# #358 Why 95% of AI Projects Fail and How to Succeed

Page: https://stenobird.com/podcast/embracing-digital-transformation-441152/358-why-95-of-ai-projects-fail-and-how-to-succeed
Text version: https://stenobird.com/podcast/embracing-digital-transformation-441152/358-why-95-of-ai-projects-fail-and-how-to-succeed.md
Podcast: [Embracing Digital Transformation](https://stenobird.com/podcast/embracing-digital-transformation-441152)
Published: 2026-06-11T10:57:44+00:00
Episode link: https://share.transistor.fm/s/6f18d94f
Audio file: https://2.gum.fm/op3.dev/e/pdcn.co/e/dts.podtrac.com/redirect.mp3/media.transistor.fm/6f18d94f/06a23a11.mp3
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Duration seconds: 1796

## Resource

Check out my new book AI Augmented Teams on Amazon or on my website paidar.ai/books. Host **Dr. Darren** sits down with **Michael Chavira**, co-founder and managing partner of **Axiologic**, to unpack the real reasons **AI projects fail**. From AI governance and workflow redesign to training, adoption, and ROI, this conversation shows why successful **AI implementation** is rarely a plug-and-play solution—and why people, process, policy, and technology all have to move together. ## Key Takeaways - **AI amplifies existing systems**: If your workflows are broken, AI will usually make the problems bigger, not better. - **Start with AI maturity assessment**: Before buying tools, determine where your organization is actually ready for AI adoption. - **Fix the process first**: Many AI failures come from outdated workflows, poor training, and disconnected tools. - **Governance matters**: Clear AI policies, data protection rules, and shadow AI controls are essential for organizations. - **Pilot before scaling**: Choose one use case, prove value, and measure ROI before rolling AI out across the business. - **Use AI to support people, not replace thinking**: The best results come from practical, specialized AI tools that fit real work. ## Chapters - **00:00** Intro and the 95% AI failure problem - **01:40** Michael Cervera’s origin story - **05:10** Why AI projects struggle to deliver ROI - **09:30** People, process, policy, and technology - **13:05** Workflow problems and the JIRA example - **17:20** AI governance, shadow AI, and data leakage - **22:15** Choosing the right AI pilot - **26:10** Building vs. buying AI tools - **30:00** Vibe coding, prototypes, and operationalizing AI - **34:00** Dissertation research and what’s next - **37:10** How to connect with Michael and Axi…

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