Strategy · AI Governance
AI governance done badly is either a blocker or a fig leaf. Done well, it is what lets your organisation move fast on AI — because accountability, risk classification and regulatory alignment are settled once, at the framework level, instead of renegotiated for every initiative.
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Why AI Governance
Regulators, auditors, customers and your own board are all asking the same question in different words: who is accountable for what your AI does? Organisations without a clear answer either freeze — every AI decision escalated and relitigated — or drift into ungoverned adoption that surfaces as an incident.
We design governance proportionate to your risk and your sector: policy and principles people can actually follow, an accountability model mapped to your real organisation, risk classification that sorts the trivial from the consequential, and alignment to the regulation that applies to you. Designed at the strategy stage; enforced through our AI Assurance service in operation.
Controls scale with risk — lightweight for low-stakes automation, rigorous for consequential decisions about people and money.
Accountability assigned to roles that exist, through forums that already meet — not a parallel bureaucracy.
Framework aligned to the regulatory landscape that applies to you, including EU AI Act obligations, UK regulatory guidance and data protection law.
Every control designed with the evidence it will produce, so ongoing assurance and audit are routine rather than a scramble.
We present the same work in the language each stakeholder needs — commercial for the boardroom, plan-ready for the programme, technical for the architecture.
Designed together so policy, people and process reinforce each other.
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Every engagement is scoped around a defined set of deliverables agreed at the outset.
AI and analytics are only as good as the enterprise data beneath them. That data is our home ground.
A typical framework engagement runs six to ten weeks, then hands into operation.
Inventory current AI use — sanctioned and shadow — map existing policies and forums, and identify the regulatory obligations that apply.
Policy, accountability model, risk tiers and lifecycle controls designed with your stakeholders, proportionate to your risk profile.
Forums stood up, roles briefed, templates in use, first AI initiatives taken through the new process to prove it works.
Handover to business-as-usual — with our AI Assurance service available for ongoing monitoring, testing and compliance evidence.
AI Governance connects naturally with these services across our Data & AI portfolio.
