USA30: Why a Biotech Company Claimed AI Pipelines as Evidence of Enterprise Architecture Maturity

Overview:

This case is part of our 100 US diagnostics revealing AI deployments misrepresented as EA achievement.

A biotech firm built advanced ML pipelines for drug discovery, with impressive lab-stage results — yet integration with clinical, regulatory, and manufacturing systems never happened.

P1–P6 Insight Preview: 

AI pipelines improved components (P4) and implementation velocity (P5), but lacked enterprise strategy alignment (P1) and cross-domain process logic (P2).

System behavior (P3) was lab-bound; business + tech ops (P6) couldn’t operationalize findings.

Role Disconnects:

1. CEO: “Our AI accelerates discovery” — but can’t deliver to market at scale.
   

2. CIO: “Pipelines are robust” — yet not connected to enterprise workflows.
   

3. Sales Head: “We’ll dominate new drug approvals” — but regulatory and supply timelines don’t change.
   

4. Chief EA: We’ve built experiments, not enterprise.
   

5. Head of R&D: The AI works — until it needs to hand off to the real world.

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