Inventory & Framework
- Full AI system catalog
- M-25-21 risk classification
- Six-pillar Responsible AI framework
AI GOVERNANCE & TRUST
Policies, controls, and testing frameworks that keep AI fair, transparent, secure, and defensible across audits, compliance, and public scrutiny.
Governance failures are the fastest path to lost public trust, stalled AI programs, and regulatory action.
AI that harms citizens, discriminates in benefits, or exposes sensitive data damages the mission far more than any short-term efficiency could justify. Federal, state, and sector-specific regulations are converging, and the clock is running. The numbers show what is required and how little time remains.
April 2026
OMB M-25-21 compliance deadline
6
Responsible AI pillars in every framework
7
Required risk practices for high-impact AI
80%
Federal threshold for disparate impact testing
Governance follows a five-phase journey drawn from our Responsible AI practice:
Catalogs AI systems, classifies risk, and maps ownership, data sources, and downstream decisions.
Builds the Responsible AI framework, governance structure, policies, and intake processes aligned to NIST AI RMF.
Validates fairness, security, explainability, and regulatory alignment while generating audit-ready evidence and governance documentation.
Continuously tracks drift, fairness, performance, and data quality with alerts, reviews, and governance oversight.
A defensible Responsible AI program built for regulators, auditors, and the public, from inventory to continuous monitoring.
Fairness, transparency, and human oversight are what allow public-sector AI to operate responsibly.
Strong governance goes beyond regulations to create durable, future-ready AI programs.
Citizens deserve clear reasoning behind AI-driven decisions affecting benefits, eligibility, or enforcement.
Responsible AI requires continuous monitoring as models, data, and regulations evolve.
Fairness, transparency, and human oversight are what allow public-sector AI to operate responsibly.
Strong governance goes beyond regulations to create durable, future-ready AI programs.
Citizens deserve clear reasoning behind AI-driven decisions affecting benefits, eligibility, or enforcement.
Responsible AI requires continuous monitoring as models, data, and regulations evolve.
The April 2026 OMB M-25-21 deadline is approaching. Start now.