Episode #48 - The Continuous Improvement Loop — Feedback to Refinement

Episode #48 - The Continuous Improvement Loop — Feedback to Refinement

Episode 48: Why Your AI Gets Dumber Over Time — And Exactly How to Stop It

What if the biggest threat to your AI investment isn't a bad vendor, a failed deployment, or a data breach — but simply walking away after launch? In this episode of The AI Strategy Blueprint, host Lara Wilson unpacks one of the most overlooked realities in enterprise AI: the systems you build will degrade, drift, and disappoint if you treat them like traditional software you install and forget.

Drawing directly from John Hanby's The AI Strategy Blueprint, Lara breaks down the four-phase continuous improvement loop — Feedback Collection, Prioritization, Implementation, and Validation — and explains why implicit signals like session abandonment and query reformulation reveal far more friction than any thumbs-up button ever will. Could your AI system be silently failing users right now, in ways no one is reporting?

The numbers from real A/B testing are staggering: one organization achieved a 13x increase in engagement by testing personalized AI video content, and another hit an 81.6% click-through rate on cold email campaigns — against an industry average of just 5%. Lara walks through exactly how to design statistically significant tests, avoid skewed results, and know when you've actually found a winner versus gotten lucky.

But here's the trap that takes down even the most rigorous teams: the pilot data illusion. When your proof of concept runs on sanitized Word documents and your production environment is flooded with 500-page scanned contracts faxed three times in 1998, the gap is catastrophic. Lara covers how to demand representative data, design for worst-case outliers, and ensure your pilot investment carries forward seamlessly — with zero starting over — into full enterprise deployment.

From content expiration timers that force regular SME review cycles, to gap-driven content expansion that pulls in new knowledge only when real users actually need it, this episode gives you the organizational playbook for building AI systems that get smarter — not staler — over time. If you're serious about making AI a compounding competitive advantage, this is the framework you need. Learn more at https://iternal.ai/ai-strategy-blueprint

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Episoder(51)

Episode #51 - Your Seven Commitments — Leading the Greatest Technology Transformation

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Episode #49 - The Transformation We've Mapped — Your Complete AI Strategy Recap

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Episode #45 - Why AI Hallucinations Are a Data Problem, Not a Model Problem

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Episode #44 - Air-Gapped AI, Data Sovereignty, and Compliance Frameworks

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