Fractional Chief AI Officer
Fractional CAIO · $5M–$50M companies
A fractional Chief AI Officer for the company with a roadmap and no one to run it.
Your CFO owns the numbers and your ops lead owns the floor. AI usually belongs to whoever has a spare hour, so it lives in personal ChatGPT accounts and a Copilot license that renews whether anyone uses it or not. I take that seat: the roadmap, the vendor calls, the builds, the policy, and a monthly report to your leadership team. Part time, one fixed monthly fee, for companies at $5M to $50M.
26%
of organizations now have a Chief AI Officer. The ones that do report about 10% higher ROI on AI.
IBM Institute for Business Value, Jul 2025
94%
of mid-market companies use generative AI. 2% run it at scale.
Kaufman Rossin / NewtonX, Dec 2025, n=100, $5M+ revenue
95%
of enterprise AI pilots show no measurable P&L return.
MIT NANDA, Aug 2025, 300 deployments
Big companies hire for the seat. At $5M–$50M the job usually lands on the CFO or the IT lead as a side project, and that's how a company ends up in the 98%.
What the seat is
What a fractional Chief AI Officer does.
A Chief AI Officer owns 4 decisions: which AI work gets funded, which tools get bought, what the rules are, and whether any of it paid back. Here's how the 3 ways to fill that seat compare.
AI consultant
Hired for a project. Leaves when it ships.
Good for one build with a clear spec. The trouble starts in month 4, when the vendor raises the price, the model changes, or the person who ran it quits.
Full-time CAIO
A seat on the org chart, and a salary to match.
Right when AI work fills 40 hours a week across several teams. Most $5M–$50M companies aren't there yet, and a hire made early spends year 1 looking for a mandate.
Fractional CAIO
The same seat, sized to your company.
Owns the roadmap, vendor decisions, governance, and builds for one fixed monthly fee. Scales up when the work does, steps back when it doesn't.
The fractional seat is the one still answering for the result in month 6.
Every month
What the retainer covers.
Every month ships 3 things: a build, a governance review, and a leadership session. The rest is the work a Chief AI Officer picks up in between.
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One build in production. A workflow from your Blueprint roadmap goes live with an owner, an SOP, and a Loom. Your team runs it. I watch the numbers.
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One governance review. Usage policy, data boundaries, vendor terms, and the log of what each system did. Fixed before it turns into an audit finding.
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One leadership session. What shipped, the hours it returned, what's next, and what got cut. Numbers first.
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Vendor and tool decisions. I sit in on the sales calls and read the contract before you sign. You find out which demo is a product.
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Team training. Short sessions on the tools your people use, tied to the workflows we built. New hires get the same sessions.
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Board and owner reporting. Hours returned, dollars spent, risks open. One page your board, lender, or PE partner can read in 5 minutes.
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The people side. When a build changes someone's job, I'm in that conversation with the SOP and the training ready.
The rule I run every month
Eliminate before you build.
A retainer that ships something every month can turn into a build factory. One rule keeps it honest.
If a task returns under 20% of someone's time, I recommend deleting it. Over 20%, it goes on the roadmap and gets scoped. The delete list costs nothing to act on, which is why it comes first.
That's also why the monthly review stays short: every line on it is a build with a number attached, or a task that's gone.
How it starts
The first 90 days.
The retainer starts after the Blueprint, so discovery is already done and month 1 goes straight to work. Here's the sequence.
Want a number before the call? The calculator prices one workflow in 4 questions, no signup.
01
Week 1: take the seat
Access, introductions, and the Blueprint roadmap turned into a 90-day plan your leadership team signs off on.
02
Month 1: rules first
AI usage policy written and approved. An inventory of the AI tools your people already use. Data boundaries set for every system on the roadmap.
03
Months 1 to 2: first build live
The top workflow from the Blueprint goes to production with a named owner, an SOP, a Loom, and error handling written before launch.
04
Months 2 to 3: vendor decisions
Tools picked against the spec the Blueprint wrote. Contracts read before signing. Subscriptions you don't need, cancelled.
05
Day 90: the review
Hours returned against the Blueprint projection, money spent, what's next. You continue, change the scope, or stop.
Who sits in the seat
Lee Pomerantz, Certified Chief AI Officer.
