The Hidden Reason Why Companies Waste Millions on AI

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Most companies are pouring millions into AI and have very little to show for it.

The problem isn't the technology. It isn't the budget. And it isn't the team.

Dr. Brindha Jeyaraman has seen it from every angle as a regulator, inside big tech, as Head of AI Governance at a major regional bank, and now as founder of an AI governance infrastructure company. The reason most AI transformations fail starts at the top.

In this episode, Brindha breaks down what most organizations are getting wrong about enterprise AI strategy and what the ones succeeding are doing differently.

We cover:

- Why AI projects fail to scale beyond the experiment stage

- The "braking system" case for embedding AI governance frameworks into your architecture from day one

- Why the bottom of your organization is moving faster than the top — and what that leadership gap is costing you

- The real reason hiring consultants to lead your AI implementation backfires

- How AI has cut cybersecurity exploitation speed from months to hours and what that means for enterprise risk management

- What the right AI team structure actually looks like today — and why most organizations have it upside down

- Why human in the loop is one of the most misunderstood concepts in LLM deployment

Whether you are a Chief AI Officer, Chief Data Officer, Head of AI, AI governance lead, or senior executive navigating AI transformation in banking, financial services, or regulated industries — this conversation gives you a practitioner's honest view of what actually works. If you are researching enterprise AI strategy, AI governance frameworks, LLM deployment best practices, agentic AI implementation, AI risk management, how to scale AI across your organization, or why so many AI projects fail to deliver ROI — this episode covers it all.

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⏱️ CHAPTERS

00:00 — Why AI Replacements Still Need Human Reviewers
01:32 — Brinda's Journey: Regulator, Big Tech, Bank, Founder
01:55 — How a Family Health Crisis Shaped Her View of AI's Purpose
03:12 — What Senior Executives Get Wrong About Deploying LLMs at Scale
05:29 — Operationalizing AI at the Speed of Change
06:37 — Why Organizations Get Distracted by New Tech Instead of Readiness
08:22 — Experimentation vs ROI — The Tension No One Talks About
09:52 — Why Companies Overestimate How Far Along Their AI Journey They Are
10:38 — The Role of Data Strategy, AI Strategy and Board-Level Buy-In
12:26 — Why the Top of the Organization Is Falling Behind
13:01 — What Separates Companies That Accelerate From Those That Stall
14:31 — The Middle Management Problem: Who Actually Gets the AI Mandate
15:50 — How to Push Leadership Into the AI Journey From the Start
16:45 — The Case for an AI Council
17:12 — Why Siloed Ownership Kills AI Transformation
18:05 — Building AI Foundations: Data, Knowledge and Tech Readiness
20:03 — "AI Governance Is Just Added Cost" — Brinda's Response
22:05 — Why Hiring Consultants to Lead Your AI Strategy Backfires
23:27 — Where the True Risk of AI Implementation Actually Lies
25:21 — The Human in the Loop Problem: Speed, Accountability and Design
26:18 — How to Design Human Oversight Into an AI Architecture
28:15 — How Organizational Culture Shapes Your AI Governance Framework
30:27 — What Worked Across Regulator, Big Tech, Bank and Startup
31:00 — Why Data Teams Are the Hardest to Bring Along
32:49 — What Actually Made Brinda Succeed Across Very Different Environments
34:18 — Why What Works in Big Tech Won't Work in a Bank
36:08 — The Hardest Leadership Conversations on AI Risk
38:28 — Posting AI Success Stories on LinkedIn Without the ROI
38:51 — Building the Right AI Team Structure Today
41:37 — Andrej Karpathy Stopped Writing Code — What That Means for Teams
42:09 — Why Coding Skills Still Matter in an LLM World
43:51 — How AI Team Structures Will Evolve Over the Next Two Years
45:49 — Are Companies Justified in Cutting Headcount Because of AI
47:02 — If You Could Redesign AI Governance From Scratch
48:46 — Claude Mythos, Cybersecurity and the New Threat Landscape
51:21 — Exploitation Speed: From Months to Hours
52:02 — Governance as the Answer to AI-Enabled Cyber Threats
53:45 — Rapid Fire Round Begins
54:07 — ChatGPT, Gemini or Claude?
55:27 — Head of Data Governance or Head of AI Governance?
55:34 — Centralized vs Decentralized AI Teams
55:41 — Most Overrated AI Trend Right Now
55:59 — Most Underrated AI Trend
56:23 — One Global AI Regulation You'd Implement Tomorrow

🎙️ The AI Visionary Podcast is hosted by Joel Azariah and Milind candid conversations with the leaders shaping AI.


#AIGovernance #EnterpriseAI #LLMOps #AIStrategy #AILeadership #AITransformation #AIRisk #ResponsibleAI #ChiefAIOfficer #AIImplementation #TheAIVisionaryPodcast

The AI Visionary Podcast is a platform where AI leaders share bold, unique and tangible insights about pathways to realizing meaningful ROI from AI, pitfalls to avoid and their success stories.

These conversations go beyond the hype to uncover what it takes for organizations to be successful in their AI transformation journeys from a leadership, talent, strategy and operating model perspective. 

Co-hosted by Joel Azariah and Milind, new episodes release every month via You Tube, Spotify, Apple Podcasts and various other Podcasts Channels

Links

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