The AI Table

About The AI Table

Discussing AI topics that matter. www.theaitable.org

Publisher

The AI Table

Category

business · technology

Language

en

Explicit

No

First episode

5 Jun 2026

Latest episode

14 Oct 2026

Latest episodes

12 episodes in the feed.

1. 

   14 Oct 2026

   How Comcast Solved the AI Productivity Paradox

   Why are companies seeing massive productivity gains on paper, yet failing to see it hit the bottom line? In this episode of The AI Table, we sit down with David Krause to unpack the AI Productivity Paradox—the glaring gap between perceived AI output and actual financial returns. If your board is asking for hard proof of AI ROI, this conversation is your blueprint. We cut through the hype to explore why traditional metrics are breaking down, how to draw a hard line between human and machine output, and why proper governance and clear ownership are the ultimate differentiators between AI success and expensive shelfware. Key Takeaways: The Earnings Gap: Why standard productivity metrics fail to capture true AI profitability. Accountability Frameworks: Defining who actually owns model performance and risk inside the enterprise. Governance at Scale: How to manage vendor models and structure AI steering committees that drive action, not bureaucracy. The Human Element: Why expert judgment and rigorous change management are more critical than ever in the agentic era. Chapters: 00:00 — The AI Productivity Paradox 03:45 — Measuring True AI Impact 05:17 — Distinguishing Human vs. AI Actions 10:40 — Ownership and Accountability in AI 14:01 — Governance of Vendor Models 16:54 — The Role of AI Steering Committees 22:44 — Critical Evaluation in the AI Era 28:12 — The Importance of Expert Judgment 30:15 — Defining Business Metrics That Matter 34:01 — Change Management in Metrics 36:44 — Debunking Common AI Myths #TheAITable #EnterpriseAI #AIReturns #AIGovernance #DataStrategy #AILeadership #AIROI #AIstrategy

2. 

   8 Oct 2026

   The Truth About AI Fortune 500 Leaders and Workers Don’t Want to Hear

   Dia Adams sits down with Wall Street AI Guru Max Gokhman (Head of AI at Franklin Templeton) to break down the hard truths of enterprise AI implementation. Moving beyond the hype, they explore why corporate culture is the ultimate bottleneck to AI adoption, how organizations are actually measuring AI ROI, what AI job loss could look like in the future, and the critical need for model explainability and governance in automated decision-making. Discover what it takes to transition from experimental AI chat interfaces to secure, autonomous enterprise workflows without falling into common productivity and security traps. Key Takeaways: Why cultural adaptation is a prerequisite for successful enterprise AI deployment How to measure real AI success and corporate productivity beyond vanity metrics The vital role of model explainability and zero-trust governance in AI decision-making Navigating the build vs. buy dilemma for scalable enterprise AI infrastructure Chapters: 00:00 Merging AI with Human Expertise 08:11 Measuring AI Success in Enterprises 11:05 The Future of AI and Productivity 14:57 Understanding AI's Limitations 18:25 Navigating AI Risks and Governance 22:18 Ethics and Morality in AI Decisions 26:31 Model Explainability and Trust 29:31 Building vs. Buying AI Solutions 32:47 Transitioning to Autonomous AI Systems 35:43 AI Pet Peeves and Concerns #EnterpriseAI #AIGovernance #ArtificialIntelligence #DataStrategy #AIAdoption #TechLeadership #MaxGokhman #DiaAdams #TheAITable

3. 

   1 Oct 2026

   Why Legacy Data Stacks Fail AI Agents (And How Modern Teams Are Fixing It)

