What AI governance means, in plain words
AI governance answers four questions: which AI are we using, who is responsible, what could go wrong, and is it paying off? If you can answer those quickly and with evidence, you have governance. If the answers live in people's heads, you don't.
Good governance is not a brake. It is what lets you move from scattered pilots to AI that runs in the business, because the board, your customers and your insurers can see it is under control.
The five parts of the framework
1. Ownership
One named senior owner for AI on the leadership team, and a board member who receives a short report each quarter. Without an owner, every other part slowly stops.
2. Policy
An AI acceptable use policy for employees: approved tools, data rules, human review and how to report mistakes.
3. Register
One spreadsheet that lists every AI tool and use case: what it does, which data it touches, who owns it, its risk tier and its status. This is the single most useful governance document you will have.
4. Risk checks
A short assessment before anything new goes live, scaled to the risk tier. Check data protection, accuracy, bias, security, supplier terms and what happens when it gets something wrong.
5. Reporting
A one-page quarterly report to the board: what is live, what it delivered against its business case, incidents and lessons, and decisions needed. This is where AI earns its budget.
Use risk tiers so effort matches risk
Most AI use is low risk. Treat it that way, and save the heavy checks for the few uses that matter.
| Tier | Examples | Checks before go-live |
|---|---|---|
| Low | Drafting internal emails, summarising public documents, brainstorming | Approved tool, policy followed, owner named |
| Medium | Customer-facing content, internal data analysis, chat assistants on your own documents | Plus data protection check, accuracy testing, human review step, supplier terms checked |
| High | Decisions about people (hiring, credit, health), automated actions on customer accounts, regulated advice | Plus full impact assessment, bias testing, board sign-off, monitoring and a fallback plan |
A 90-day plan to set it up
- Days 1 to 30: own it and set the rules. Name the owner, agree board oversight, publish the acceptable use policy and choose approved tools.
- Days 31 to 60: see everything. Build the register from a staff survey and supplier review. Assign risk tiers and run checks on anything medium or high.
- Days 61 to 90: prove it. Set a business case and measure for each live use case, send the first quarterly board report and book the next review.
Tip: start the register with the tools people already use, not the ones you plan to buy. That is where the real risk sits today.
Rules to build in, by market
- UK: UK GDPR and the Data Protection Act 2018, the ICO's guidance on AI and data protection, and sector regulators such as the FCA and PRA for financial firms.
- Saudi Arabia: the Personal Data Protection Law and SDAIA's AI ethics principles. SDAIA has consulted on draft responsible AI rules that would add binding requirements, so track the final version.
- UAE: the federal Personal Data Protection Law, the UAE Charter for the Development and Use of AI, and the DIFC and ADGM data protection rules where they apply.
- EU customers: the EU AI Act can reach firms anywhere whose AI is used in the EU.
- Anywhere else: start with your country's data protection law and the international standards below.
- Standards: ISO/IEC 42001 and the NIST AI Risk Management Framework are useful references, even if you never certify.
The AI Governance Handbook covers each of these in detail, in UK, GCC and Global editions.
Questions about AI governance
What is an AI governance framework?
It is the way your business decides which AI to use, who is responsible for it, how risks are checked and how results are reported. In a mid-sized business it fits on a few pages and one spreadsheet.
Do mid-sized businesses really need AI governance?
Yes, and it does not need to be heavy. Investors, insurers, large customers and regulators increasingly ask how AI is controlled. A light framework answers those questions and makes it safer to move faster.
Who should own AI governance?
One senior owner on the leadership team, with board oversight. Many businesses use a fractional Chief AI Officer for this until AI is big enough to justify a full-time role.
How long does it take to set up?
Around 90 days for the first version: ownership and policy in the first month, the register and risk checks in the second, and reporting in the third.
Is there a standard we can follow?
ISO/IEC 42001 is the international standard for AI management systems, and the NIST AI Risk Management Framework is widely used. Most mid-sized businesses borrow from these rather than certify against them.
This guide is general information, not legal advice. Laws, draft rules and regulator guidance change, so check the current position for your business and sector.