Your AI is in production. Who operates it?
Deploying an agent takes two weeks. Operating one takes an inventory, an owner, a support group and a fallback when it fails.
Deployed is not the same as Operated
Most mid-sized companies have more AI running than anyone can list. A copilot licence here, an automation a business team built themselves, a vendor feature switched on inside a platform you already pay for. Every other production service has an owner, a support group, a runbook and an escalation path. These went live without any of it.
That holds until something breaks. Then:
What do we actually have running? Not the pilots — the systems in live processes today.
Who takes the ticket? Not who built it. Who picks it up on a Monday morning.
What happens to the customer meanwhile? A fallback to a human, or does the process stop?
Can we show any of this to an auditor? You can't evidence AI Act compliance for systems you can't name.
The last question creates the deadline. The first three cost you money, and they land on IT.
Our Services
Helping you embed AI operations & governance into every stage of your AI lifecycle.
AI Operations
Make every AI system owned, supportable and accountable.
AI Governance
Establish clear accountability, roles and compliance for AI management.
GOVERNING ARTIFICIAL INTELLIGENCE: A Handbook for Leaders and Boards
Governing Artificial Intelligence: A Handbook for Leaders and Boards explores this growing gap between technological capability and organisational responsibility.
Written for executives, board members, risk professionals, and managers, the book does not assume a technical background. Instead, it focuses on the questions leaders actually face:
Where is AI already influencing decisions in our organisation?
Who is accountable when automated systems shape outcomes?
How do governance models designed for human decision-making adapt to systems that learn from data?
What structures, oversight mechanisms, and leadership responsibilities are needed to govern AI responsibly?
Rather than focusing on algorithms or coding, the book examines AI through the lens of decision-making, accountability, and governance.
