Why You May Need One More Than You Think
There's a personal story behind this one.
In late October 2023, right before I left for a 10-day Vipassana retreat in India, I was signing on as a fractional partner — with loose equity — in a business called chiefaiofficer.com. It was started by a guy I didn't know well. He appeared to know what he was talking about. He was a big-time coach — or so he said. He definitely knew how to talk a big game.
He came to me asking for technical help. I had a team of developers at the time, so I told him I'd be glad to contribute. I even flew out to Santa Fe, New Mexico, to meet the team.
The premise of the business was simple. Every company, eventually, was going to need a Chief AI Officer. Peter Diamandis — XPRIZE founder — had a talk on AI and the future of work where he made exactly that case. His line was direct: there are two kinds of companies this decade — those fully utilizing AI, and those out of business. That video was the literal call-to-action on the early homepage. If you'd asked me at the time, I would've said he was right, and I still say he's right. The thesis isn't what failed.
Keep in mind this was deep — deep — into my personal and professional dark night of the soul. My son Finn had died six months earlier. I didn't want to work. Who does in that state? But I had to work. We all have to work. And I was searching desperately for meaning in the work, or at minimum a team I liked, doing something I was good at.
So I said yes.
End of October. I told the CEO and the rest of the team that I was going into a 10-day silent retreat. My dev team is at your disposal, I said. Use them as you need. Then I went offline — really offline — for about twelve days. (The Vipassana Reset covers that period.)
I came out the other side and looked at the invoice.
It had ballooned. My project manager had five guys on it. The billing machine was cranked. I told the PM to slow it down — we couldn't bill this hard without confirming the work was actually authorized. The CEO had been approving every request, but I suspected he didn't understand what those requests cost. I raised it with him. I was right. He was shocked.
That's where the relationship collapsed. He declined to pay — anything. Four months of development work sat on the books. I'd been planning to cut him a break on rates because he was giving me equity. The equity evaporated. He started firing people because he couldn't pay other bills. He dipped into his own savings. And to this day, the guy still owes me tens of thousands of dollars.
This was at a time when I didn't really care about anything in life. I'd been working for him full time. I wanted it to work, because I knew — I still know — every serious company is going to need fractional or full-time AI leadership. I mean, it was obvious even back then.
Meanwhile, I still owed my team for the work.
Eventually, I wrote to him. "Hey — not sure if you knew, but my son died earlier this year. I'm hurting. It would really help if you'd pay your dev bills."
His response, roughly: "Oh wow, so sorry to hear that. Had I known, I would never have hired you. I have a rule — I don't hire people who are going through tough times. Divorce, drug problems, things like that." I don't recall exactly what he said, but the sentiment was clear. I should have been more forthright about my situation, I guess.
I've since moved on from that team. I'm fighting for my own survival now, paying bills as they come, and I've told my former developers I'll keep chasing him until he pays. I still write him from time to time on Telegram. I keep it polite so he won't ghost me, hoping he'll come clean. We're at thirty months. My illusions are fading.
It's strange that two and a half years later, I've come full circle to the idea he was selling. He was right about the thesis. He was catastrophic at the execution — though I suspect he's actually doing really well, and he still won't pay me. Writing this post about him, one that he will likely never see, is my own way to vent an awful business situation that upset me and my team for many months. I feel some small sense of retribution, and I know karma will eventually pay him back in some way.
What a Fractional Chief AI Officer Actually Does
Here's the part that matters for you, if you're reading this trying to decide whether your company needs one.
A fractional CAIO — what I do at TestVentures — is not an AI consultant who writes a deck and disappears. It's not a prompt engineer. It's not a developer wrapping APIs around the mess you already have.
A fractional CAIO is the operator who sits inside your business 10–15 hours a week, learns how the company actually runs, and rebuilds the operation around what AI can now do that it couldn't do two years ago. You still own the domain. You still run the company. I handle the AI layer that sits on top of every workflow that used to require a full-time human to execute.
