Most AI initiatives get approved based on compelling pitches. Then they stall when reality hits. I help you see what's actually executable before you commit.
I work with senior leaders to assess which AI initiatives their organization can actually execute. Not which ones look good in a vendor demo, a consultant's roadmap, or an internal team's pilot.
Presenting research on AI initiative assessment at BIG.AI@MIT 2026.
What I Do
You've seen the pattern. A vendor demo that looked flawless. A consultant's roadmap that made sense on paper. An internal team's pilot that “just needs to scale.” Then reality hits: the data isn't ready, the stakeholders aren't aligned, the governance path is unclear, and momentum dies.
The problem isn't the pitch. The problem is that nobody assessed whether your organization could actually execute what was proposed.
I assess the fit between your AI initiatives and the organizational reality required to execute them. Different initiatives require different stakeholders, different data, different governance paths, and different levels of team readiness. I evaluate each one against its own execution context. Then I tell you what's actually likely to succeed.
What you get:
- A clear verdict on each initiative: greenlight now, pause, or kill
- The specific readiness gaps that would cause each initiative to stall or fail
- A sequenced path forward that matches your ambition to your actual capabilities
- A decision framework you can apply to future opportunities independently
Typical engagements run 2–4 weeks from kickoff to final deliverable.
What I Don't Do
I don't implement.
I assess and recommend. I don't build, deploy, or manage AI systems. This preserves my objectivity. I have no incentive to greenlight work that becomes my next project.
I don't select tools or vendors.
I evaluate whether your organization can execute, not which platform you should buy. But I can tell you whether a vendor's proposal will actually work in your environment before you sign.
I don't evangelize AI.
I may recommend killing initiatives or slowing down. My job is clarity, not enthusiasm.
I don't run transformation programs.
I surface the leadership, adoption, and capability gaps that will determine success. I don't own the organizational change required to close them.
Who This Is For
Senior leaders in regulated or risk-sensitive organizations who are accountable for AI outcomes.
Typically: CDO, CIO, Head of Data, Head of Transformation, VP of Analytics.
Organizations with 500–10,000 employees. Large enough to have real AI investment and governance pressure. Small enough that you need results, not a six-month engagement that ends in a strategy deck.
You're a good fit if:
- You have multiple AI initiatives in flight or under consideration
- You're under pressure to show results but skeptical of the hype
- You want an independent perspective before committing further resources
- You can act on recommendations, or you need clear analysis to make the case internally
You're not a good fit if:
- You're looking for implementation help
- You're in early exploration with no active initiatives
- You want someone to champion AI internally
Experience Snapshot
MIT Sloan MBA. Over fifteen years in financial services. I've led data and AI initiatives at Fidelity, Santander, Edward Jones, John Hancock, and Kessel Run (Air Force). Presenting at BIG.AI@MIT 2026.
I've worked across enterprise platforms, data strategy, and hands-on AI implementation. I've built production RAG systems that actually went live. I know the difference between a demo that impresses and a system that ships. That pattern recognition is what I bring to your portfolio.