Most AI consultants come from one of two worlds: they're technologists who learned business, or they're strategists who learned to talk about AI.
I come from both.
I hold a PhD in Industrial-Organizational Psychology — the science of how people perform at work. I spent a decade building machine learning products at some of the most demanding environments in AI: leading NLP research at a major bank's AI lab, building ML systems at Pinterest, developing LLM-powered coaching products at BetterUp. I hold a patent in predictive assessment.
Today, I help mid-market enterprises in regulated industries figure out where AI will drive measurable returns — and where it won't. I don't sell platforms. I don't resell vendor solutions. I assess your workflows, interview your people, and give you an honest view of what's possible, what's premature, and what to do first.
The organizations I work with don't need a Big 4 engagement with 40 consultants and a 200-page deck. They need a senior advisor who understands the technology deeply enough to call BS on vendor pitches, and understands people deeply enough to know why adoption stalls.
I didn't learn AI from a slide deck. I led ML teams, shipped production models, and built the systems that enterprises now adopt. When I assess your AI readiness, I'm evaluating it against what I know works in practice — not what looks good in a proposal.
Most consultants have an incentive to find AI opportunities everywhere. I don't. My credibility is built on honest assessment. If a workflow doesn't benefit from AI, I'll say so — and save you six months and six figures.
Every engagement I deliver is designed to leave your organization stronger and self-sufficient. I train your people, document the methodology, and transfer the knowledge. When the engagement ends, you don't need me to maintain what we built.