What is a Fractional AI Officer (FAO)? The executive who decides where AI belongs in your business.
A Fractional AI Officer gives a small or mid-sized business executive-level AI leadership without a full-time hire. The role owns the strategy, sets the guardrails, gets the first working automations live, and gets your team using them. One to three days a month. Measured in hours returned, leads converted and costs removed, not in slide decks about AI.
A ranked roadmap tied to your business goals, not to whatever tool was demoed last week.
Acceptable-use policy, data handling, vendor review, and a human owner on every automation.
Role-based training, playbooks and office hours, scored monthly on who's using what.
What is a Fractional AI Officer (FAO)? Plainly.
A Fractional AI Officer is a part-time executive who owns your company's AI strategy the way a fractional CFO owns your finances: with authority, accountability and a monthly scorecard, without the full-time salary.
The fractional model is familiar. Companies have used fractional CFOs, CMOs and CTOs for years when they needed the judgment of a seasoned executive but not forty hours a week of it. The AI version exists for the same reason, with one difference: the field changes monthly, so a fractional officer who sees patterns across several clients is often better informed than a single-company hire could be.
For a 5–50 person company, the job is less about the technology and more about the decisions: which workflows get automated first, what the rules are, which subscriptions get cut, who owns each system, and whether the whole thing is paying off. That's executive work. It just doesn't need an executive salary.
What a full-time Chief AI Officer costs, if you can find one. Most companies under $50M in revenue need the judgment, not the headcount.
How often the AI tooling landscape changes. Cross-client pattern recognition is the only way to keep up.
Heavy in the first 90 days, then a steady cadence of oversight and new use cases. The shape of the work fits the fractional model.
One decides what to build. The other builds it.
Most companies that are stuck on AI don't have a strategy problem or an engineering problem. They have both, in sequence. Here is how the roles divide the work, and where the usual alternatives fall short.
| Fractional AI Officer | Forward Deployed Engineer | AI consultant / strategy deck | |
|---|---|---|---|
| Primary question | What should we do with AI, and how do we govern it? | How do we make this specific workflow work with AI, in production? | What could AI do for a company like yours? |
| Works with | CEO and leadership team | Operators, sales, ops, support and admin staff | Whoever signed the engagement |
| Output | Strategy, roadmap, policy, oversight, first live automations | Deployed automations, agents, integrations, SOPs | A deck and a list of recommendations |
| Time pattern | 1–3 days per month, retained | 2–5 days per week during a build sprint | Six weeks, then gone |
| Accountable for | The monthly scorecard: adoption, hours saved, revenue and cost impact | Each system adopted, measured and handed off | Delivering the deck |
| Best paired | Sets the backlog the FDE builds from | Executes the backlog and feeds learnings back | Hands you the deck and wishes you luck |
The two roles are built to pair. The AI Officer sets priorities and guardrails; the FDE executes the backlog and feeds what it learns back into the roadmap. Most clients start with the AI Officer and add the engineer when the backlog is bigger than one to three days a month can build. Read about the Forward Deployed Engineer role.
Eight responsibilities. One scorecard.
This is the job. If a proposal is all strategy and no live automations, or all automations and no governance, it's half a role.
AI strategy and roadmap
Audit current workflows, data and tools. Rank AI opportunities by impact and effort. Publish a 12-month roadmap tied to business goals.
Use-case delivery
Scope, build or oversee the priority automations: sales follow-up, lead routing, content, reporting, customer service, back office.
Governance and risk
Write the acceptable-use policy, data-handling rules, vendor review standard and human-in-the-loop requirements. Manage privacy, IP and compliance exposure.
Tool and vendor selection
Evaluate platforms, negotiate and consolidate subscriptions, and stop shadow-AI sprawl before it becomes a data problem.
Team enablement
Train leadership and staff by role. Build prompt libraries, SOPs and playbooks. Coach the internal champions who carry it forward.
Measurement
Define KPIs per use case. Report monthly on adoption, time saved and revenue impact. Kill what isn't working.
AI visibility (AEO)
When a customer asks ChatGPT or Google AI who to call, make sure the answer is you. Baseline how AI assistants describe the company, then close the gaps.
Executive advisory
Brief leadership each month on what changed in AI and what to do about it. Sit in on strategic planning.
