The AI Automation Gap: Why Enterprise AI Breaks After the Demo
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The AI Automation Gap: Why Enterprise AI Breaks After the Demo
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Why Enterprise AI Breaks After the Demo
AI rarely fails because the technology is weak.
It fails because it’s deployed inside workflows that were never designed for intelligence.
In this episode of The AI Storm, we explore The Automation Gap — the space where AI pilots succeed, demos impress, and real-world execution quietly breaks down.
You’ll learn:
Why automating broken workflows amplifies chaos instead of fixing it
How poor data quality, missing context, and fragile integrations cause AI to fail silently
The difference between human-in-the-loop and human-on-the-loop — and why leaders must design for both
Why most AI failures are operational and leadership problems, not model problems
The four workflow design questions every executive must answer before scaling AI
This episode isn’t about better models.
It’s about better workflow design.
If AI in your organisation “works… but only sometimes,” this episode will help you understand why — and what to redesign next.
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