Most of the enterprise clients who might need a fractional Chief AI Officer are world-class at what they do. A wealth manager with thirty years of client relationships. A professional services firm where the partners are the product. A family office that runs on trust and judgment. None of them are technology companies. None of their founders came up writing code. That's not a weakness — it's the reason they're good at what they do. They don't even know who to hire. To be sure, if they did start looking, what would they even be looking for? A virtual CTO? Maybe a recent college grad who was really good at software development and using AI — honestly, that would beat the virtual CTO, who would sell you services you didn't need and smother you in jargon.
Diamandis said roughly the same thing in Inc. — find somebody 22 years old who's in love with AI, he advises. He's not entirely wrong. But a 22-year-old knows AI; they don't know your operation. That's the gap a fractional CAIO fills.
But it does mean that when AI changes the economics of their operation, they often don't have anyone in-house who can tell them what's real, what's hype, what works in their specific context, and what they should stop doing manually tomorrow morning.
That's the job.
A company doesn't need a full-time Chief AI Officer at $250K+ a year to do it — at least, not yet. A fractional CAIO on a monthly retainer is enough to move the operation hard and save headcount until it's really needed.
What I actually do on an enterprise retainer:
I sit in on their operations meetings when it's needed. I watch the work. I rebuild the parts that shouldn't still be manual — client reporting, research summaries, meeting notes, pipeline tracking, compliance drafting. I hire and manage the AI specialists underneath me so the client doesn't have to. I decide which tools get adopted and which ones never get in the door. And when something new ships — in this market, that's every week — I decide whether it matters for them, and if it does, I integrate it.
The founders I work with don't want to become AI experts. They want to keep being the best at what they do while their operation quietly gets five times faster and more accurate underneath them.
That's the value of a fractional CAIO. Not theory. Not a roadmap deck. An operator, embedded, shipping.
When to Hire a Fractional CAIO — The Five Trigger Events
If you're not sure whether it's time, here are the five signals I see most often in the week a client finally picks up the phone.
1. You're still the one doing the pattern-matching work.
You — or your most senior partner — is the only person who can reliably turn a client call into a usable summary, a pile of research into a decision memo, or a messy draft into a polished deliverable. Every time, it comes back to your desk. That's not leverage. That's a bottleneck in a suit.
2. Your team is using AI tools off-book, with no coordination.
Four people on ChatGPT. One on Claude. Marketing on Copilot. Legal quietly running documents through something nobody has vetted. Nothing shares state. Nothing compounds. Everyone is reinventing the same prompt twice a week. You have AI usage, but you don't have AI operations.
3. A competitor shipped something that used to take a team, and you can't tell how.
They're turning proposals around in two hours. Their research briefs are suspiciously thorough. Their inbound responses feel like they hired a whole new desk. Nobody in your shop can tell you whether they're using AI, which tools, or whether you can catch up. That gap gets wider every month you delay.
4. You've tried hiring an "AI person" twice and neither stuck.
First one was academic — brilliant on LLM theory, couldn't ship anything your ops team would actually use. Second one was a developer who built a chatbot nobody talks to. The problem wasn't the people. The problem is that "AI person" isn't a role. It's a stack of four roles, and founders keep hiring for one of them at a time.
5. Your operational costs are rising faster than your revenue.
Headcount is creeping. Software licences are multiplying. Reporting takes longer than it did last year. Something underneath the operation isn't being rebuilt, and you can feel it without knowing where to cut. This is the most common trigger I see, and it's usually the last one a founder will say out loud.
Bonus trigger: the founder-in-every-meeting problem.
You're still in every client call, every partner sync, every ops review, because the operation can't run without your pattern-matching. That's a lifestyle problem and a succession problem. A fractional CAIO rebuilds the operation so you're back to running the parts only you can run.
If two or more of these are true, it's time.
A Real Day — What Tuesday Actually Looks Like
Fractional means embedded, not scattered. Here's a real Tuesday for me on retainer.
6:45 AM. Coffee. Gratitude journal. Headspace. I open my Obsidian dashboard and read the overnight digest from my AI team — what shipped on each client's operation while I was asleep, what got flagged for human review, what's waiting on a decision. I run an AI ops agent loop across all active clients; it reports in every morning before I do anything else.
