Part 3 of the Corporate Assist Data and AI Governance Series
Effective AI governance requires more than approving and publishing a policy.
An AI policy can establish what is permitted, identify prohibited activities and set expectations for confidentiality, accuracy, transparency and human review. However, the existence of the policy does not demonstrate that employees understand it, responsibilities are clear or the required controls operate in practice.
Moving from policy approval to implementation
A policy establishes the organisation's intended position.
For example, it may state that employees must not enter confidential information into an unapproved AI system. In practice, the organisation also needs to define which systems are approved, explain what constitutes confidential information, provide a process for requesting new tools, and monitor whether the restriction is followed.
Without these arrangements, the policy may be clear but difficult to apply consistently.
Using the AI inventory
The organisation first needs to understand which AI systems and functions it uses.
The previous article in this series, AI Inventory: Do You Know Where AI Is Being Used Across Your Organisation?, explains how this information can be gathered.
The organisation can then review the completed inventory against the policy. For each material system, the organisation should be able to establish which policy requirements apply, who is responsible, what approvals have been obtained, and whether any gaps or exceptions remain.
This provides more reliable assurance than simply asking whether the organisation has an AI policy.
Making use of existing controls
An established organisation is likely to have existing controls that support aspects of AI governance.
These may include supplier due diligence, data protection impact assessments, information classification rules, access controls, change approval, employee training, incident reporting and compliance monitoring.
The objective is not to create duplicate processes merely because AI is involved. The organisation needs to establish whether existing controls address the particular AI use and whether they need to be adapted.
For example, a supplier due diligence process may already exist but may not ask whether a product contains embedded AI, how organisational information is used or how material system changes will be communicated.
Mapping policy requirements to controls
A policy-to-control map can show how each key requirement is implemented.
The responsible owner
The relevant process or control
Who operates the control
What evidence it produces
How it is monitored
What happens if it does not operate
A requirement for human review of AI-generated customer communications could, for example, be supported by written guidance, an approval stage and retained evidence of the review.
This is not about producing documents for their own sake. It is about demonstrating how an important policy requirement operates in practice.
Bringing different functions together
Implementing AI policy may require input from Legal, Compliance, Data Protection, Information Security, Procurement, Risk, and operational teams.
Each function may complete a different part of the work. The organisation also needs to understand how those contributions fit together.
Responsibility should be clear for approving systems, maintaining the AI inventory, obtaining supplier assurance, monitoring compliance and responding to incidents. The organisation should also record unresolved questions and matters requiring further specialist advice.
Evidence of implementation
The evidence required should reflect the nature and significance of the AI use.
It may include approval records, impact assessments, supplier information, employee guidance, training records, evidence of human review, monitoring results and incident records.
A low-impact administrative tool would not normally require the same evidence as a system affecting recruitment, customer treatment or a regulated decision. The important point is that the organisation can support the assurance it provides.
AI literacy in practice
Employees cannot follow an AI policy unless they understand what it means for their work.
A general awareness session may be sufficient for some employees. Others need more specific guidance because of the systems they use or the effect of their decisions.
The organisation should determine what different groups need to understand, provide appropriate guidance and retain evidence that this has happened.
The objective is not simply to record training completion. It is to support appropriate and informed use of AI.
Monitoring and review
AI systems can change after approval. Suppliers may add new functions, the organisation may expand the original use, or employees may begin relying more heavily on the output.
Periodic review should therefore consider whether the inventory remains current, the system or purpose has changed, ownership remains clear, and the controls continue to operate. The review should also identify incidents, exceptions and outstanding actions.
Supporting an AI policy implementation project
Your internal specialists may already understand the relevant legal, data protection, security and risk requirements. The capacity issue often arises when those contributions need to be brought together and converted into an implementation plan.
Corporate Assist can provide additional compliance project support by coordinating contributions, mapping requirements to controls, maintaining evidence and action records and preparing progress reports.
If you need additional capacity to support a defined governance or compliance project, find out more about our Corporate Project Support or get in touch to discuss your requirements.
The next article in the Data and AI Governance Series is the EU AI Act 2026: Practical Governance for UK Organisations which covers whether additional European requirements may apply.
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