AI inventory
Identify AI systems, embedded features, models, vendors, data flows, business owners, users, and intended outcomes.
Govern innovation
Create guardrails without stopping useful experimentation.
AI adoption often spreads through software features, third-party tools, internal automation, and individual employee use before the organization has a complete picture. That creates questions about data handling, accuracy, bias, security, intellectual property, transparency, and accountability.
Launch GRC turns those questions into a practical operating model. The program can align with recognized approaches such as the NIST AI Risk Management Framework and ISO/IEC 42001 while remaining proportionate to your actual AI use and business risk.
AI governance services
Make AI use visible, reviewable, and accountable.
AI risk assessment
Evaluate use cases using consistent criteria for impact, data sensitivity, autonomy, external exposure, and human reliance.
Policies and standards
Define acceptable use, prohibited practices, approval expectations, development requirements, and exception handling.
AI vendor governance
Assess third-party AI providers for security, privacy, data use, performance claims, transparency, and contractual risk.
Human oversight
Establish when people must review, approve, challenge, override, or monitor AI-assisted decisions and outputs.
Monitoring and reporting
Track incidents, exceptions, changes, reviews, testing, and program metrics for leadership and customer assurance.
A risk-based program
Apply more governance where consequences are higher.
Not every AI use case needs the same process. A tiered model lets low-risk productivity uses move quickly while higher-impact systems receive stronger review, documentation, testing, and oversight.
- AI-assisted employment or workforce decisions
- Customer-facing recommendations and outputs
- Processing of confidential or personal data
- Automated security or access decisions
- AI used in healthcare-related workflows
- Model training, fine-tuning, or retrieval with company data
- Generative AI embedded in products and services
AI governance questions
Frequently asked questions
What is AI governance?
AI governance is the system of roles, policies, processes, controls, and evidence used to direct and oversee how an organization develops, buys, deploys, and uses artificial intelligence.
What should an AI governance program include?
A practical program commonly includes an AI inventory, risk classification, acceptable-use rules, review and approval workflows, vendor governance, human oversight, incident handling, monitoring, training, and leadership reporting.
How does AI governance connect to GRC?
AI governance extends existing governance, risk, compliance, privacy, security, vendor, and product processes to address AI-specific uncertainty. Integrating those functions avoids creating an isolated program.
Can a small company implement AI governance?
Yes. A proportionate program can begin with inventory, ownership, a simple risk-tiering method, acceptable-use rules, and review requirements for higher-risk uses, then mature as adoption grows.