8:30 AM. Thirty-minute ops review with the client's COO. We go through the pipeline dashboard, the three items my agents flagged, and what's on the table for the week. Two questions, one decision, done.
9:00 – 11:30 AM. Build time. This week I'm rebuilding a client's research-summary pipeline. Their analysts write two-page briefings on private companies, and about forty percent of each briefing is structured lookup that doesn't need a human. I ship a Claude workflow that produces the structured sections in three minutes. The analysts keep the judgment sections. Net effect: four hours a week back to each analyst, seven analysts, twenty-eight hours a week recovered. They'll spend those hours on the judgment work the firm actually bills for.
11:30 AM – 3:00 PM. Midday break. If I'm lucky, the waves are up. I hop on the Royal Enfield, strap on the favourite twinnie, and catch 90 minutes of good surf. Other days it's a long lunch outside with Kirsten and the two dogs. This middle-of-the-day block isn't optional — the afternoon is cleaner when the middle of the day is real life.
3:00 – 5:30 PM. Second client block. Different industry — a family office running compliance-heavy workflows. Today it's a 45-minute working session with their ops manager, kept at arm's length through async comms on Trello and Loom. Then the rest of the block is drafting their monthly AI governance memo and onboarding a new specialist I've brought in to handle reporting automation underneath me.
5:30 – 6:30 PM. BIP writing. Ship today's build-in-public post, review tomorrow's. File handoff notes for future sessions. Close out. (What's BIP? You're reading it.)
Evening. Family. Reading. Off.
That's two to three hours of ops time per client, four days a week, inside a life that still looks like a life. The clients don't want forty hours of me. They want five hours that rebuild the week.
CAIO vs. CTO vs. AI Advisor — Don't Hire the Wrong One
These three roles get confused constantly, and the wrong hire wastes a year.
A CTO builds and owns your technology stack. They hire engineers. They decide architecture. They're responsible for the platform that runs your product or your internal tooling. If your company is a technology company, you need one. If your company is a wealth management firm or a professional services partnership, you almost certainly do not.
An AI advisor meets with you monthly. They review your roadmap, recommend tools, flag what's coming in the market. They do not execute. They are the AI equivalent of a board member — useful, slow, and fundamentally strategic. They don't change your Tuesday.
A fractional CAIO rebuilds how the operation runs. They sit inside the business, redesign workflows around what AI can now do, hire and manage the AI specialists who execute the work, and make weekly decisions about what the company adopts, retires, or ignores. They are closer to a fractional COO with an AI mandate than to a CTO.
Shortest version: the CTO owns the platform. The advisor owns the opinion. The CAIO owns the rewrite.
If you hire a CTO when you needed a CAIO, you get a beautifully architected internal tool that nobody in ops uses. If you hire an advisor when you needed a CAIO, you get a roadmap and no execution. If you hire a CAIO when you needed a CTO, you get great AI workflows running on infrastructure that will fall over in a year.
Diagnose the job before you hire for the title.
How to Hire a Fractional CAIO — And How Not To
This is where I'm going to be direct, because I've now been on both sides. Most of the people selling fractional AI leadership right now are selling it because they took a three-week cohort course and got a certificate. That's not a moat. That's the marketing funnel the coach who ran the cohort is running on them.
Here's what to check before you sign anything.
1. Ask them to walk you through one workflow they've built for a real client.
Screenshare. Open the tool. Show the input, show the output, show the cost. If they can't do this in five minutes, they haven't built one. If what they show you is a ChatGPT custom GPT, they're playing at it.
2. Ask them to name three operators they've helped — and let you talk to one.
References should be operators, not other coaches. If their reference list is full of other fractional leaders who trained in the same programme they did, you're looking at a pyramid, not a practice.
3. They should be in your operations meetings, not on a monthly Zoom.
Fractional does not equal advisor. It does not equal monthly call. If the person wants to "connect every few weeks and check progress," they're an advisor with delusions of execution. A CAIO is in your ops review at least once a week, and often more.
