Enterprise AI strategy, governance, and transformation program
A program that moved an enterprise from fragmented AI experimentation to governed, scalable adoption - prioritization, pilots, and a HIPAA/GDPR-aligned governance framework.
- Client
- An enterprise (anonymized)
- Techniques
The problem - An enterprise had plenty of AI activity but it was fragmented: scattered experiments, no shared way to decide what to pursue, no guardrails, and no path from pilot to scaled adoption.
What we built - An AI transformation program spanning prioritization to adoption. We prioritized opportunities on impact, data readiness, and feasibility, then ran pilots across AI-driven scheduling, real-time operations monitoring, and automated eligibility and pre-approval checks. Alongside them, a governance framework with executive, legal, and ethics oversight, defined success metrics, continuous model monitoring, and controls aligned with HIPAA and GDPR - plus change management and leadership education to drive adoption.
The outcome - Converted ad hoc AI interest into a governed, repeatable program - a prioritized pipeline, working pilots, and the oversight to scale responsibly.