AI Strategy
AI strategy is deciding where AI belongs and where it doesn’t, fitting it into how the business actually runs, and getting it built, adopted and paying back. I bring the business, finance and operations judgment to make the economics work, and I fix AI that was put in the wrong place.
- Companies spending on AI without a return
- Teams that slapped AI on something, or vibe coded something that now can’t scale
- Pilots that stalled
- Boards asking for an AI strategy
- PE portfolios that need AI across several companies
Where AI belongs
AI is a force multiplier. It does not care if it is multiplying your output or your chaos.
AI is not Frank’s Red Hot. We don’t put that on everything.
I don’t just look for where AI can go. I look for where it belongs.
Some problems require deterministic solutions. Some benefit from probabilistic ones. Getting that wrong, in either direction, is one of the most expensive mistakes an organization can make right now.
How I look at it
An organization is not complicated. It is complex. It adapts. It responds to being observed. It has emergent behavior that doesn’t appear in an org chart, a requirements document, or a kickoff call.
I was trained in complex adaptive systems. I approach every engagement the way a diagnostician approaches an unknown: no hypothesis before evidence.
I use human factors to diagnose how people actually work inside the system, and to help leaders make better decisions about where AI belongs.
Humans stay in control of the loop, but not as a redundant step that adds friction. Where a person adds judgment, they stay. Where they only add delay, the design changes.
What I do
What gets automated, what stays human, where AI creates advantage and where it creates risk. Built for your industry, your workflows, and your risk tolerance.
Before anything is built
- What outcome are we trying to create?
- Is the underlying process understood?
- Should the problem be solved deterministically or probabilistically?
- What should remain human?
- Where does AI create actual leverage?
- Where does AI introduce unnecessary risk or complexity?
Inside or outside the organization
From the outside
An independent diagnostic and a clear decision on what should change.
Alongside your team
A senior operator embedded for the decisions that matter, for as long as they matter.
In the seat
AI leadership inside the organization, as a fractional or interim Chief AI Officer.
FAQ
What is AI strategy, and who needs one?
Deciding where AI belongs in your business, where it doesn’t, and what has to change around it for it to actually pay back. Any organization spending on AI, or about to, needs one before building, not after.
Do you work as a fractional Chief AI Officer?
Yes, and also as an outside advisor or an embedded operator. The engagement fits the situation, not the other way around.
Can you fix AI we’ve already built?
Yes. The first question is whether to keep it, refactor it, rebuild it, or replace it. The answer depends on where it broke, not how much was spent.
How is this different from an AI vendor?
There’s no predetermined solution. Vendors sell a product. I find out whether AI is the right answer and, if it is, what kind. Sometimes the answer is not AI.
How long does it take?
The Intervention delivers a full diagnostic in five to seven business days. From there, scope depends on what we find.