You get me every month, in the meetings and in the builds. Here's what's behind the seat.
Credential
Certified Chief AI Officer
Certified in AI program leadership, governance, and risk. Rebuilt the company as eMediaAI in 2022 to do this work for companies your size.
Operator
24 years running an agency
I've made payroll, chased receivables, and sat on the owner's side of a lot of vendor pitches. The advice comes from that chair.
Builder
Builds what I recommend
HubSpot, GoHighLevel, Make, Copilot Studio and Power Automate, NotebookLM, Cloudflare Workers, Claude Code, Codex, Firecrawl, Langfuse, Promptfoo, and custom agent harnesses. If it goes on your roadmap, I've shipped with it.
Based in Fort Wayne, Indiana. Remote nationwide, and on site when you're within a day's drive.
Governance
The controls your board and your insurer will ask about.
Every AI system I'm responsible for ships with these 5 controls, and the monthly review checks that they still hold.
AI usage policy
Which tools staff can use, with what data, and who approves a new one. One page, signed by leadership.
Data boundary
Which systems each tool can read, which it can write to, and what never leaves your network.
Audit trail
Every action a system takes, logged with the inputs it used and the person who approved it.
Vendor review
Security, data retention, and exit terms checked before anything is bought, and again at renewal.
A named owner
Someone on your team owns each system, with an SOP and a Loom. Done when they run it 30 days without me.
Your people
Your team will hear “Chief AI Officer” and think “cuts are coming.”
I decline engagements whose goal is eliminating jobs. It's in writing on the engagement letter.
Every build is scored on the hours it gives back to the person doing the work, and every one names who owns it afterward. If the first build is quoting, your estimator still owns quoting. She just stops retyping part numbers.
Most teams relax once the first build ships. When a team doesn't, that tells me something about the workflow, and it goes in the monthly review.
How you get there
One door in. The retainer comes after the Blueprint.
1. AI Opportunity Blueprint™
10 days, $5,000 flat. I map your workflows, apply the 20% rule, price each candidate in hours a year, and hand you a sequenced roadmap. That roadmap becomes the retainer's first 90 days.
2. The retainer
One fixed monthly fee for a defined scope, quoted after the Blueprint. 3-month minimum, then month to month.
3. Bigger builds
Anything larger than the monthly build is scoped from the Blueprint and quoted as one project fee. Your team, your vendor, or us.
If the Blueprint doesn’t identify at least 200 hours a year of removable work, each with a named mechanism and an implementation estimate, you don’t pay. You keep the document either way.
Questions owners ask before the call.
How is the retainer priced?
One fixed monthly fee for a defined scope, quoted after the Blueprint. 3-month minimum, then month to month. You get one number in writing before you commit, and no menu of tiers.
Why do I need the Blueprint first?
A retainer without a roadmap spends its first 2 months on discovery at retainer rates. The Blueprint is 10 days and $5,000 fixed, and it hands the retainer its first 90 days of work.
What's the difference between a fractional CAIO and a full-time hire?
Same seat, different size. A full-time Chief AI Officer makes sense when AI work fills 40 hours a week across several teams. Below that, the fractional seat covers the roadmap, vendors, governance, and builds for a fixed monthly fee.
How is a fractional CAIO different from an AI consultant?
A consultant is hired for a project and leaves when it ships. The fractional CAIO owns what happens next: the vendor renewal, the model change, the new hire who needs training, the board asking what it returned.
Will you sit in on vendor calls?
Yes, and I read the contract before you sign it. I don't resell platforms, so the only side I'm on is yours.
We're a division or plant of a larger company. Does this work for us?
Usually not, and I'll tell you on the fit review. If a corporate parent decides which tools you can buy, the roadmap is one you can't act on. The exception is a plant with its own P&L and purchasing authority for pilots under a set amount. Bring that number to the call.
Do you work with companies outside Indiana?
Yes. Most of the work is remote: your leadership meeting, your vendor calls, your builds. I'm on site in Fort Wayne and anywhere within a day's drive.
Put someone in the AI seat before the next tool gets bought.
Bring the one process that hurts. Within 24 hours of the call you'll get a one-page note naming the 2 or 3 workflows where AI would pay off first, whether or not you book anything.