- Not a full-time IT or data-science function; infrastructure and heavy engineering are scoped separately
- Not a software vendor; every recommendation is tool-agnostic and referral relationships are disclosed
- Not a replacement for your team's judgment; every automation ships with a named human owner
- Three people are paying for four different AI subscriptions and nobody knows what data is going where
- You've had the "we should be doing something with AI" conversation at every leadership meeting this year
- A competitor is showing up as the recommendation when buyers ask an AI assistant, and you aren't
- You tried a tool, it didn't stick, and nobody can say why
- Your team is quietly worried about what AI means for their jobs, and nobody has told them
AI won't transform your company. Your people will.
Every automation we design starts with a goal, and every goal is set at the level where the work happens: the organization, then departments, teams, and individuals.
The people in those roles have a say in how the process should work. Where the slop is. What they hate doing. What would work better. What they'd rather spend the hours on. When they know what to expect and why, they build with you instead of bracing for it.
To be unclear is to be unkind. A Fractional AI Officer's job includes making the plan clear enough that nobody on your team has to guess what AI means for them.
A 60-minute briefing, then a monthly brief: what changed, what it means here, what decisions are needed.
Two role-based training sessions, a prompt library and playbooks written for the job they actually do.
One internal champion coached to own the tools, run office hours and carry the work when the officer isn't in the room.
Ninety days of foundation. Then a monthly cadence.
The engagement runs in two phases: a 90-day Foundation Sprint that produces the audit, roadmap, governance and first live automations, then a month-to-month Advisory Retainer that keeps delivering use cases and oversight. The Day 90 readout is where you decide whether to continue.
- Stakeholder interviews
- Workflow, data and tool inventory
- AI readiness scorecard
- Ranked use-case backlog
- 12-month roadmap
- AI acceptable-use policy
- 2–3 live automations
- Role-based training
- AI visibility baseline
- Monthly executive brief
- One new use case per month
- AI scorecard
One gate: the Day 90 leadership readout, scored against the baselines captured in the first 30 days. You decide go or no-go on the retainer with the results in hand.
| When | Activity | Who's in the room |
|---|---|---|
| Week 1 | Executive AI brief: what changed, what it means, decisions needed (60 min) | CEO + leadership |
| Week 2 | Build or oversee this month's use case; review automations in production (4–8 hrs) | Internal champion |
| Week 3 | Team office hours and training touchpoint (60 min) | Open to all staff |
| Week 4 | AI scorecard delivered; backlog re-ranked (45 min) | Sponsor + champion |
| Ongoing | Slack or email questions, vendor evaluations, policy updates; one-business-day response | As needed |
- An executive sponsor and one internal champion, 2–4 hours a week during the sprint
- Access to systems, data and the people who run the workflows under review
- Decisions on the roadmap within 5 business days of presentation
The Foundation Sprint is a fixed fee. The Advisory Retainer is month-to-month at a Core (one day a month) or Growth (two to three days a month, with a new use case monthly and vendor management) level, with 30 days' notice. We'll scope it against your business in the first call.
The baseline is set at Day 30. Day 90 is scored against it.
Every Fractional AI Officer engagement we run ships with a scorecard like this, delivered monthly on the retainer. Targets are set with you during the audit, so the readout has something real to measure.
| Metric | Baseline | 90-day target | 12-month target |
|---|---|---|---|
| Hours returned to the team per week | 0 | 20+ | 60+ |
| Staff using approved AI tools weekly | Measured | 80% | 95% |
| Automations live with named owners | 0 | 2–3 | 10+ |
| Speed to first response on new leads | Hours | Under 1 hr | Under 15 min |
| AI assistant recommendation rate for the brand | Measured | Top 3 gaps closed | Recommended in test prompts |
| AI governance incidents | n/a | 0 | 0 |
Illustrative targets for a 5–50 person company. Yours are set from your baseline.
Most AI officers know the technology. Ours have carried the P&L.
Come from technology. They can explain the model but have never run a campaign that had to produce revenue.
Bolt "AI" onto their homepage and call it strategy. There's no roadmap, no policy, no scorecard.
Is both. Thirty years of sales and marketing with P&L accountability, and AI built into every client workflow since 2022.
