Ep#249 How leaders need to rethink their approach to AI altogether

Everyone is asking "can AI do this?" But that's the wrong question. The right questions are: does it have the right knowledge, the right tools, and clear enough instructions to do the job? And is your enterprise actually ready for what comes after?In this episode, Jon Myer is joined by Christopher and Diego from Epi-use — two experts in AI architecture, governance, and enterprise implementation — for a frank conversation about why so many agentic AI projects fail, what the successful ones have in common, and why the real bottleneck is almost never the AI itself.Topics covered:Why most companies are implementing AI for the wrong reasons and asking the wrong questionsThe difference between generative AI and agentic AI — vending machine vs. sous chefPilot purgatory — why AI projects get stuck and never make it to productionWhy the AI part is usually the easiest part and the foundation is the heavy liftHow governance becomes the enabler not the obstacle when done rightThe difference between human in the loop and human on the loop — and why it matters for designA real-world case study — a bank that ran 350 agentic AI use cases and what actually workedDo we want true autonomy or accountability? The answer is both⏱️ Timeline0:00 — Introduction — Reframing agentic AI as an evolution that demands first principles thinking0:50 — What companies are getting wrong at the very start — the fascination phase2:13 — Is agentic AI truly novel or just a rebrand of what we already had3:03 — The right questions to ask — knowledge context tooling and instruction4:51 — Pilot purgatory — AI projects stuck in QA that never make it to production5:46 — First principles have not changed — what problem are we solving and what outcome do we want8:50 — Are we implementing true agentic AI or just rebranding existing workflows9:59 — Generative AI as a vending machine vs agentic AI as a sous chef11:51 — Model in the loop — when you are really just calling a more sophisticated API13:33 — Where agentic AI adds the most value — exception handling in enterprise workflows16:40 — Governance as an enabler — why dirty data is a governance failure not an AI failure18:19 — What feels familiar and what feels genuinely new about AI adoption today20:29 — The importance of foundation before implementation — and the rush that bypasses it23:29 — 40% of AI projects will fail by 2027 — and the bank that ran 350 use cases25:18 — What actually determines AI success vs quiet failure26:28 — Human in the loop vs human on the loop — why design matters from day one29:41 — Agentic AI is a business project not a technology project31:05 — Do we want true autonomy or accountability? The answer is both🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization