Fractional Chief AI Officer.

The Fractional Chief AI Officer is a productized monthly engagement where I run your AI practice inside your company part-time. You get the senior-level strategic role without paying for a full-time CAIO hire (which currently runs $300k+ all-in). The work follows a structured monthly operating system — same four-week rhythm every month — that produces a predictable cadence of executive alignment, deep workflow improvement, automation builds, and team training. Unlike a consulting engagement, this is built to compound: what we ship in month 3 builds on what we shipped in month 2.

Not ready for an ongoing engagement? Start with a 2-week AI Audit instead — if you sign within 60 days, the audit fee credits toward month 1.

A fractional Chief AI Officer is a senior AI leadership role that operates inside your company without the cost of a full-time exec hire. I run the operating system, manage the 90-day roadmap, ensure the cadence stays on track month over month, and transfer capability to your internal team so the result lives in your company — not in a relationship with mine. Think of it the way you’d think of a fractional CFO: someone who sets up the function, keeps it sharp, and stays accountable for the outcome.

Three differences.

Cadence vs. project. Consultants are paid by deliverable; I’m paid by the rhythm — every month produces alignment, work, and reporting on a fixed structure regardless of which deliverable is in flight.

Embedded vs. external. I work inside your company, with your team, on your tools — not as an outside vendor delivering against a SOW.

Capability transfer vs. dependency. Consultants can leave you more dependent on them over time. The fCAIO model explicitly transfers capability to your internal team — sponsor, operator, and AI champions — so the system survives the engagement ending.

Same four-week rhythm.

Week 1: Align. KPI review with leadership, roadmap adjustment, priority decisions for the month.

Week 2: Activate. Deep work with the department(s) we’re focused on this month — workflow identification and improvement.

Week 3: Build. High-impact builds, automations, or workflow rewrites go live.

Week 4: Train and Report. Team training session, monthly impact report delivered, next month pre-loaded.

The framework is fixed; what’s inside each week adapts based on what last month surfaced.

The first two weeks of every engagement are explicit discovery — AI readiness assessment, initiative identification, department prioritization. The output, delivered at end of week 2, is a 90-day roadmap: 6–12 AI initiatives identified and prioritized, department activation sequence defined, expected outcomes for each phase, resource requirements mapped, quick wins surfaced for early momentum, success metrics established. Months 1–3 execute against that roadmap. At quarter-end, the roadmap refreshes — same structured discovery, new 90 days. Scope expands as maturity grows.

Three roles.

One Executive Sponsor (C-level or VP) who owns the AI mandate, removes blockers, and ensures organizational commitment.

One Internal Operator — day-to-day point of contact who coordinates across departments, manages priorities between sessions, and drives execution between us.

Three to ten AI Champions — team members across departments who receive deep training and lead AI adoption within their teams. They become the internal expertise layer the system runs on.

If you can’t commit to those three roles, this engagement isn’t the right fit yet — and that’s a useful thing to know before signing.

Each month delivers a written impact report. The exact metrics tune to what your roadmap surfaces, but the spine is consistent: workflows automated this month, hours saved per role, departments active vs. inactive, AI-touch rate on key processes, what we shipped, what we deferred, what’s queued for next month.

The metrics aren’t vanity — they’re the conversation we have with leadership in the next Week 1 alignment. Strategy → measurement → strategy is the loop.

AI Leadership System works for organizations that need strategic direction first — exec cadence, roadmap, training framework, monthly reporting. No builds.

AI Enablement adds 1–2 workflow implementations per month and department-level rollout — for organizations ready to move from strategy into tangible deliverables.

AI Transformation adds multi-department activation and 3–5 initiatives per month — for organizations ready to move fast across the board.

Tier conversation usually happens in week 1 of discovery; you don’t have to pick before signing.

Discovery weeks 1–2 don’t produce visible results — they produce the roadmap. Weeks 3–4 of month 1 stand up the foundation and ship the first quick wins identified during discovery. Most clients see meaningful time savings inside month 1 and measurable workflow improvement by end of month 2. By month 3 the system is part of how the company works, and the question shifts from “is this working?” to “what do we tackle next?”.

Engagements have a structured quarterly review built in. If the system isn’t producing what we agreed it would by end of quarter 1, we have a real conversation: re-scope, change tier, or wrap cleanly.

The capability you’ve already received — installed tooling, trained champions, documented playbooks — stays with you. The framework is built to make a clean wrap-up cheap, because that’s what creates the trust to stay engaged in the first place.