AI Governance
The policies, roles, controls and records an organisation uses to make sure AI systems are built and operated responsibly, lawfully and with accountability.
Definition
AI governance is the management layer above individual AI projects. It answers organisational questions: which AI systems do we run, who is accountable for each, what risks do they carry, what may they be used for, how are they tested, and what records show all of this? It draws on existing disciplines such as data protection, information security and model risk management, and adds the parts specific to AI: bias, transparency, human oversight and the behaviour of probabilistic systems.
In practice it produces an AI inventory, a risk classification scheme, an acceptable-use policy, review gates in the delivery process, and monitoring and incident procedures once systems are live. Standards and laws give it structure: ISO/IEC 42001 defines an AI management system, the NIST AI Risk Management Framework organises risk work, and the EU AI Act sets legal duties by risk level.
Example: a retailer's inventory lists eleven AI uses, from a support bot to a credit-scoring vendor model. Two are classified high-risk and get documented oversight, testing and a human-review step. The rest follow a lighter policy. Every system has an owner and a review date.
Why it matters for your business
- Regulation now attaches obligations and penalties to how AI is used, not only to how data is stored.
- Customers and partners increasingly ask for evidence of AI controls in procurement.
- Clear ownership prevents the quiet spread of unreviewed AI tools across teams.
- Done proportionately, it speeds projects up: teams know the rules before they build.
How Teksmobile uses it
Our AI governance service sets up the inventory, policies and review gates described above, sized to the organisation. For companies in scope of EU law we add EU AI Act readiness, and for those seeking certification we align the programme with ISO/IEC 42001.
Related terms
Part of the Teksmobile AI Glossary. For longer reads, see our guides.
Frequently asked questions
Is AI governance only for large companies?
No. A ten-person company using an LLM on customer data needs an owner, a policy, a risk assessment and a record of what the system does. The scale changes; the elements do not.
Which frameworks should we follow?
ISO/IEC 42001 for a management system, the NIST AI Risk Management Framework for structuring risk work, and the EU AI Act where it applies. They overlap heavily, so one set of controls can serve all three.
What is the minimum viable governance?
An inventory of AI systems, a named owner for each, a risk classification, a short acceptable-use policy and a review step before anything new reaches customers.