Engagements typically begin with a paid diagnostic or board briefing. Company-level sprints and portfolio-level scans are scoped based on complexity, stakeholder groups, and desired outcomes.
For: PE-backed companies, boards, and operating partners moving beyond pilots.
A 30–45 day engagement that turns AI activity into governed operating leverage — value map, delegation model, and 90-day roadmap.
Explore the Sprint →For: Leadership teams that need a fast, focused read before a larger commitment.
A focused assessment of where AI can create value, which workflows are ready for delegation, and what governance gaps need attention.
Book Diagnostic →For: Boards, investment committees, and leadership teams.
A 60–90 minute executive briefing that gives directors a practical model for AI oversight and value creation.
Request Board Briefing →For: PE firms and operating partners.
A portfolio-wide assessment of where AI can create value and where governance maturity is lagging across companies.
Discuss a Portfolio Scan →For: Companies redesigning work and decision-making around AI.
Focused redesign of workflows, supervision, and accountability so AI adoption becomes measurable and repeatable.
Explore this practice →For: Leadership teams executing on governance over time.
A monthly retained relationship supporting governance design, operating model execution, board readiness, and value creation.
Discuss an advisor retainer →For: Companies needing senior product and AI leadership without a full-time hire.
Embedded operating leadership with real authority across a defined transition or inflection point.
Explore this practice →When the governance architecture is in place, your board can approve AI bets with real confidence — because the accountability structures, decision rights, and risk tiers are already working, not being built after something breaks. Most boards aren't there yet: they're approving investments without a clear model for who owns the outcomes or what level of oversight each initiative actually requires.
I help PE boards and portfolio company leadership teams build the governance architecture that makes AI a durable asset, not an audit risk. This work is grounded in the frameworks I developed across 25+ years of AI and product leadership — and published in The AI-Native Organization.
Board-level AI governance policy and decision rights framework
AI Readiness Index across leadership, data, process, risk, and board literacy
Trust tier classification for every AI initiative in your portfolio
Board reporting template for AI investment decisions and ROI measurement
90-day governance roadmap with clear ownership at each level
Most AI governance work runs 60–120 days for the initial framework, followed by an optional retainer for ongoing board advisory.
I've managed a $1.2B P&L at CDW, directed product strategy at Microsoft for Defense and Intelligence customers, and built and exited a company. When I embed with a PE-backed portfolio company, I'm not an advisor with a framework — I'm an operator with scar tissue.
Operating partnership engagements are structured around a specific value creation mandate. I work at the CPO, SVP, or GM level, typically with authority to hire, build, and make product and go-to-market decisions that move the thesis forward.
Leadership infrastructure: roles, accountabilities, decision rights in first 60 days
Operating cadence design: the rhythm of reviews, reporting, and accountability forums
Product and platform strategy aligned to the investment thesis
AI integration and operating model redesign — not bolt-ons to legacy org charts
Exit readiness: building the bench and operational story 18 months before you need it
Engagements are typically 6–18 months. I work at the senior leadership level with real authority — not as an external consultant submitting decks.
Sometimes a company is between senior leaders. Sometimes the business is moving too fast to wait for a full-time hire. Sometimes the board needs someone with the title and authority of a CPO or SVP but not the overhead of a full seat.
As a Fractional CPO, I step in with real operating authority — running the product and technology organization, setting direction, and building the team — while working on a timeline that's structured around your actual need, not a permanent hire.
Bridge between departing CPO/CTO and permanent hire — keep momentum without losing ground
Scaling inflection: company is outgrowing its current product organization structure
M&A integration: acquired company needs senior product/tech leadership immediately
AI transformation: company needs a leader who can set the AI agenda and deliver it — not just advise on it
Board accountability: investors need a senior operator who reports directly and tells the truth
Engagements typically run 90 days to 18 months, with a defined scope and clear success criteria established at the outset.
Boards are approving AI investments, signing off on operating model changes, and overseeing leadership transitions — often without a director who has actually done any of those things at scale. The gap isn't intent. It's the absence of someone who can evaluate an AI thesis with the same rigor they bring to a financial model, and challenge an operating assumption before it becomes a missed target.
I bring the AI governance, operating model, and P&L experience that most boards are missing. Not as a subject-matter expert brought in for a single session — as a director with skin in the outcome. The practical difference: the board can approve bolder AI bets — and hold management accountable for them — because someone at the table has actually done it.
Independent evaluation of AI investment theses — governance readiness, execution risk, and value creation probability
Operating model challenge: the ability to stress-test whether the management team's plan will actually work
Technology-to-business translation — bridging the gap between what the CTO is reporting and what the board needs to decide
AI governance policy ownership at the board level, including decision rights, risk tiers, and accountability mapping
Pre-exit operating narrative: building the AI and product story that holds up in diligence
Board relationships are typically ongoing. I take on a small number at a time to maintain genuine engagement — not board seat collection.
30 minutes. You describe the situation — I tell you what I see, whether I can help, and what kind of engagement makes sense. No pitch. If it's not a fit, I'll say so directly.
If the discovery call confirms fit, we have a deeper conversation about scope, timeline, authority, and success criteria. This is where we agree on what we're actually solving.
No long ramp. No shadow period. I start with a rapid assessment in the first two weeks, then move into execution. The board or sponsor gets a direct read at day 30.
It gives leadership a clear view of where AI can create value, which workflows are ready for delegation, and what to prioritize over the next 90 days. No pitch — a direct read on fit.