In this episode of The CTO Show with Mehmet, Mehmet Gonullu sits down with Betsy Atkins, serial entrepreneur, board member of global companies, and advisor to leading organizations including Google Cloud.

The conversation explores how the role of the board is evolving in an era defined by AI, agentic systems, and accelerating technological change. Betsy shares deep insights on how boards must move from passive oversight to active orchestration, the risks introduced by agentic AI, and what leaders must do today to stay relevant.

From “corporate cholesterol” slowing down organizations to the emergence of AI governance frameworks, this episode offers a candid look at the challenges and opportunities shaping the next generation of leadership.

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👤 About the Guest

Betsy Atkins is a three-time CEO, serial entrepreneur, and globally recognized corporate governance expert. She has served on over 30 public and private company boards and currently sits on the Google Cloud Advisory Board, as well as boards including Wynn Resorts and goPuff.

Betsy brings decades of experience across venture capital, private equity, and public markets, advising leadership teams on digital transformation, governance, and innovation.

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🔑 Key Takeaways

• Boards are shifting from passive oversight to active involvement in technology and innovation

• Agentic AI introduces new risks that require structured governance and monitoring

• “Corporate cholesterol” slows companies down as they scale and must be actively removed

• AI governance will become as critical as cybersecurity oversight

• Founder-led companies must carefully select board members based on mindset, not just resumes

• Decision speed and adaptability are now core competitive advantages

• There is currently no clear “kill switch” for agentic AI systems, creating new risk categories

• Investors must rethink due diligence to properly evaluate AI-driven companies

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📚 What You Will Learn

• How the role of the board is evolving in the age of AI

• The concept of “corporate cholesterol” and how it impacts growth

• How to build AI governance frameworks inside organizations

• The real risks behind agentic AI and autonomous systems

• What founders should look for when building their boards

• How investors should evaluate AI capabilities during due diligence

• Why execution speed is becoming a key differentiator

• The future of leadership in an AI-driven world

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⏱️ Episode Highlights

00:00 Introduction and Betsy Atkins’ background

02:45 How boards have evolved from oversight to active engagement

05:30 The concept of “corporate cholesterol” and organizational drag

08:40 Innovation vs. risk in public and private companies

11:00 Founder-led boards and selecting the right directors

17:30 AI’s impact on organizational structure and decision-making

21:00 Agentic AI risks and real-world experiments

25:00 Balancing innovation and governance in AI adoption

30:00 Who owns AI governance inside the organization

33:00 The need for monitoring, orchestration, and control systems

35:30 The “kill switch” debate and future AI risk

40:30 AI due diligence for investors and common mistakes

44:30 Key technology trends shaping the next decade

48:00 Optimism vs. risk in the future of AI

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🔗 Resources Mentioned

• Betsy Atkins Website: https://betsyatkins.com/

• Betsy Atkins LinkedIn: https://www.linkedin.com/in/betsy-atkins-a36b114/

• Anthropic research on AI agent behavior: https://www.anthropic.com/research/agentic-misalignment

Tokenization has moved beyond hype. The real opportunity is no longer in creating tokens, but in building the infrastructure that allows real-world assets to operate at scale.

In this episode, Mehmet speaks with GP Worrell, Co-Founder and CPO of Blubird, about the evolution of Web3 from speculation to systems. They explore why most tokenization projects fail, how modular infrastructure changes time-to-market, and why compliance, trust, and operational systems are becoming the true moats in the space.

The conversation also dives into AI’s role in Web3, the shift from ICO-era hype to real assets, and what it takes to build scalable, institutional-grade platforms in a rapidly maturing market.

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👤 About the Guest

GP Worrell is the Co-Founder and Chief Product Officer at Blubird, a platform focused on building the infrastructure layer for tokenized real-world assets.

With over two decades of experience across enterprise systems, fintech, and blockchain, GP has been active in the Web3 space since 2016. At Blubird, he focuses on enabling institutional-grade tokenization through compliance, governance, onboarding, reporting, and lifecycle management.

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🚀 Key Takeaways

• Tokenization alone is not enough, infrastructure is where long-term value is created

• Most projects fail not because of tech, but due to lack of market fit and distribution

• Modular platforms dramatically reduce time-to-market from months to weeks

• Compliance, governance, and reporting are critical for institutional adoption

• Real-world assets differ fundamentally from NFTs and speculative tokens

• Infrastructure creates operational trust across issuers, investors, and regulators

• AI will play a supporting role, especially in compliance and decision-making workflows

