Most AI programs can’t prove adoption happened. Our working paper proposes an open method for measuring it — and we run the build and change program that moves the number.
For leaders in regulated and technology-heavy enterprises being asked whether the AI spend worked.
Polywise Partners is an AI advisory and consulting firm dedicated to helping organizations capture the full economic value of AI before their competitors do. We operate at the intersection of enterprise strategy and technical execution — a pairing that most advisory firms cannot credibly offer.
Our engagements are structured to prove value quickly and build lasting capability. We don't produce strategy decks that require a second firm to implement. We design and build working systems, test them with your team, and transfer the keys with the governance and training to sustain what we've built.
Our firm brings together deep vertical expertise in financial services, healthcare, and enterprise technology, supported by twenty-five years of running enterprise programs, fourteen of them in healthcare and financial services.
Across every engagement, we bring the same combination of strategic rigor, technical depth, and executive access that distinguishes a delivery partner from a traditional advisor.
Every engagement is scoped to deliver a tangible result in a defined window — no open-ended engagements, no scope creep, no dependency on us to function.
Polywise concentrates its practice in verticals where AI transformation is most complex, most regulated, and most consequential.
From global banks to regional credit unions, Polywise understands the intersection of AI capability and regulatory constraint. Our principal has led governance of enterprise transformation programs inside a regulated bank and managed financial-services enterprise relationships at Microsoft through the first waves of cloud and AI adoption. Relationships across wealth-management, brokerage, retirement-and-benefits, and financial-technology firms.
Health systems, payers, and healthcare technology companies navigating HIPAA and the governance of AI in regulated workflows. Our principal led end-to-end scalability and performance testing across 10 interdependent systems for a top-3 US managed-care provider ahead of an ACA-driven jump in claim volume, and later provided enterprise-architecture oversight of a national health insurer's claims-mainframe modernization.
Mid-market and enterprise technology companies building or deploying AI capabilities at scale. AI-first product development program management, vendor governance at scale, and the stakeholder management required to move from pilot to production. Our principal's delivery history spans the launch of Amazon's Appstore for Android, program management at Hulu, and an AI-first program office at Trilogy.
Damon has spent twenty-five years running enterprise programs — as the builder, the buyer, and the advisor.
He has sat in the buyer's seat, as an SVP at City National Bank leading governance of the transformation programs its in-house transformation group delivered across the bank. He has carried the vendor's side, leading financial-services enterprise relationships at Microsoft through the first waves of cloud and AI adoption. And he has run delivery at scale — standing up an AI-first program office at Trilogy, advising performance-improvement engagements at Alvarez & Marsal, and, earlier, serving as the founding and sole technical program manager of Amazon's Appstore for Android, from concept through launch.
Polywise's approach is grounded in NANTE™, the adoption-measurement method Damon proposed in Adoption Telemetry (2026), a working paper — five computable stages for reading enterprise AI adoption directly from production signals. He builds on that research hands-on, in Microsoft Copilot Studio, the Claude API, and Google Gemini. An open measurement method, Prosci-certified change management, and working fluency in the platforms themselves: that combination is the foundation of every Polywise engagement.
Relationships built across Microsoft, Amazon, Hulu, City National Bank, Alvarez & Marsal, and the Princeton alumni community.
If you're moving AI from pilot to production as a program, not a demo, the right conversation starts here. We respond within one business day.