   In this episode of The AI Table, Dia Adams sits down with Jenna Zhang, the first University Chief Data & AI Officer in the midwest, to unpack the shift transforming education: the jump from legacy data stacks to real-time, agentic AI. They break down why traditional data governance fails in autonomous environments, how to bridge the communication gap between data leaders and the C-suite, and where the biggest innovation opportunities lie for modern enterprise leaders. Unlock Enterprise AI Authority To lead in the agentic era, you need strategy over hype: Subscribe to The AI Table Newsletter: Receive executive-level breakdowns on AI governance, agentic workflows, and data strategy delivered straight to your inbox at theaitable.org/newsletter (https://www.theaitable.org/newsletter). Join The AI Table Membership: Gain exclusive access to peer networks, strategic briefings, and enterprise frameworks designed for senior data and AI leaders. Apply for Pro Membership at theaitable.org (https://www.theaitable.org/). #aistrategy #AgenticAI #DataGovernance #EnterpriseAI #EdTech #TheAITable #aigovernance Takeaways Shift from data for humans to machines Importance of data governance in AI Chapters 00:00 The Evolution of Data Management 02:02 Understanding Agentic AI 03:33 Defining True Data Products 05:45 Persuading Leaders on Data Value 08:02 Navigating AI Pressure as a Leader 09:43 Transforming Raw Data into Value 12:28 Universal Standards for Data Integration 14:00 Real-Time Data Pipelines in AI 16:21 Investing in Agent-Ready Data Products 21:03 Accountability in Data Ownership 23:37 Encouragement for Future Builders

4. 

   24 Sept 2026

   The Real Reason Your Team Is Resisting AI | Harvard Business School Professor David Almog

   Harvard Busines School Professor David Almog sits down at The AI Table. The conversation explores the intersection of human behavior and AI, addressing the fear of over-reliance on AI, cognitive and social frictions in AI adoption, human oversight of AI systems, incentive structures and AI adoption, the impact of AI on skill tiers, experience levels and AI reaction, and incentive schemes for AI productivity. Takeaways Understanding human behavior is crucial for successful AI adoption. Incentive structures and human oversight play a significant role in AI adoption and productivity. Chapters 00:00 Understanding Human Behavior and AI 02:32 Fear of Over-Reliance on AI 08:03 Cognitive and Social Frictions in AI Adoption 12:09 Human Oversight of AI Systems 15:16 Incentive Structures and AI Adoption 17:07 Impact of AI on Skill Tiers 18:43 Experience Levels and AI Reaction 22:09 Incentive Schemes for AI Productivity If you enjoyed our podcast please leave a review and subscribe. To become a memeber of The AI Table visit: https://www.theaitable.org/membership (https://www.theaitable.org/membership)

5. 

   18 Sept 2026

   Leveraging AI at $300B Scale: Lessons from McKesson’s CDO

   The conversation with Zachary Elewitz covers a range of topics related to AI governance, risk management, and the future of AI-enabled workforce. Zachary shares insights on balancing AI experimentation with risk governance, collaborative governance, centralized vs. decentralized AI labs, translating soft efficiency metrics into hard financial value, AI governance frameworks, building vs. buying AI solutions, professional support and skill sets for AI enablement, and the future of workforce enabled by AI. Chapters 00:00 Introduction and Background 01:23 Balancing AI Experimentation and Risk Governance 03:50 Collaborative Governance and Legal Compliance 08:15 Centralized vs. Decentralized AI Lab 11:31 Translating Soft Efficiency Metrics into Hard Financial Value 15:00 AI Governance Frameworks for Speeding Up Innovation 17:37 Building vs. Buying AI Solutions 22:29 Professional Support and Skill Sets for AI Enablement 33:17 Future of Workforce Enabled by AI 36:07 AI Pet Peeves and Key Messages

6. 

   10 Sept 2026

   How Walmart Scales Agentic AI: Data Products, Governance & ROI

   How does a Fortune 1 company build a data foundation built for autonomous AI agents? In this episode of The AI Table, host Dia Adams sits down with Amit Shivpuja, Walmart AI Executive, to break down the real-world operational strategy behind enterprise AI at massive scale. From solving the data-to-business misalignment gap to transforming compliance-heavy governance into value-generating data products, Amit shares the frameworks every CDO, CIO, and enterprise AI leader needs to navigate the shift to Agentic AI. CHAPTERS: 00:00 - Introduction & Walmart's AI Strategy 01:40 - Solving Data & Business Team Misalignment 04:09 - The 3-Layer Approach to Data Products for AI Agents 07:25 - Hurdles to Becoming AI-Ready at Scale 10:30 - Early Signals Your Data Foundation is Ready 12:07 - High-Value Use Cases vs. Speculative AI Pilots 13:57 - Rethinking Data Governance for Value Generation 16:25 - Immediate Operational Shifts from Agentic AI 18:10 - Translating Technical Agentic Concepts for the C-Suite 20:36 - Global AI Ethics & Policy Adoption 24:14 - The Evolving Role of the Chief Data Officer (CDO) 27:28 - Capital Allocation & The Future of Data Professionals 💡 SUBSCRIBE TO THE AI TABLE: Join 800+ Fortune 500 CIOs, CDOs, CAIOs, and Federal AI leaders receiving our executive intelligence newsletter: https://shorturl.at/AabH3 (https://shorturl.at/AabH3) CONNECT WITH US: Website: https://www.theaitable.org (https://www.theaitable.org) #AgenticAI #DataStrategy #AILeadership #EnterpriseAI #WalmartTech #DataProducts #ChiefDataOfficer

