling out AI tools and drive the behavioral shift that sets clear expectations and enables real change.

When leadership teams get the people part right, they can avoid the usual mistakes, align teams on what matters and turn AI into real business results.

Learn about AI agents and application architecture → https://ibm.biz/BdbR2B

0:00 Intro

04:52 AI adoption is a behavioral challenge

07:55 AI isn’t digital transformation

11:30 The risk of using AI agents as mere replacements

16:31 Finding the AI champion who drives change

18:18 The shift from commands to conversations

22:39 The foundation for scaling AI workflows

32:22 Why AI agents aren’t just machines

33:15 Trust, hallucinations and the data problem

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

AI news is moving fast. Keep your business ahead with updates about AI advancements, strategies and expert perspectives → https://ibm.biz/BdbdvS

Explore the podcast → https://ibm.biz/Bdbbwt

Every company is sitting on a mountain of data, but only a few know what to do with it. In this episode of AI in Action, Madison Faulkner talks with David Levy about turning data chaos into clarity. She explores how agentic AI depends on strong data management and data governance, and why unstructured data and big data only create value when they’re organized with purpose. In other words, the real competitive edge isn’t the AI itself; it’s the data behind it. Because in the end, intelligent systems are only as powerful as the data that trains them.

0:00 Intro

1:35 Madison Faulkner’s journey

2:40 The birth of data science

4:00 Bridging Silicon Valley hype with real-world industries

8:40 Structuring unstructured data for agentic AI

12:00 Automation, knowledge graphs and agentic sourcing

16:40 Tactical and organizational failures in data strategy

20:30 Data as code: The next wave of infrastructure

24:00 Rethinking data foundations for agentic AI

30:12 Turning data governance into a real business advantage

33:45 Final takeaways: Clarity over chaos in the AI era

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

AI news is moving fast. Keep your business ahead with updates about AI advancements, strategies and expert perspectives → https://ibm.biz/Bdbbw6

#DataStrategy #EnterpriseAI #AIforBusiness #DataLeadership #BusinessIntelligence #AgenticAI #DataDrivenBusiness #DataManagement #MadisonFaulkner #DavidLevy

Explore the partnership → https://ibm.biz/BdbTR7

In this AI in Action episode, David Levy talks with Alon Cohen about how the UFC has turned its deep history of data into clear, meaningful insights. Alon shares how the team has moved from basic number tracking to smart systems powered by machine learning, computer vision and NLP. Thanks to better data management and processing, the team can measure speed, power and even fighter intent with far more accuracy.

He explains why combat sports are challenging in terms of AI and data analysis, and how IBM watsonx® helps deliver real-time insights to fans and commentators. The episode also covers why building good AI takes patience, steady improvement and the careful judgment of people who truly understand the sport.

0:00 Intro

04:11 Understanding MMA athletes and the culture

07:17 Identifying the opportunity for statistical analysis in UFC

09:28 The challenges of AI with real-time fight data

16:24 How the UFC uses IBM watsonx® to power UFC Insights

21:34 What data reaches UFC commentators

25:14 How IBM and UFC built and trained the models

31:08 How UFC measures the success of AI-driven fan experiences

34:02 Advice for businesses advancing with AI

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Can agentic AI solve the scalability challenge in wealth management while expanding access to underserved communities?

Ramona Ortega believes it can, but only with the right foundation. She explains how WealthBuild has moved from basic chatbots to RAG and now to agentic workflows that can deliver accurate and personalized guidance at scale. In her opinion, the real blockers aren’t algorithms but messy data, governance gaps and enterprise-grade security.

Since traditional financial services can’t reach many everyday consumers, she partners with community banks to close the gap. For her, the future lies where AI, APIs and blockchain meet, opening the door to accessible and democratized financial advice.

Explore the podcast → https://ibm.biz/BdbuaR

In this AI in Action episode, David Levy talks with Yashodha Bhavnani, Head of AI at Box, about how enterprises can turn massive volumes of unstructured data into high-value intelligence.

Yashodha explains how Box is embedding AI into its content platform for easier data management without compromising security or governance. She shares real-world examples of enterprise content management and explains how agentic AI powers smarter workflows.

The conversation also covers the role of IBM watsonx® in Box AI and what it takes to bring AI from experimentation into production.

The Recording Academy is thoughtfully integrating generative AI to improve efficiency, accuracy and fan engagement across the GRAMMYs. David Gregory, CIO of the Recording Academy, describes using AI solutions, machine learning and large language models to streamline the GRAMMY Awards submission and voting process while preserving human oversight and strong AI governance.

Fan-facing tools like GRAMMY IQ, an AI-powered chatbot, enhance grammy.com through interactive trivia and historical insights. Collaborating with IBM and others, the Recording Academy is exploring AI agents and advanced analytics across archives, membership platforms and operations. Their overall vision is to drive innovation balanced with responsibility, creativity and trust.

0:00 Intro

05:01 How GRAMMY IQ elevates the fan experience

06:43 Beyond GRAMMY IQ: The future of AI at the GRAMMYs

12:10 Leading the AI initiatives with caution and clarity

17:43 Driving member value with AI and digital transformation

21:54 Operationalizing AI across the Recording Academy

25:08 What every CIO should know about getting started with AI

27:14 What’s next for AI at the Recording Academy

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

In this AI in Action episode, David Levy speaks with Lorie Meola about how IBM is transforming procurement through AI adoption and data management. Lorie explains how focusing on good-enough enterprise data, supported by data transparency and data visualization, leads to faster insights and better decisions.

She shares how agentic AI helps teams move away from manual work and focus on higher-value outcomes. The conversation also highlights the cultural change required for digital transformation, including leadership support and iteration. The episode shows how modern procurement can drive efficiency, insight and business impact across the enterprise.

Inside IBM's Client Zero journey: https://ibm.biz/BdbW4b

In the latest episode of AI in Action, Bernard Marr shares his perspective on how AI is changing the way we work and why AI literacy is becoming essential for every organization. He explains that real AI-driven business growth starts with a clear strategy. To make AI work at scale, companies need strong data foundations, modern data architecture and solid data management practices.

Many organizations still struggle with siloed systems, weak governance and low data literacy, which hurts their competitive edge. Bernard encourages leaders to connect business intelligence with AI goals, rethink existing processes and give teams space to experiment. From agentic AI to quantum computing, he reminds us that change is happening fast and that a thoughtful, strategic approach to AI is key to building future-ready organizations.

0:00 Intro

03:47 What AI really means for companies in 2026

06:47 Scaling AI starts with strategy

10:42 Leading the cultural shift to AI

13:17 Competitive advantage starts with AI awareness

18:14 The real barriers to scaling AI

28:33 What enterprises can learn from AI startups

30:58 Top trends for data and AI leaders

34:24 Overcoming data and governance challenges

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

AI news is moving fast. Keep your business ahead with updates about AI advancements, strategies and expert perspectives → https://ibm.biz/BdpEkq

On AI in Action, IBM researcher Campbell Watson explains how foundation models are accelerating discovery across Earth and space science. Moving beyond traditional numerical methods, his team applies concepts from large language models to multimodal satellite data to build powerful, open-source AI systems.

In collaboration with NASA and the European Space Agency, they have developed foundation models for Earth observation, weather and heliophysics. They are using AI for sustainability use cases, such as flood detection, biodiversity monitoring and solar flare forecasting.

Designed for hybrid cloud environments and even deployed in orbit, these models point toward a future where AI and quantum computing unlock deeper planetary insights.