AI governance for the AI you build or buy.
AI brings real value and new risks: bias, privacy, transparency and regulation. We help organizations adopt AI with a structured governance framework built for the current regulatory environment.
What we do
Service 2 of 6 ยท Responsible AI
AI risk assessments
Identify and quantify AI-specific risks: bias, hallucination, data leakage, model drift and shadow AI usage.
Governance framework design
Custom governance frameworks aligned to NIST AI RMF, ISO/IEC 42001, EU AI Act, and OECD AI Principles.
AI maturity evaluations
Benchmark your current AI governance practices against peers and define a roadmap to maturity.
Model inventory & lifecycle
Establish centralized model registries, approval workflows, and ongoing lifecycle oversight.
Bias, fairness & explainability
Technical reviews of training data, model outputs, and decision logic with mitigation recommendations.
AI policy development
Acceptable use policies, employee guidelines, procurement standards, and ethics charters.
Data governance for AI
Training data lineage, consent management, quality controls, and privacy engineering for AI pipelines.
Third-party AI risk
Vendor AI due diligence, contract review, and ongoing monitoring of external AI systems.
Executive & board advisory
Strategic AI governance briefings, board reporting structures, and C-suite enablement workshops.
From principles to practice
Inventory
Discover every AI system in use, including shadow AI, embedded vendor features, and research projects.
Classify
Risk-tier each system using EU AI Act categories and custom business criteria for prioritization.
Govern
Deploy policies, controls, and oversight mechanisms proportional to each system's risk classification.
Monitor
Continuous monitoring for model drift, bias, new regulations, and emerging AI risks.
Regulations and standards we work to
The regulatory landscape is evolving rapidly. Our frameworks are designed for flexibility, satisfying current requirements and adapting quickly to emerging ones.
Why it matters now
- Regulatory exposure
- EU AI Act fines can reach 7% of global revenue. US state laws are proliferating. Inaction is no longer viable.
- Reputational risk
- AI failures make headlines. Bias incidents, hallucinations, and data leaks erode trust fast.
- Shadow AI proliferation
- Employees use AI tools your security team does not know about, exposing sensitive data daily.
- Customer expectations
- Enterprise buyers increasingly require AI governance attestations before they'll sign.
- Competitive differentiation
- Demonstrable responsible-AI practices open doors in regulated industries and high-trust markets.
- Innovation enablement
- Good governance accelerates safe AI adoption rather than blocking it.
AI Governance: Common Questions
What is AI governance, in practice?
It is the set of policies, risk assessments, and oversight controls that ensure the AI systems your organization builds or uses are transparent, fair, and compliant, rather than a single document you file away.
Do we need ISO 42001 if we already have a general risk framework?
A general framework rarely covers AI-specific risks like model bias, data provenance, or explainability. ISO/IEC 42001, the EU AI Act, and NIST AI RMF add controls purpose-built for AI systems.
We use third-party AI tools, not our own models. Does governance still apply?
Yes. Vendor and third-party AI use still carries risk and, under frameworks like the EU AI Act, still carries obligations. We assess your AI supply chain, not just systems you built in-house.
How long does an AI governance engagement take?
An initial AI risk assessment and policy baseline typically takes a few weeks. A full governance framework aligned to ISO 42001 generally falls in our standard 10 to 16 week delivery window.
Let's Design Your AI Governance Program.
A complimentary discovery session will map your AI estate and recommend priority actions.