About ThinkCapital
Advancing the evidence base for responsible AI governance in government and commercial business. Accountability follows ambition.
Why ThinkCapital Exists
Government agencies across federal, state, and local levels are deploying artificial intelligence at an accelerating pace. Mandates, executive orders, and OMB guidance have established frameworks for responsible AI adoption. Yet a critical gap persists: the measurement infrastructure needed to know whether AI is actually working. Is AI delivering better decisions, improving mission outcomes, and maintaining meaningful accountability?
Governance policies without measurement mechanisms are aspirational documents. ThinkCapital exists to close this gap.
To develop and disseminate rigorous, evidence-based frameworks for measuring, governing, and advancing artificial intelligence in government contexts. We enable agencies to move from policy compliance to genuine accountability.
Core Commitments
We believe that governance without measurement is aspiration without accountability. Every framework we develop is grounded in measurable criteria and empirical evidence.
Commercial AI governance frameworks often don't translate directly to government contexts. We focus on the unique constraints, mandates, and mission requirements of public sector organizations.
Research that stays in journals doesn't change practice. We design our work to produce tools, frameworks, and guidance that CIOs, program managers, and policy makers can actually use.
We approach AI governance as a genuine empirical problem, not an ideological one. We follow evidence where it leads, without regard to prevailing assumptions.
Scope
ThinkCapital's primary focus is government agencies: federal, state, and local. We support agencies and the contractors, integrators, and advisory firms that serve them. However, our research on AI measurement, adoption thresholds, and organizational readiness is broadly applicable. We welcome engagement from researchers, think tanks, and private-sector organizations grappling with the same questions in adjacent contexts.
