Most companies aren’t failing at AI because of the technology.

They’re failing because of leadership, incentives, and execution.

And it’s costing them millions.

In this episode, a former CIO, Stanford AI PhD, and global AI transformation leader breaks down why most AI initiatives never deliver meaningful ROI — and what business leaders must do differently.

If you’re a CEO, board member, Chief Data Officer, or senior executive navigating AI investments, this conversation will challenge how you think about AI strategy, org design, hiring, and transformation.

This isn’t about hype.

It’s about execution.

You’ll learn what actually drives AI ROI, why endless pilots happen, how AI leadership must evolve, and the structural mistakes that keep companies stuck.

• The 3 reasons most AI initiatives fail
• Why hiring engineers won’t fix your AI problem
• The “AI Translator” role every organization is missing
• Why AI leaders must report directly to the CEO
• The execution gap blocking AI ROI worldwide
• How to structure your first 90 days as a Chief AI Officer
• Why endless AI pilots are often intentional
• The dangerous myth about humans in the age of AI

00:00 – Why AI ROI keeps failing
03:18 – From Wall Street CIO to AI transformation leader
07:01 – The 3 real reasons AI initiatives fail
10:37 – Where AI leadership must sit in the org chart
15:55 – Are we in an AI bubble?
17:51 – The execution gap nobody talks about
19:18 – Why some companies move fast — and others stall
23:31 – Real use cases: Where banks see ROI first
31:52 – The first 90 days as a Chief AI Officer
34:45 – Why AI leaders fail (even with great resumes)
38:02 – Rapid fire: CDO vs Chief AI Officer
39:27 – The most underrated truth about AI

Dr. Maxim Afanasyev is the Financial Services Industry Head for Asia-Pacific and Japan at Google Cloud, where he's leading AI strategy for one of the fastest-growing industries across some of the world's most dynamic markets.

But what makes Maxim's perspective truly unique is the journey that got him here. He holds a PhD from Stanford in Operations and AI, spent years as a derivatives trader at Royal Bank of Scotland, became Chief Investment Officer managing over a billion dollars in AI and tech investments, then pivoted to become one of McKinsey's first "Analytics Translators" - a role McKinsey predicted would need millions of professionals worldwide.

From there, he led the digital transformation of an $11 billion corporate banking business at Standard Chartered across 50+ markets, before joining Google Cloud where his work has contributed to FSI revenue growing at 2x the market average for three consecutive years.

He's behind some of the most impressive AI deployments in financial services - including HSBC's Anti-Money Laundering AI system that processes over a billion transactions per month and cut false positives by 60% while increasing true fraud detection by up to 4x.

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