Built on doing it, not just advising on it.

Why Human–AI Systems exists

Most organisations are at the early stages of AI adoption. They're running pilots. Some of them are working. Fewer are changing how work actually happens at scale.

The gap isn't technology. Organisations have access to excellent tools. The gap is operational adoption — the hard work of redesigning workflows, building governance that is rigorous without being obstructive, and developing the leadership capability to manage teams where AI is part of how work gets done.

Human–AI Systems was founded to help organisations close that gap. The approach is practical and evidence-based, shaped by direct experience of what it takes to move from experimentation to operational adoption — and what goes wrong when organisations try to skip the difficult parts.

Leading it at Verimatrix

At Verimatrix — a publicly listed cybersecurity company — Mike led the company's AI transformation programme. This was not a pilot project or an innovation initiative. It was a programme designed to change how engineering teams actually worked: how they wrote code, reviewed it, managed technical debt, and shipped product.

That meant confronting what most AI transformation programmes avoid: the workflow design questions, the accountability questions, and the governance questions. What happens when AI makes a mistake in production code? Who owns the output? How do you measure productivity when the nature of the work has changed?

The board approval process for the governance framework was, in some ways, the most instructive part. It required translating the operational reality of AI adoption into language that directors could interrogate, challenge and ultimately stand behind. That experience — of making AI governance real at the highest level of a listed company — is directly relevant to any organisation facing similar scrutiny.

Cabinet Member at Cotswold District Council

As a Cabinet Member at Cotswold District Council, Mike held the digital and climate strategy portfolio — including responsibility for the council's approach to AI. He co-authored the council's AI Policy and oversaw the rollout of Microsoft Copilot to around 250 officers and elected members.

AI adoption in local government is different from commercial settings in almost every dimension: the governance environment is more complex, the consequences of getting it wrong are more public, the resource constraints are tighter, and the workforce is more varied in its starting point with technology. None of that makes it slower because people are resistant. It's slower because the design constraints are genuine — and need to be taken seriously.

That combination of commercial and public sector experience is not common. It means the governance instincts developed at Verimatrix translate directly into the scrutiny environment of local government — and vice versa.

Enterprise technology at scale

Before founding Human–AI Systems, Mike spent over two decades in enterprise technology — including a senior leadership role at Cisco, where he held responsibility for a £430M EMEA Public Sector P&L. That background — building and leading large commercial technology organisations across major enterprise and public sector accounts — provides the business context within which AI adoption advice is grounded.

The career has run across enterprise SaaS, cybersecurity, public sector digital, and AI transformation. It is not a background in AI research or software development. It is a background in making technology work inside real organisations — and in understanding what leadership, governance and operational design are required to do that.