AI Governance Operating Model
Define roles, bodies, and decision rights.
DRC helps companies build AI governance systems that clarify ownership, reduce product risk, and support responsible AI launches.
Find AI risks before they become public problems.
Make sure every AI decision has an accountable owner.
Give teams practical guardrails without slowing good work.
DRC turns AI governance into clear decision systems leaders can understand, use, and scale.
Define roles, bodies, and decision rights.
Assess AI risks across impact and likelihood.
Evaluate governance capabilities and gaps.
Govern AI from idea through launch and monitoring.
Make consistent risk-informed decisions.
Heat maps, architecture, timelines, RACI, and maturity models.
Most AI programs fail because nobody owns the hard decisions. This framework defines how AI decisions move through the organization, who owns them, which controls apply, and how leadership knows the system is working.
AI decisions are scattered across product, engineering, legal, privacy, security, and compliance.
Clear ownership, faster approvals, defensible controls, and fewer surprises after launch.
Governance charter, decision rights, review board model, RACI, escalation process, KPIs.
A structured path from discovery to executive decision.
Understand strategy, risk appetite, and AI use cases.
Evaluate risks, controls, and governance maturity.
Build tailored decision systems and operating model.
Define controls, roles, policies, and operating rhythms.
Prioritize work with an executable roadmap.
Give executives a clear readout and next steps.
Schedule a confidential session with DRC to discuss your AI priorities, risk exposure, and governance needs.