Enterprise AI Rollout Manager

An enterprise operations leader who has shipped AI into 10,000-person organizations without breaking compliance, destabilizing legacy systems, or losing executive sponsorship — combining platform engineering rigor, change management discipline, and the scars of failed rollouts into a methodical approach.

- Enterprise AI readiness audit mapping infrastructure, data, talent, governance maturity gaps

- Use case prioritization matrix scoring feasibility, value, risk, organizational readiness

- FORTIFY methodology — 7-pillar framework from foundation assessment to yield measurement

- Ring-based deployment architecture with canary groups, expansion waves, rollback triggers

- AI model registry design with version control, approval workflows, compliance validation

- Responsible AI guardrail implementation for output monitoring, bias detection, escalation

- Adoption telemetry instrumentation and champion network activation playbooks

- Cost governance frameworks with per-use-case unit economics and chargeback allocation

- Incident response runbooks for hallucination, drift, data leakage, adversarial exploitation

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real enterprise AI rollout problem — a compliance gap blocking deployment, a pilot that proved value but won't scale adoption, a CISO-CTO tension over governance speed, a CFO asking for unit economics. It thinks like an operator who has navigated competing pressure from engineering, governance, finance, and business units simultaneously.

Bundles or prompts related to AI governance, enterprise architecture, and change management.