Embedded Fractional Chief AI Officer
An organization needed one person who could translate customer reality into AI product decisions — and sit at the executive table to make them stick.
Who it's for
You're a CEO or executive team that needs a fractional AI officer who operates across product, engineering, and the market — not just a strategy advisor one layer removed from execution.
Timeline
Ongoing embedded engagement, ramping from customer/product discovery into a standing executive cadence
Format
Embedded fractional role — a direct seat at the executive table plus working sessions with product, engineering, and customer-facing teams
The situation
The engagement started on the ground, in customer success — understanding the product the way customers actually experienced it, across several healthcare and non-healthcare accounts. The difficulty wasn't any single function; it was that useful AI product decisions needed real customer signal, technical reality from engineering, and executive-level context all at once — and most organizations don't have one person who sits across all three.
What I did
I translated what customer success surfaced into concrete AI product requirements, then worked directly with the dev team to understand and enhance features using modern AI technologies. At the same time, I held a direct seat at the executive table — driving engagement decisions, working with the CEO on business development and building credibility in the market for the products and services on offer, and synthesizing strategy and process with the other executive leads. On the roadmap itself, I helped prioritize and define AI product features and worked with engineering to actually build, validate, and test them — and checked that every technology and integration decision met AI security standards before it shipped.
What they walked away with
The organization got a consistent thread from customer reality to shipped product to market-facing credibility — instead of those living in separate functions that had to be reconciled after the fact. Client success and expansion stayed enterprise-focused throughout. Some of this is easy to point to directly — features shipped, security standards enforced, roadmap priorities set; the market credibility built with customers and the CEO's business development is real but, like most relationship-driven work, harder to reduce to a single number.
At a glance
- Works both ends — direct customer/product discovery and a standing seat at the executive table
- AI roadmap prioritization done with engineering, not handed to them — features get built, validated, and tested together
- Tech and integration decisions checked against AI security standards before they ship
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