AI and data programs that survive contact with a real organization.

Most AI work fails on the organization, not the model. The pilot works, the demo lands, and then nothing reaches production because no one owns the data, the hiring plan doesn't exist, and the roadmap was written for a company that doesn't operate that way.

I come in at the point where a company has already decided AI matters. My job is the unglamorous middle: what gets built first, who builds it, what data has to be fixed before any of it works, and how the whole thing is sequenced so each step pays for the next.

At Monogram Health I was brought in to lead engagement and moved to Head of AI once the transformation was under way, building the AI program, the strategic roadmap, the data transformation, and the hiring plan under the COO and CTO. I've also built the go-to-market plan for Roboto AI, advised Lumetec's founder on investor strategy and fundraising, and led strategy for Meta Materials, an AI-driven nanotech business.

Programs at the scale where coordination is the work. Many workstreams, several regions, a stakeholder list long enough that alignment is a full-time discipline rather than a meeting.

I ran the PMO for a $2B asset transformation at Morgan Stanley spanning the US, Europe, and Asia-Pacific. I led an IT implementation at Maersk across more than fifteen consultants and fifty stakeholders. At Aetna I worked on carving a health-tech subsidiary out into a standalone shared-services IT entity.

I learned this at EY, where I was a Manager and the Nordic Analytics Lead across New York and Copenhagen, and I've been doing it independently since 2018 for clients from seed stage to the Fortune 500.