One role,
six jobs
A Chief AI Officer’s job is to hold the three folds together: the business, the data and IT side, and the governance around both. As your fractional CAIO, I cover all of it. Here is what that means in practice.
AI strategy and roadmap
Where AI can actually move your numbers, and in what order. We align AI with business goals, define how AI work should be structured inside your organization, and build a roadmap your executives can defend to the board and your engineers can build against.
Enterprise AI architecture
The technical decisions that decide whether anything survives contact with your systems: data foundations, model selection (LLM, SLM, or classical ML), agent architecture, orchestration, and integration with what you already run.
AI governance
Security, data control, model lifecycle management, and compliance, designed in from day one rather than bolted on before an audit. Practical responsible AI frameworks that let you move fast without losing control.
Production AI systems
The move from proof-of-concept to systems that run: RAG on your enterprise knowledge where it is genuinely needed, automation and AI agents where they pay for themselves, plus cost control and token economics so the CFO stays on your side.
Vendor and platform strategy
Anthropic, OpenAI, AWS, Azure, Google, and IBM. Open models against closed ones. Build against buy. I have worked inside these ecosystems and have no reseller agreements, so the recommendation follows the problem, not a commission.
Capability building
Training and coaching for your executives and technical teams, so the organization needs less of me over time, not more. When execution needs extra hands, I bring in specialists I trust and stay accountable for the result.
How an engagement works
30 minutes. You describe where you are; I tell you honestly whether I can help.
A short, structured look at where you stand on each of the three folds: business alignment, data and IT, and governance. Usually one of them is the real blocker, and it isn’t always the one you expect.
Prioritized initiatives with owners, costs, and the business value each one is tied to.
A monthly cadence of strategy, architecture reviews, and hands-on work with your teams until the systems run.
A note on how long this lasts
Consulting folklore says the best advisor makes himself unnecessary and walks away. Reality inside organizations is messier. Strategy changes, models improve every few months, regulation moves, and new leaders arrive. The goal isn’t to stay indispensable. It’s to stay useful: you build internal capability, I keep helping you read what changed and turn it into the next practical step. Engagements scale down as your team scales up.