Fractional Chief AI Officer.
The executive AI function, without the executive hire. We measure where AI pays off in your business, set the roadmap, then build and operate the systems — one accountable engagement, reporting ROI in hours and dollars.
Who it's for: SMB owners who keep being told to "get an AI strategy" and would rather have one person accountable for AI actually working.
The paid AI Readiness Assessment: ten business days of consent-based measurement, ending in a workflow-by-workflow ROI map and an honest go/no-go. That report is the strategy — evidence first, then a roadmap.
Learn moreWhat you get.
- An AI roadmap built from measurement of your actual workflows — not an interview and a slide deck
- One named lead accountable end-to-end: strategy, build, operation, and the ROI report
- Vendor-neutral tool decisions — we hold no reseller quotas and say no to tools that do not earn their keep
- The systems land in production and someone runs them — strategy that ships, not a binder
- Everything built is yours: infrastructure you own, ownership and export rights in the contract
What's included.
- →The paid AI Readiness Assessment — the measured baseline every decision argues from
- →AI roadmap and build order, ranked by ROI per workflow
- →Vendor and tool selection, including retiring overlapping subscriptions
- →Build: agents, integrations, and custom apps on infrastructure you own
- →Operation under the MAISP retainer — monitoring, maintenance, and a monthly written review
- →Board-level reporting: hours and dollars per workflow, in writing
How we do it.
- 01
Measure
The Assessment maps how work actually happens on your team’s machines and models ROI per workflow. The roadmap is scoped from that evidence.
- 02
Decide + build
We set the build order, pick the tools that earn their keep, and ship the systems — AEGIOS underneath for orchestration and memory.
- 03
Operate + report
The systems run under SLAs with a named lead, and you get the ROI ledger monthly. If a bet is not paying, the report says so and the roadmap changes.
Examples.
The stalled-pilot rescue
Three overlapping AI subscriptions, none owned by anyone. The Assessment maps what is salvageable; the roadmap retires the rest.
The quoting bottleneck
Proposals rebuilt by hand from old quotes. A generator trained on your past work drafts them; a person approves.
The reporting week
The days each month someone spends assembling numbers become an automated report — reviewed, not compiled.
An operator, not an advisor.
Twenty-plus years running IT and security for SMBs under SLAs is the discipline behind the title. Most fractional AI executives advise and leave the doing to you. This one comes with the engineering team and the ops bench attached.
The promises we put in writing.
If we don't find ROI, you get the fee back.
Edgerton measures how your team's work really happens — with your team's knowledge and consent — and puts a dollar figure on what it finds. If there's no clear ROI path, the verdict is 'don't build' — and the Assessment fee comes back. The report is yours to keep either way.
Production by a fixed date.
Set during the Build. If we miss it, additional weeks of build are on us.
You keep the system — whatever happens.
Data, memory, integrations — yours in the contract, on infrastructure you own, with full export rights. Leaving is a handover, not a hostage negotiation.
Your rules decide what the AI sees.
Only what you approve goes in. Nothing you don't approve comes out. And every access is written down — so "what did it see?" always has an answer.
A named engagement lead.
Not a queue, not a rotation. You know their name, they know your business — and they pick up the phone.
Questions we get.
What is a fractional chief AI officer?
A part-time executive function accountable for AI in your business: where it pays, what to build, what to buy, what to skip. Ours differs from the usual model in one way — the strategy comes with the team that builds and operates it, so the roadmap is never someone else’s problem to execute.
What does a chief AI officer actually do?
Sets AI direction from evidence, owns the tool and vendor decisions, sequences the builds by ROI, and answers for whether it worked. In an SMB, that is a fraction of a role — which is why buying it fractionally beats a full-time hire you cannot keep busy.
Does my company need a fractional chief AI officer?
Honest answer: run the math first. If AI decisions are being made ad hoc — tools bought on trial cards, pilots stalling, nobody reporting ROI — then yes, someone needs to own it. The Assessment is the cheap way to find out; it ends in a go/no-go either way.
How is this different from hiring an AI consultant?
A consultant hands you a strategy deck and leaves execution to you. This engagement is accountable for the outcome: the same team that writes the roadmap builds the systems, operates them under SLAs, and reports the ROI in hours and dollars.
How is this different from buying AI tools ourselves?
Tools without an owner become shelfware — overlapping subscriptions, half-finished pilots. What you are buying here is the accountable function: someone measures where AI pays, chooses the tools, builds the system, runs it, and shows you the ledger. The tools are an implementation detail.
Will AI replace our team?
It replaces repetitive work, not judgment. The Assessment shows which hours are leaking into work nobody should be doing, and the builds give those hours back. Where a whole role genuinely can be automated, the report says so out loud — that becomes a decision you make with evidence, not one that happens to you.
What does a fractional chief AI officer cost?
We publish the structure, not a rate card: a fixed-fee Assessment quoted on the first call and refunded if no ROI path is found, fixed-price builds scoped from the evidence, and an Operate retainer scoped to what we run. The pricing page explains each stage.
Related guides.
Go deeper in the Learn library.
Start with an Assessment.
Ten business days of measurement. Whatever the verdict, the deliverable is yours.