Chris Bernard has spent over 30 years in sales and marketing, eighteen of them leading Content Engagement Lab.
Big-brand work at Starcom MediaVest and Publicis gave us the tools, resources and techniques to ask better questions. Your business has what those brands never will: the speed and agility to act on the answers.
Meet ChrisThe rules come first. Then the automations.
A Fractional AI Officer is accountable for the company's AI risk, not just its AI upside. These are the standards every engagement starts with and every automation ships under.
Acceptable-use policy.
What staff may put into which tools, written for the roles they hold, approved by leadership by Day 60.
Vendor review standard.
A checklist every new AI subscription passes before it touches customer or company data. No shadow AI.
Human in the loop.
AI drafts, people decide. Autonomy is graduated on observed results and never assumed. Every automation has a kill switch and a named owner.
Consent and compliance.
Outbound on consented channels only. Voice AI is inbound and consented; we don't build outbound AI cold calls.
Tool-agnostic. You own the deliverables.
Every recommendation is independent of any vendor, and any referral relationship is disclosed in writing. All roadmaps, policies, automations and documentation produced in the engagement belong to you. The retainer is month-to-month with 30 days' notice, so the only reason to stay is that the scorecard says you should.
Questions owners ask before they book the call.
What is a Fractional AI Officer (FAO)?
A Fractional AI Officer (FAO) is an executive who owns a company's AI strategy on a part-time, retained basis, typically one to three days a month. The role decides where AI belongs in the business and where it doesn't, builds or oversees the first working automations, sets the governance and guardrails, gets the team using the tools, and reports measurable outcomes: hours returned, leads converted, costs removed. It gives a small or mid-sized business chief-AI-officer judgment without a full-time hire.
Why hire a Fractional AI Officer (FAO) instead of a full-time Chief AI Officer?
A full-time Chief AI Officer costs $250,000 to $400,000 or more and is scarce. Most companies under $50 million in revenue need the judgment, not the headcount. AI tooling also changes monthly, and a fractional officer brings pattern recognition from several clients that a single-company hire can't. The work is front-loaded, heavy in the first 90 days and then a steady monthly cadence, which fits the fractional model.
What does a Fractional AI Officer actually do each month?
Week one is a 60-minute executive brief on what changed in AI, what it means for your business and what decisions are needed. Week two is building or overseeing the month's use case and reviewing what's in production. Week three is office hours and a training touchpoint open to all staff. Week four is the AI scorecard and a re-ranked backlog. In between, Slack or email questions get a one-business-day response.
How is a Fractional AI Officer different from a Forward Deployed Engineer?
The AI Officer answers "what should we do with AI, and how do we govern it?" The role works with the CEO and leadership team one to three days a month and produces strategy, a roadmap and policy. A Forward Deployed Engineer answers "how do we make this specific workflow work with AI, in production?" The role works with operators two to five days a week during a build and produces deployed automations and SOPs. The AI Officer sets the backlog; the FDE builds from it. More on the FDE role.
How does the engagement work?
Two phases. A 90-day Foundation Sprint produces the AI readiness audit, ranked roadmap, governance policy, two to three live automations, role-based training and an AI visibility baseline, ending with a leadership readout. A month-to-month Advisory Retainer then delivers one new use case a month, a monthly executive brief and AI scorecard, team office hours and vendor decisions.
What is "AI visibility," and why is it the AI Officer's job?
When a buyer asks ChatGPT, Google AI or a voice assistant who to call, the assistant names one or two companies, not ten blue links. AI visibility, sometimes called answer engine optimization (AEO), is the work of making sure your company is that answer. We baseline how AI assistants currently describe you, then fix the site, content and structured data that feed them. It sits with the AI Officer because it's a leadership decision about how the company is positioned, not a marketing tactic.
Will this replace people on my team?
Every automation is designed around goals set with the people who do the work, and ships with a named human owner. In our experience the hours returned go to higher-value work: the marketing team that got 38% of its week back used it to raise the organization's billable rate from $150 to $350 an hour. Being clear with your team about what AI will and won't do is part of the officer's job.
Stop having the AI meeting. Start having the AI plan.
Fifteen focused minutes on your business. You'll leave with your top AI opportunity identified and a clear picture of what the first 90 days would produce.
Talk to a Fractional AI Officer