A fractional chief AI officer, 2 to 5 days a month

A fractional chief AI officer does the job of a head of AI for a set number of days each month: deciding which AI work the company funds, making sure it gets built properly and reporting on whether it pays back.

A month on our 3-day arrangement usually looks like this:

• A 90-minute leadership session to review the roadmap, decide on new requests and unblock live projects.
• Half a day of vendor work: reading proposals and renewals, testing claims on your data, pushing back on usage terms.
• About a day of build oversight: architecture reviews, checking evaluation results before anything goes live and pairing with your internal builders.
• Half a day on governance: updating the usage policy, reviewing new tool requests and checking that data rules hold.
• The monthly report, written for the board or leadership team.

Between sessions your lead answers on Slack or Microsoft Teams within 1 working day.

The difference from a consultant is continuity. A consulting phase produces a roadmap and ends. A fractional lead owns that roadmap month after month, changes it when models, prices or your priorities move, and is accountable when a project slips. If you need the roadmap first, start with corporate AI consulting and move into the fractional role afterward.

Choose by how many AI decisions you face each month. A one-off question suits a consultant. A handful of decisions and 1 or 2 builds a quarter suit a fractional lead. Daily decisions and a team to manage suit a full-time hire.

A full-time hire becomes the right call when AI work fills a calendar: several builds running at once, an internal team of 3 or more engineers to manage, or AI inside the product you sell. Until then, a full-time leader would spend much of the week on work a fractional lead covers in 3 days a month.

The options also work in sequence: a consulting phase to set direction, a fractional lead to run it for a year, then a full-time hire who inherits a working roadmap. Our guide to fractional chief AI officers covers the hiring decision in more depth.

Our fractional chief AI officer costs $4,000 to $15,000 a month, in 2 tiers:

• 2 to 3 days a month, $4,000 to $7,500. Monthly leadership session, roadmap ownership, vendor reviews and the monthly report. Fits companies starting 1 or 2 AI projects a quarter.
• About 1 day a week, $8,000 to $15,000. Everything above plus hands-on build oversight, work with internal builders, board attendance and policy rollout. Fits companies running several AI projects or building AI into a product.

Within a tier, price depends on the number of business units, whether board meetings are included, how many vendors need managing and whether your industry adds review work, as healthcare and financial services usually do.

The first engagement runs for 3 months, because the inventory and first funding decisions take that long to pay off. After that it is month to month with 30 days' notice.

Production builds are priced separately as fixed-price projects. If we bid on a build, we say so in writing and your leadership team makes the call; your fractional lead does not score our proposal.

For reference, the Christian & Timbers guide to hiring a fractional chief AI officer (September 2026) (opens in a new tab) puts fractional AI leaders at about $3,000 to over $30,000 a month, usually for 1 to 3 days a week. Model and tool usage on any project is billed at cost with no markup.

Yes. Vendor management is part of every month in the role, and it covers 4 jobs.

• Every AI proposal gets a short memo: what it does, what it would cost at your real volume, how it handles your data and whether a feature in a tool you already pay for would do the same job.
• Where a vendor claims accuracy or time saved, we test the claim on your own data before you sign. A set of 50 to 100 real examples is usually enough to tell a good product from a good demo. Our glossary entry on LLM evaluation explains how those tests work.
• We read the contract sections on training, retention and subprocessors, and flag any that let a vendor train models on your data.
• Before each renewal we check usage. API bills grow with volume, and seat licenses get renewed for people who never log in.

We do not sign contracts on your behalf, and the final decision stays with your leadership team.

Once systems are live, the daily checks on quality, cost and failures can move to AI ops monitoring. That keeps your lead's days for decisions, and the monitoring reports feed straight into the monthly AI report.

A fractional lead is the wrong hire if you have fewer than about 30 staff, no AI budget for the next 12 months, or a need for someone to write code every day.

Small companies get more from a half-day workshop and 1 well-chosen build than from a monthly retainer, because there is not enough AI spend to manage. Companies with no budget to build get a roadmap that nobody acts on, plus a monthly fee for meetings about it. And if the gap is engineering capacity, you need a builder: a developer, an automation partner or a fixed-price project.

It is also a poor fit when an existing executive already owns AI and has the time. A CTO or COO who is leading AI work well may only need a quarterly review of the roadmap, which costs less than a retainer. We will say so on the scoping call.

What the role does not include: production builds (priced separately), cybersecurity audits, legal advice on AI regulation, recruiting fees or line management of your staff. Your lead advises, oversees and reports. Your managers still manage their teams.