European Data Protection & Privacy Programme Management - DPO Ready - The Training Centre 
Artificial Intelligence is rapidly becoming part of everyday organisational life. It can help us draft documents, analyse information, automate routine tasks, identify patterns, support decision-making and find new ways of delivering services.
But as organisations become increasingly comfortable asking “What can AI do for us?”, another question is becoming equally important:
“How do we make sure we are using it properly?”
That, in essence, is what AI governance is about.
AI governance is the framework through which an organisation makes sure that Artificial Intelligence is used responsibly, safely, legally and effectively.
It brings together the policies, processes, responsibilities and controls that determine how AI can be introduced and used within an organisation.
Importantly, AI governance is not simply about technology.
It encompasses areas such as data protection, information governance, cybersecurity, ethics, risk management, procurement, quality, legal compliance, workforce responsibilities and corporate governance.
A good AI governance framework should therefore help an organisation answer some fairly fundamental questions:
- What AI systems are we using?
- Why are we using them?
- What information are we putting into them?
- What risks do they create?
- Who is responsible for them?
- How do we know their outputs are reliable?
- Where is human oversight required?
- How do we make sure AI is being used fairly and transparently?
- What happens if something goes wrong?
- How do we provide assurance to senior management and the Board?
AI governance is ultimately about ensuring that there is organisational accountability for the use of AI.
One of the challenges with AI is the speed at which it has become accessible.
Historically, introducing a significant new piece of organisational technology would usually involve IT, procurement, contracts, information governance, cybersecurity assessments and formal implementation.
Generative AI has changed that.
An employee can now access an extremely powerful AI system through a web browser or mobile phone within seconds.
That creates enormous opportunities for innovation, but it also means AI can enter an organisation without the organisation necessarily knowing about it.
An employee might use an AI tool to summarise a document, analyse a spreadsheet, prepare correspondence, review applications or help solve a business problem. Their intention may be entirely positive.
But what information has been shared with the system? Where has that information gone? Can the output be trusted? Is the organisation permitted to use the tool? Has confidential or personal information been disclosed?
Without governance, nobody may have asked those questions.
This has led to the emergence of what is sometimes called Shadow AI — employees using AI systems outside formally approved organisational processes.
It is similar to the long-standing problem of “Shadow IT”, but potentially much more significant because of the volume and sensitivity of information that can be entered into generative AI systems.
The instinctive response might be to prohibit AI altogether.
That may actually increase the risk.
Employees who recognise that AI can help them work more efficiently may continue to use it regardless, particularly when the technology is freely available outside the organisation's systems.
Good AI governance therefore should not simply say “No.”
It should help people understand “Yes, provided…”
That means identifying approved technologies, establishing acceptable uses, defining what information can and cannot be entered and providing staff with sufficient training to use AI appropriately.
Governance becomes the guardrail rather than the roadblock.
AI may be new. Our responsibility for protecting information is not.
There is no single AI governance framework that will be appropriate for every organisation.
Governance should be proportionate to the organisation, the technology being used and the risks involved.
This is an important distinction.
Good governance creates the confidence to innovate. Employees can explore new ways of working because they understand the boundaries. Managers can adopt new technology because appropriate controls are in place. Boards can support investment because they have assurance that the risks are understood. And patients, customers, employees and the wider public can have greater confidence that AI is being used with appropriate care and accountability.
The organisations that succeed with AI will not necessarily be those that adopt it fastest. They are more likely to be those that understand how to balance innovation with responsibility.
That is ultimately the value of AI governance: not controlling technology for the sake of control, but creating the conditions in which we can use it confidently, responsibly and well.
A practical approach might include:
John McGlone, a Data Protection & AI Governance specialist, delivers a range of GRC focussed training courses via The Training Centre, the largest UK provider of IAPP training.
Click here for a list of courses from The Training Centre
