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AI governance is the difference between shipping healthcare AI and watching the project get shut down — Andre Samokish on privacy, AI strategy, and governance for 2026.

AI governance is becoming the difference between shipping AI in healthcare and watching the project get shut down. Andre Samokish, a privacy and AI governance expert, joins Chris Hutchins to explain why most AI initiatives will fail by 2026 and what responsible AI actually looks like inside organizations that refuse to take vendor assurances at face value.

What We Cover

• The concrete difference between privacy governance, AI governance, and cybersecurity, and why conflating them creates blind spots leaders will pay for later
• Why governance is not a project blocker. It is the pathway that lets teams move fast without inheriting regulatory debt
• The 3 pillars of AI literacy that separate organizations ready for responsible AI from ones that will inherit their vendor's mistakes
• How to embed privacy by design into AI product workflows before launch, not after incidents
• The failure modes hiding in data collection, model deployment, and organizational culture that teams routinely misdiagnose

Key Takeaways

• The "vendor has it covered" assumption is the single most dangerous governance gap in AI today. If you cannot explain how a model was trained, you cannot defend the decision it made.
• AI literacy is not training. It is infrastructure. Organizations treat it as optional, then discover their executives cannot distinguish generative AI risk from traditional IT risk when regulators ask.
• Data minimization is a governance principle before it is a privacy one. The less data you collect, the less exposure you carry through the model's full lifecycle.

Frameworks & Tools Mentioned

• OneTrust (privacy + AI governance platform)
• IAPP (International Association of Privacy Professionals) certifications
• Privacy by design methodology
• AI literacy pillars (technical, operational, governance)
• Vendor governance frameworks

## Timestamps 00:00 Introduction: The AI project failure wave of 2026 03:00 Andre Samokish on why AI governance is the root cause 09:30 AI strategy beyond proof of concept: what enterprises get wrong 16:00 AI implementation challenges that kill projects at scale 22:30 AI readiness: governance maturity vs. technical capability 29:00 Responsible AI development when privacy controls are inadequate 35:00 AI regulation signals and what they mean for 2026 planning 41:00 Leadership strategies for surviving the AI contraction

About Andre Samokish

Andre Samokish is a privacy and AI governance expert whose work spans regulated industries implementing responsible AI at scale. He advises organizations on embedding governance into product workflows, building AI literacy across technical and non-technical teams, and navigating the intersection of privacy law and machine learning practice.

Related Resources

• Episode: The Dark Side of the $5

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About The Signal Room: The Signal Room is a podcast and communications platform exploring leadership, ethics, and innovation in healthcare and artificial intelligence. Hosted by Christopher Hutchins, Founder and CEO of Hutchins Data Strategy Consultants. Leadership, ethics, and innovation, amplified.

Website: https://www.hutchinsdatastrategy.com

LinkedIn: https://www.linkedin.com/in/chutchins-healthcare/

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