• The Web3 market is maturing, but still far from fully developed

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🎯 What You’ll Learn

• Why tokenization is shifting from hype to infrastructure

• How modular systems are transforming Web3 development

• The biggest mistakes founders make in the RWA space

• What makes a tokenization platform scalable and compliant

• How regulators view trust in tokenized assets

• The role of AI in Web3 platforms and infrastructure

• The future of tokenization in real estate, commodities, and beyond

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⏱️ Episode Highlights

00:00 – Introduction and GP’s background

01:00 – What Blubird is building in tokenization infrastructure

02:00 – Why infrastructure matters more than tokens

03:00 – From bespoke tokenization to modular systems

04:00 – Common mistakes founders make in Web3

05:00 – Explaining tokenization using Web2 analogies

06:00 – Real-world asset examples and use cases

07:00 – What is defensible in tokenization platforms

08:00 – Speed, scale, and time-to-market advantages

09:00 – Compliance, KYC, AML and institutional requirements

10:00 – Trust, regulators, and infrastructure layers

11:00 – Impact on investor confidence and adoption

12:00 – Government use cases and institutional focus

13:00 – Tokenization as a fundraising tool for founders

14:00 – Why infrastructure alone is not enough

16:00 – Market fit, GTM, and why projects fail

18:00 – Blockchain choice vs business fundamentals

19:00 – The role of AI in tokenization platforms

21:00 – Product leadership in Web3 vs Web2

24:00 – Emerging use cases beyond real estate

26:00 – Lessons from ICOs and market evolution

29:00 – Why the market is maturing but not mature

31:00 – Parallels between Web1, AI, and Web3

34:00 – The future “ChatGPT moment” for tokenization

35:00 – Final thoughts and where to connect

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🔗 Resources Mentioned

• Blubird: https://www.getblubird.com/

• GP Worrell on LinkedIn: https://www.linkedin.com/in/gpworrell/

AI is moving faster than security, and the gap is widening.

In this episode, Mehmet sits down with Walter Haydock, Founder of StackAware, to explore how organizations can safely deploy AI while managing growing risks across cybersecurity, compliance, and governance.

As AI systems become embedded in products, operations, and decision-making, traditional security approaches are no longer enough. From data leakage to supply chain vulnerabilities, and from regulatory pressure to investor scrutiny, AI introduces a new layer of complexity that leaders can no longer ignore.

Walter breaks down the emerging AI risk landscape, the importance of standards like ISO 42001, and why governance is becoming a competitive advantage, not just a compliance exercise.

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👤 About the Guest

Walter Haydock is the Founder of StackAware, a company helping organizations measure and manage cyber, privacy, and compliance risks in AI systems.

He previously served as a Marine Corps officer and worked on Capitol Hill advising members of the U.S. House of Representatives. His experience spans government, cybersecurity, and enterprise software, giving him a unique perspective on managing risk in fast-moving technology environments.

Walter focuses on helping companies accelerate AI adoption responsibly while maintaining trust, security, and regulatory alignment.

https://www.linkedin.com/in/walter-haydock/

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🔑 Key Takeaways

• AI risk is becoming a core cybersecurity challenge, not a separate discipline

• ISO 42001 introduces a structured way to manage AI governance and risk

• Many companies still treat compliance as a checkbox instead of an operational system

• AI supply chain risks are one of the biggest emerging threats

• Training AI on customer data without transparency can lead to backlash and liability

• Open-source AI tools introduce new attack vectors through plugins and dependencies

• AI governance is quickly becoming part of investor due diligence

• Companies that manage AI risk well will gain a competitive advantage

• Speed of decision-making matters more than perfect information in AI adoption

• Every company is becoming an AI company, whether they realize it or not

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🎯 What You’ll Learn

• What ISO 42001 is and why it matters for AI-driven companies

• How AI risk differs from traditional cybersecurity risk

• The biggest vulnerabilities in the AI supply chain

• How attackers are already using AI to accelerate cyber threats

• Why governance frameworks are essential for scaling AI safely

• How regulations in the US and EU are shaping AI adoption

• The role of AI governance in fundraising and M&A due diligence

• Practical first steps to assess and manage AI risk

• How to balance innovation speed with compliance requirements

• Why AI governance will become table stakes for every business

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⚡ Episode Highlights (Chapters)

00:00 Introduction and guest background

02:30 What is ISO 42001 and why it exists

05:00 Why AI governance is becoming critical

07:00 Who needs AI compliance the most

10:00 Regulation across the US, EU, and globally

13:00 Innovation vs regulation: finding the balance

18:00 AI supply chain risks explained

21:00 Open source AI and new attack vectors

25:00 Why AI risk management will be mandatory

27:30 AI in due diligence and fundraising

30:00 Future threats and AI-driven attacks

32:00 First steps for managing AI risk

34:00 Leadership mindset and decision making

37:00 Who owns AI risk inside organizations

39:00 Closing thoughts

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🔗 Resources Mentioned

• StackAware: https://stackaware.com/

• ISO 42001 (AI Management System Standard): https://www.iso.org/standard/42001