7. 

   3 Sept 2026

   Human-Centered AI: Why Corporate AI Needs a Heartbeat

   Tiankai Feng discusses the importance of humanizing AI and data strategy, emphasizing the need for a human-centric approach to technology. He shares his passion for making data and AI more accessible and approachable, and highlights the significance of considering human needs and opinions in technological choices. Takeaways Humanizing AI and data strategy Importance of human-centric design #HumanizingAI #CorporateAI #FutureOfWork #DataStrategy #TechLeadership Book: https://a.af/6mmum (https://a.af/6mmum) www.theaitable.org

8. 

   3 Jul 2026

   The Context Layer for Enterprise AI: Ontologies, Knowledge Graphs & Meaning

   Why are billion-dollar enterprise AI initiatives stalling out in production? In this episode of The AI Table, former Adobe Senior Information Architect and taxonomy veteran Jessica Talismanbreaks down why raw LLMs fail inside large enterprises—and why the secret to reliable, non-hallucinating agentic AI isn’t bigger models, but the Context Layer. Most enterprise AI pipelines fail because they treat data as a technical storage problem rather than a knowledge management challenge. Without a formal ontology pipeline, enterprise knowledge graphs, and semantic data models, AI agents lack the business logic, data provenance, and procedural context required to deliver accurate outcomes. Jessica walks us through how Fortune 500 leaders can leverage library science principles to turn messy unstructured data into deterministic, decision-ready intelligence. Key Takeaways AI bias stems from flawed training data, so businesses must prioritize context and knowledge management to address it. Responsible AI demands a human-centered approach, investment in knowledge systems, and a focus on augmenting—not replacing—human capabilities. Key Executive Takeaways The Context Gap: AI bias and hallucinations stem from unvetted, context-free data pipelines. Fixing AI output requires fixing the semantic architecture underlying your models. Ontologies as Defensive Assets: A formal ontology model provides the rules, relationships, and lineage necessary for autonomous agents to execute complex workflows safely. Human-Centered Augmentation: Responsible enterprise AI execution focuses on structuring tacit human knowledge to augment—not replace—high-value workforce decisions. 🔗 Connect & Learn More Subscribe to The AI Table (www.theaitable.org) for weekly executive briefings on AI strategy, enterprise architecture, and data governance.

9. 

   19 Jun 2026

   Preparing CEOs and Corporate Boards for Successful AI Implementation

   Most organizations are still unprepared for the real challenges AI brings. This episode with Chief Data Officer Elena Alikhachkina cuts through the noise to tackle what actually matters: governance, accountability, and leadership in the age of intelligent systems. We explore why AI initiatives fail more often than they succeed—and how “shadow AI” is quietly introducing risk into even the most sophisticated organizations. More importantly, we break down what executives must understand now to stay competitive: from building formal AI education pathways to redefining decision-making frameworks at the highest levels of leadership. If you’re a CEO, Chief Data Officer, CIO, CTO, Chief Compliance Officer, or board-level executive, this conversation is essential. The future of your organization depends not just on adopting AI—but on governing it effectively, measuring its value, and ensuring your leadership team is truly AI-literate. Topics covered: Why most AI projects fail—and how to fix it The hidden risks of shadow AI inside your organization How to quantify the ROI of AI governance Why AI literacy is now a board-level priority The evolving role of executives in an AI-driven enterprise Subscribe for more insights at the intersection of AI, leadership, policy, and enterprise strategy. Contact: LinkedIn: https://www.linkedin.com/company/yourcompany (https://www.linkedin.com/company/yourcompany) Website: www.theaitable.org #AILeadership #AIGovernance #AITransformation #AIliteracy #CDO #corporateboard #EnterpriseAI #AICompliance Chapters 00:00 The Role of Accountability in AI Governance 05:36 The Need for Formal Curriculum in AI Education 13:06 Preventing Cross-Functional Gridlock in AI Deployments 18:52 Challenges in AI Project Success and Quality of Decisions 35:07 Workforce Development and AI Literacy 40:25 Demystifying AI for Non-Technical Executives Visit Us: www.theaitable.org Listen to more talks: https://www.theaitable.org/podcast