4. Payment terms need to be clean before the work starts.
This is where the cautionary tale at the top of this page matters. The man who ran chiefaiofficer.com — the founder I told you about — is the textbook failure case. He hired my team, approved the work, then declined to pay when the bill arrived. Thirty months later he still owes me tens of thousands of dollars, and he's still firing people because he can't cover the operation.
The lesson isn't about him specifically. It's about the pattern. If a fractional leader can't pay their own contractors on time, do not let them anywhere near your operating decisions. You're about to be the next contractor waiting thirty months for a cheque, and worse, you're trusting their judgment about how to rebuild your business while their own is underwater.
Ask to see invoicing terms in writing. Ask how they pay their own team and on what schedule. Pay them only on clean terms — deposit up front, net-15 after.
5. Coaching background without technical depth is a red flag, not a resume line.
"Big-time coach" is not a substitute for "has shipped AI workflows into live operations." Coaches without a technical team underneath them are repackaging the content of whoever trained them. You don't want the course. You want the operator.
6. Ask them when they'd tell you NOT to use AI.
If they can't give a fast, specific answer — a workflow, an industry, a class of decision — they haven't thought about it. AI is a tool. Anyone who sells it as a universal answer is selling you a vibe.
7. Ask them what their stack looks like in September.
Trick question. Nobody knows what the stack looks like in September. The right answer is some version of: "I re-evaluate the stack every month. Here's what I'd drop today, here's what I'm watching." If they give you a confident twelve-month roadmap, they're either lying or not paying attention.
Get these seven right and the risk collapses.
Frequently Asked Questions
What does a fractional Chief AI Officer cost?
At TestVentures, pricing depends on what you need. The standard package — unlimited requests, one task at a time — is $4,995 per month. No contracts, pause or cancel anytime, and 75% back if the first week isn't a fit. For larger enterprise engagements, where I'm embedded deeper, hiring specialists underneath me, and running the AI layer across a whole operation, pricing is custom and quoted in your currency. As a benchmark, a full-time CAIO runs $250K–$400K a year loaded. Most operations under 100 people don't need the full-time hire yet.
How is a fractional CAIO different from an AI consultant?
Consultants deliver a deck. Fractional CAIOs embed, execute, and own the outcome. Consultants bill hourly and leave. A fractional CAIO is on the retainer every week until the operation runs without them — and usually long after.
How long until I see results?
First workflow shipped inside a week. First measurable cost-or-time compression in thirty days. Full operational rewrite in 60 to 90 days. If we're at sixty days and nothing has materially changed, one of us is in the wrong engagement.
Do I need a technical background to hire one?
No. My best clients are domain experts — wealth managers, family offices, professional services partners — who are world-class at what they do and explicitly not technologists. The whole point of hiring a fractional CAIO is so you don't have to become one.
Can a fractional CAIO replace my IT person?
No. Different job. IT keeps your existing systems running. A CAIO redesigns how work gets done. You need both, and they should talk to each other.
What industries are the best fit?
Professional services. Wealth management. Family offices. Legal ops. Accounting firms. Agencies. Nonprofits. B2B services. Anywhere the value is in human judgment and the drag is in process work. Less fit: heavily regulated industries with zero tolerance for experimentation, and early-stage consumer startups who really need a CTO.
What if the AI stack changes again in six months?
It will. That's the job. You're not hiring me for a specific tool. You're hiring me to re-decide the stack every month, integrate what works, kill what doesn't, and keep your operation ahead of the line. If you want stack stability, hire an IT manager. If you want to stay ahead, hire a CAIO.
How do I start?
Book a 15-minute discovery call at testventures.net. We diagnose the fit on the call — no deck, no pitch. If it's not a fit, I'll tell you who I'd send you to instead.
Closing
Every serious operation is going to need AI leadership inside the next two years. Most of them are going to hire wrong at least once before they hire right. I've been on both sides of that — as the guy who got burned by a coach masquerading as a CAIO, and now as the operator clients hire when they're tired of decks and want the work done.
If you're reading this trying to decide, here's the honest answer. If two of the triggers in the first half of this page are true, the cost of waiting six more months is almost always higher than the cost of starting. Book a call. Let's see if it's a fit.
And if it's not — I'll point you at someone better.