01
Tool sprawl, shallow use
Every function picked its own AI tool. The subscriptions add up. Actual workflow value is uneven and rarely measured.
AI that actually changes how the work gets done.
I'm a fractional Chief AI Officer. I work as a part-time fully embedded leader for small-to-mid-market companies that want AI to be a reliable part of how work gets done rather than an expensive novelty.
Built for leadership teams that have tried AI and know the workflow has not actually changed.
- CEO
- COO
- CIO
- CFO
- Founder
- Leadership team
What this comes from
Pressure to act on AI, without a clear plan.
Most companies we see have at least two of these going on:
02
A handful of power users
One or two people do impressive AI work. Everyone else copies the surface and misses the judgment that makes it work.
03
Pilots that don’t graduate
Promising experiments stall before they become how the company actually operates.
04
No shared picture of good
Different people on the same leadership team have different answers for what AI should be doing here.
What fractional means
A part-time fully embedded leader, not a consultant.
A fractional is a part-time fully embedded leader. The only difference between a fractional and their full-time counterpart is that they are part-time.
When I take a retainer engagement, I am in the seat. I sit in leadership team meetings. I participate in real decisions. I am accountable for outcomes alongside the existing leadership team. I am not a vendor or an external advisor. I am a part-time CAIO.
Small-to-mid-market companies often cannot justify a full-time Chief AI Officer at the salary that role commands. They also cannot afford to keep treating AI as a side initiative that no senior leader actually owns. The fractional model fits that gap.
How I work
Three shapes of engagement.
The right shape depends on where your company is starting from.
01
Embedded retainer
The primary engagement. I sit in the leadership team a few hours a week, drive AI adoption, and help redesign workflows around what AI makes possible. Weekly contact, monthly written summary, quarterly strategic roadmap.
02
30-day diagnostic
For companies that want to test the relationship before committing. A focused engagement that identifies the highest-value AI workflows and delivers a feasibility-validated roadmap. Many engagements continue into the retainer afterward.
03
Scoped build work
When the retainer surfaces build work that needs dedicated attention, I take that on through a separate statement of work. This is where workflows actually get rebuilt, not just recommended.
Video podcast
Frontier Tech.
Frontier technology for the people building real companies. Latest episode: AI in the Lab Episode 1, building an automated crypto trading app with AI as a partner. Recording now on YouTube.
How I think about AI capability
A few beliefs that shape how I work with teams.
01
Buying AI tools is not buying AI capability
Licenses purchased and tools opened are not the same as work being done differently. Compute is the cheapest part of the stack and the easiest line item to cut when leadership looks for ROI.
02
The real work is workflow redesign and AI proficiency
Better prompts cannot save a workflow that was never designed for AI involvement. The work has two layers. Redesign workflows around what AI makes possible. Level up the people doing the work so they move past chatbot-grade use.
03
AI accelerates the direction the company is already moving
If the direction is wrong, more speed makes things worse. If the leadership team is not aligned on what AI should accomplish, no tool deployment can fix that.
04
Most failed AI initiatives are not AI problems
They are data, workflow or ownership problems. Outdated data produces wrong recommendations. Undefined workflows resist automation. Unclear ownership produces motion without accountability.
05
Embedded leadership produces different outcomes
A consultant who hands over a deck and leaves has no skin in whether the recommendations work. A fractional executive who sits in the leadership team week to week is accountable for outcomes alongside the existing team.
06
Trust takes time
AI did not change that. It just made it cheaper to ignore. The companies that succeed treat verification and judgment as core engineering work, not as polish.
If your company has tried AI and is not seeing real impact, let's talk.
Email a short note about your situation and the workflow you want to change. I will set up a 30-minute scoping call to see whether a fractional engagement fits.
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