10. 

    12 Jun 2026

    Is AI Making us Stupid?: Thinking in the Age of AI

    Sune Selsbæk-Reitz AI strategist and tech philosopher discusses the concept of promptism (outlined in his new book) and its impact on decision-making and critical thinking. He emphasizes the importance of using AI as a sparing partner rather than a substitute for human judgment in appropriate instances. The conversation delves into the dangers of AI fluency and the fight for meaning in the age of AI, highlighting the need for thoughtful engagement with AI-generated content. Takeaways Promptism: The habit of treating AI generated text as if it were already understanding and factual, leading to a lack of questioning. AI and Critical Thinking: Using AI as a sparing partner in the thinking process, allowing it to enhance human thinking without substituting for it. The Fight for Meaning: The importance of cultivating doubt and thoughtful engagement with AI-generated content to protect competitive advantage and the meaningful aspects of decision-making. Visit us: www.theaitable.org Purchase Promptism: https://lnk.ink/wbPWb (https://lnk.ink/wbPWb) Listen to more talks on our site: https://www.theaitable.org/podcast (https://www.theaitable.org/podcast) #promptism #ailiteracy #aistrategy #AIPartnership #responsibleai #humanaicollaboration #humanfirstai

11. 

    7 Jun 2026

    AI and Kids: The Conversation Parents and Policymakers Can't Afford to Skip

    The conversation with Amber Ivey, author of "AI meets AI" covers the importance of AI literacy for kids and the need for AI guardrails for kids. It delves into the impact of AI on children's interactions, social media addiction, parental role in AI literacy, kids' perspectives on AI, policy at federal and state levels, AI literacy resources for parents, and the under-discussed risks of improper AI use for kids. Chapters 00:00 Introduction and Background 06:07 Practical Engagement with AI 11:59 Social Media and AI Addiction 18:02 Parental Role in AI Literacy 24:04 Considerations at Federal and State Level 29:49 Under-discussed Risks of AI for Kids Visit us: www.theaitable.org (http://www.theaitable.org) Listen to more talks: https://www.theaitable.org/podcast (https://www.theaitable.org/podcast)

12. 

    5 Jun 2026

    The AI Trust Crisis: Fabricated Reports and Biased Hiring, How to Fix Broken AI Systems

    Reid Blackman dives into the urgent dilemmas of AI—from HR tools facing lawsuits for scraping social media data and discriminating against older job applicants, to big consulting firms publishing AI-generated reports with fabricated citations. He explores how these issues are reshaping trust, accountability, and even mental health. Blackman shares why he wrote The Ethical Nightmare Challenge, exposing the gaps in standard AI governance and introducing his Ethical Nightmare Challenge (ENC) framework—a practical approach to identify and mitigate AI risks before they escalate. He makes the case that responsible AI is a business imperative, with clear ROI for companies that get it right. Whether you’re a CEO navigating regulatory landmines, a tech leader building responsible systems, or a parent concerned about AI’s impact on society, this conversation will push you to ask: What’s the worst that could happen—and how do we stop it? Takeaways Evolution of AI has led to a complex risk landscape Standard AI governance is inadequate for the evolving technology The Ethical Nightmare Challenge framework offers a scalable and outcome-oriented approach to AI governance Visit us: www.theaitable.org Listen to more talks: https://www.theaitable.org/podcast

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Public platform figures. Ratings count people who left a rating, not total listeners.

Apple Podcasts (US)

5.0 / 5

10 ratings

Spotify

5.0 / 5

16 ratings

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