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AI governance in practice: managing shadow AI in UK organisations
Last week, we hosted our latest Minds in Motion roundtable in Bristol, bringing together senior leaders from across healthcare, finance, manufacturing, energy and technology to explore a challenge many organisations are facing today: AI governance.
The session saw a fantastic turnout, with the room at full capacity and additional interest beyond available spaces – a clear signal that organisations across the UK are actively trying to understand how to manage AI adoption safely and effectively.
Led by our CEO, Dolo Miah, the session was designed as an open, discussion-led forum rather than a presentation. What followed was an honest, practical
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Embedding AI governance into the enterprise operating model
AI governance cannot sit on the sidelines
As AI adoption accelerates across enterprise environments, many organisations have responded by drafting governance frameworks, publishing internal principles, or forming oversight committees.
These are necessary steps but they are not sufficient.
AI governance does not become effective because it exists in policy form. It becomes effective when it is embedded into the operating model of the organisation - influencing how decisions are made, how systems are built, and how accountability is assigned.
Without that integration, governance remains theoretical while AI becomes operational.
That imbalance introduces risk.
From framework to function
A common pattern
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