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The Month-13 Problem: Why Your AI Project Died After Go-Live

Hosted by Hussam Ahmad

Mon, Sep 28, 2026

5:30 PM UTC (30 minutes)

Virtual (Zoom)

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How to Diagnose and Overcome the Five Critical Dysfunctions of AI Transformation
Hussam Ahmad
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What you'll learn

Spot the Project Mindset Before It Kills Value

Recognize the warning signs that an AI initiative is scoped as a project with an end date — and what each one costs you.

Ask the Four Ownership Questions

The questions that expose who owns the model in month 13: retraining triggers, data SLAs, and the vendor-exit scenario.

Run a Model Health Review

Turn model maintenance from a post-mortem into a recurring operational meeting, with a simple standing agenda.

Why this topic matters

Most AI initiatives don't die in the strategy room — they die in production, months after go-live, when the team has moved on and nobody owns retraining. Gartner finds models fail for lack of operational structures, not bad algorithms. It is Dysfunction 4 — the Project-Not-Product Mindset — the most common death zone. Run AI as a project with an end date and failure is scheduled. This lesson shows you how to cancel it.

You'll learn from

Hussam Ahmad

AI Transformation, Leadership & Product Excellence and OKR Coach

AI transformation advisor and OKR coach, working with leadership teams on organizational readiness for AI. Developer of the Five Dysfunctions of AI Transformation framework and the AI

Transformation Health Check diagnostic. Diglab is currently running the first pilot sessions with select leadership teams — participants in this early phase shape the framework directly and receive preferred pilot terms.

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