Questions, answered plainly

A fractional Chief AI Officer is a senior AI executive who serves your company part time, owning AI strategy, vendor decisions, and governance without the cost of a full-time hire. You get the judgment of an experienced AI leader in your leadership room, scaled to what a mid-market company actually needs.

Attain's version of the role is strictly advisory. We hold the seat, make decisions with you, and sell nothing else.

A fractional CAIO sets AI direction, makes and documents AI decisions with the CEO, evaluates vendors, and builds the governance a customer or regulator will ask about. In practice that means a decision agenda reviewed on a fixed cadence, written decision memos, vendor evaluation memos, and a quarterly value report.

The job is judgment on record, not hours on site.

No. Attain does not build, implement, or resell anything, by design. Builders profit from the decision to build, so their advice bends toward building.

We hold the executive role: direction, decisions, governance, and vendor accountability. Your team or your vendors execute, and we evaluate them with nothing to gain from the outcome. Advice is the product. Nothing else is for sale.

A fractional CAIO owns AI strategy and governance; a fractional CTO owns engineering and infrastructure; a fractional CDO owns data platforms and data quality. The roles are adjacent, not interchangeable. AI decisions now carry board, customer, and regulatory weight that sits outside a technology roadmap.

We work beside your CTO as a peer, not above or instead of them. Divided attention is the alternative, and it is expensive.

No. A consultant delivers a project and leaves; a fractional CAIO holds an ongoing executive role with decisions on record. Consultants and agencies also typically earn implementation revenue, which shapes the roadmap they hand you.

An independent fractional CAIO is accountable for the quality of decisions over quarters, not for the size of the build that follows them.

A fractional CAIO owns the AI governance baseline: usage policy, data handling rules for AI tools, vendor risk review, documentation standards for models and prompts, and board reporting on AI. The test we hold governance to is simple: it should survive a customer security questionnaire or an auditor's questions without embarrassment.

Regulated industries keep their existing compliance owners. Our job is making sure AI does not open a new gap between them.

Attain engagements are structured around outcomes and a working cadence, not days on site. Depending on tier, that is a fixed rhythm of working sessions plus an async window for the decisions that cannot wait for the next meeting.

Accountability comes from the decision agenda and positions on record, not from hours. Each tier carries a monthly time cap, detailed in the engagement terms.

The first month produces a written baseline and a prioritized 90-day decision agenda; impact shows up as decisions made and documented within the first quarter. Every Attain engagement starts the same way: a diagnostic baseline of where AI moves revenue, cost, and risk in your business.

From there the operating rhythm works through the agenda. By day 90 you have positions on record, not a plan to make a plan.

Hire a fractional CAIO when AI decisions carry six or seven figures of consequence and nobody in the leadership room owns them. Common triggers: a vendor pitch that sounds convincing, a board asking for an AI answer, a list of stalled pilots, or a customer questionnaire about your AI governance.

If the decisions in front of you are small, rare, or easily reversed, you do not need the role yet.

The fractional model fits companies large enough that AI decisions carry real money, and not yet large enough to justify a full-time AI executive. For Attain that means US founder-led companies of roughly 50 to 500 employees, typically above $5M in revenue.

Below that range, a one-off diagnostic usually answers the question. Above it, the graduation clause applies: we help you hire a full-time leader when scope justifies one.

No. Large enterprises staff the role full time; mid-market companies face the same decisions with none of the staff. That gap is exactly what the fractional model exists to close.

The decisions do not shrink with company size. A vendor commitment, a data policy, or a build-versus-buy call can move a mid-market P&L further than an enterprise one.

Five. The ceiling is published and it is a design choice, not a capacity accident. Executive advisory does not scale like software; judgment degrades when attention is split too many ways.

The ceiling is what makes the async windows honest and the working sessions prepared. When we are at five, we say so and hold a waitlist.

We help you hire our replacement. The engagement is designed to graduate: when AI scope justifies a full-time leader, we write the role definition, help you interview, and hand over a documented decision history instead of a dependency.

Success that ends in a strong full-time hire is the engagement working, not the engagement failing. The search itself is covered end to end in our guidebook, How to Hire a Chief AI Officer.

A fractional CAIO at Attain costs $6,000–$15,000 per month, published openly. Lite runs $6,000 for direction, Core runs $10,000 for decisions, and Executive runs $15,000 for a full operating rhythm. Most clients engage at Core.

Engagements carry a three-month minimum, then roll monthly. The $5,000 diagnostic is standalone and credited against the first retainer month if you convert.

A full-time Chief AI Officer in the US costs roughly $300k to $550k all-in per year, counting salary, bonus, and equity. That number is why most mid-market companies should not start with the hire.

The judgment is needed now; the full-time workload usually is not. The fractional model prices the judgment at a fraction of the all-in cost, and the graduation clause covers the day the workload catches up.

Sometimes no. If AI decisions in your company are small, rare, or easily reversed, an occasional external review beats a standing role, and we will say so on a fit call.

You need the role, fractional or not, when AI spend crosses into six figures, when the board expects a coherent AI answer, or when customers start asking governance questions your team cannot answer in writing.

The honest answer: results depend on the decisions in front of you, which is why every engagement starts with a baseline and a 90-day decision agenda rather than a promise. Typical first-quarter outcomes are documented vendor decisions, a roadmap the leadership team actually agrees on, and a governance baseline that passes customer scrutiny.

Anonymized result narratives are published on this site, and references are available on request. We never name clients.

Thirty years operating in technology, including Google, AWS, and McKinsey, and building AI products since 2014, roughly eight years before the current wave. That operating history is the qualification that matters most, and it is verifiable on LinkedIn.

On top of it sit current certifications: Claude Certified Architect, AWS AI, and Google Professional AI.

By operating a production AI system daily, and by holding the advice to an audit standard. Attain runs on its own AI system; what we recommend is grounded in what we operate, not in vendor briefings.

A governance credential stack is in progress: CAIO-CP, IAPP AIGP, ISACA Advanced in AI Audit, and ISO 42001 Implementer, alongside Anthropic and Qwen ecosystem partnerships. The bar we work to is simple: advice that survives an audit.

Under a mutual NDA as standard, governed by a one-page data policy you can hand to your security team. Client material never enters model training, ours or anyone's.

Professional indemnity insurance is in place. If your industry needs more, say so on the fit call and we will put it in writing before the engagement starts.

Almost certainly, because the CAIO role is domain-independent by design. The judgment being bought is about vendors, governance, sequencing, and risk. Your team supplies the domain depth; we supply the AI depth and the independence.

Thirty years across technology, consulting, and operating roles means most industry patterns are familiar. Where one is not, the diagnostic surfaces it in the first month, on your numbers and in your language.