AI governance at large-group scale

173AI use cases managed
+15 ptsdelivery acceleration
23→78%portfolio quality in 1 month
10+use cases modelled ROI/FTE

01 · SITUATION

The context 

Took over the full AI governance scope for a Corporate division (3 business perimeters, 173 AI use cases). Informal governance on arrival: vague definition of 'delivered', AI use-case portfolio at 23% quality, unusable as a decision-making tool, absent value measurement, structure in full reorganization.

02 · METHOD

Operational governance 

Portfolio takeover

Took over the full AI governance scope across 3 business perimeters, tracking 173 use cases, steering operational instances and escalating weak signals.

Governance model redesign

Redesigned the governance model and the AI project managers community framework, resulting in a 15-point delivery acceleration.

Project value measurement

Led ROI and FTE impact modeling across 10+ priority use cases.

Portfolio automation

Drove documentation and Jira Automation of the AI portfolio: quality improved from 23% to 78% in one month, turning an unreliable tracking tool into an actual decision-making asset.

03 · RESULTS

Governed portfolio 

173 AI use cases managed across 3 business perimeters
+15-point delivery acceleration
AI portfolio quality: 23% → 78% in one month
ROI and FTE modelling across 10+ priority use cases
Tracking tool turned into an actual decision-making asset

Next case

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AI governance at large-group scale — Diane Maurin