Founders comparing a fractional AI/CTO retainer to a full-time hire often start with the wrong question: "what is cheaper?" The honest answer depends on the engagement, but the more useful question is: "what is the right shape of leverage for this stage of the business?"
The math matters and I will get to it. But the math is downstream of the shape question, and most of the conversations I have about fractional retainers go better when the shape gets settled first.
The math, plainly
A senior AI and engineering executive hire is $400K to $600K all-in for a US-based mid-stage digital health or healthcare-AI company. That includes base salary, equity, benefits, recruiter fees, signing bonus where relevant, and the ramp cost in the first six months. The search itself takes three to six months in the current market — longer for the AI-specific roles because the candidate pool is thin and the credible-AI-plus-compliance combination is thinner still.
A fractional retainer in the same space is $60K to $180K per year, depending on scope. There is no recruiter fee. There is no equity dilution. The engagement starts in two weeks. The replacement cost if the fractional is not working is one month of notice, not a six-month search and a severance package.
The full-time hire owns the org full-time. The fractional engagement is shaped to specific outcomes: AI strategy, AI governance, hiring support for the eventual full-time CTO, architecture review, embedded leadership presence at the exec rhythm.
For most companies in the pre- or between-CTO state, the per-month math favors the fractional. For most companies that already know what their next CTO needs to do for the next three years, the per-month math favors the full-time hire. The middle case — where the role is partly defined and the company is still discovering what it actually needs — is where the fractional engagement earns its keep.
When the fractional engagement is the right shape
There are four situations where a fractional AI/CTO is genuinely the right call, not just the cheaper one:
1. Pre-CTO and not yet ready to commit to the wrong hire
The company has a head of engineering or a strong founder-engineer. It does not yet have the AI strategy clear enough to write the right CTO job description. Hiring a full-time CTO right now would lock in the wrong scope. A fractional engagement does two things: it executes the AI strategy work that needs to happen this quarter, and it sharpens the eventual full-time CTO job description so the search is grounded.
The best ending for this engagement is the fractional helping recruit the full-time hire and handing off cleanly.
2. Between CTOs and not willing to lose six months
A previous CTO has left. The search is starting. The board does not want to see six months of stalled AI work while the search runs. The fractional engagement covers the interim, keeps the AI workstream moving, and reduces the panic urgency that produces bad full-time hires.
The best ending here is the fractional engaging the new full-time CTO in a structured handoff over a month or two, then dropping to advisory.
3. A working CTO who needs an AI specialist partner
The full-time CTO is excellent and is not going anywhere. The AI surface is new for them and is starting to dominate the roadmap. They need a peer to think with, not a junior to manage and not a replacement. A fractional AI specialist who reports to the CTO is a clean way to add depth without disrupting structure.
The best ending here is the fractional becoming a long-term advisor as the CTO's team scales up its own AI capability.
4. Board or investor staging in AI leadership ahead of placement
The company is heading toward a larger round, or a private-equity transaction, where having an AI leader in the org is a value driver. The board wants someone in seat before the round closes. A fractional engagement is faster than a full-time search and is presentable to the next round of investors. After the round, the company has the budget for a permanent placement and the fractional helps run the search.
When the fractional engagement is the wrong call
It does not make sense when:
- You need someone full-time on the org. The company has scaled past the point where part-time leadership can carry the load. The fractional model breaks down when meetings and decisions can no longer be batched into a defined cadence.
- The work is hands-on coding more than 50% of the time. That is a different engagement — closer to a Build engagement, or a senior contract engineer role. Calling it a fractional CTO confuses the scope and undercharges for the work.
- The board wants accountability for the full P&L of engineering. A fractional engagement can own outcomes within a scope. It cannot own the full P&L the way a full-time CTO does. If the board needs that, it needs to do the search.
What the fractional retainer actually buys
The misconception that costs founders the most is treating the retainer as a fixed number of hours per month. It is not. A good fractional engagement is shaped to outcomes, and the time invested varies by week — heavier during a strategy sprint, lighter during a quiet quarter, on call when an incident or a vendor decision needs senior judgment.
What the monthly retainer actually buys, in a healthy engagement:
- A defined cadence with the executive team — typically weekly leadership presence, biweekly board prep where relevant
- Architecture and design review on every major AI decision
- Direct involvement in the AI hiring loop — interview design, candidate calibration, offer support
- Vendor and tooling decisions reviewed at the senior level
- Incident response when something breaks in a way the team has not seen before
- An honest second opinion when the team is about to make a mistake
The engagement is shaped to make itself unnecessary. The end state is either a full-time CTO transition where the fractional has done the search and built the onboarding plan, or a continued partnership focused on the AI surface specifically, scoped down as the in-house team grows.
The shape of pricing
Published pricing on this site is $5K to $15K per month, three-month minimum. The minimum exists because the first month is mostly discovery and onboarding — a one-month engagement does not produce enough leverage on either side to be worth the setup cost.
The lower end of the range fits a smaller scope: weekly cadence with one or two executives, AI architecture review, hiring support. The higher end fits a broader scope: embedded leadership presence at exec rhythm, deep involvement in roadmap and customer commitments, on-call for incident response.
What does not vary across the range: the work is senior-CTO-grade. The fractional model is about time shape, not seniority level. If the engagement is anything other than a senior peer to the CEO and the rest of the executive team, it is not a fractional CTO engagement — it is a different thing labeled the same way, and the pricing should reflect that.
How to think about ROI
The full-time CTO ROI conversation is about the value of the AI strategy compounding over multiple years. The fractional ROI conversation is about the value of the right decisions made in the next two to three quarters.
For most digital health companies I have seen at the pre-CTO or between-CTO stage, the right decisions in the next two quarters — vendor lock-in, BAA chain, AI governance design, eval strategy, what to build versus what to buy — are worth multiples of the fractional retainer. The bad decisions in the same two quarters are worth multiples of the wrong direction.
The retainer is the price of buying back the time that getting those decisions right would otherwise cost. That is the ROI math that holds.
If you are staring at the fork between a fractional engagement and a full-time search, book a call. Most of these conversations are short and clarifying. For the broader framing of how the engagement fits into a healthcare AI roadmap, the full version of the strategy work is in the Healthcare AI Automation Playbook.