£30M in new ARR.
Deployment lead time cut in half.
A governed AI operating model — a risk-scoring framework, a secure FedRAMP/IL5 enclave, and a dedicated innovation engine — turned scattered AI experiments into a funded, revenue-generating programme endorsed by the executive team.
projected
deployment lead time
unvetted AI tools
brought under governance
Client
A global enterprise leader in risk intelligence and organisational resilience, serving Fortune 500 companies.
Goal
Design and execute the company’s first enterprise-wide AI strategy, moving from ad-hoc, siloed AI experiments to a governed, secure, revenue-generating programme with a target of £30M in new ARR.
AI was everywhere in the business. Governance was nowhere.
Nine business units were already using AI tools of their own choosing, unvetted and ungoverned, creating real compliance exposure under frameworks such as the EU AI Act and NIST. There was no central strategy, no risk-scoring process, and no consistent way to measure or realise ROI from any of it.
Promising ideas had nowhere to go. Without a repeatable, cross-functional process for moving a concept from idea to a funded, technically vetted pilot, high-potential work stayed trapped in silos, wasting R&D and costing missed market opportunities. The innovation pipeline was slow, there was no secure, compliant environment to build in, and deployment lead time was the single biggest blocker standing between a good idea and a commercial product.
Three constraints were non-negotiable:
- Nine business units running unvetted AI tools with no central governance
- No repeatable process from idea to funded, technically vetted pilot
- No secure, compliant environment to build and deploy AI products in
One governance model, one secure enclave, one innovation engine.
Our Fractional Head of AI started with governance: establishing and chairing an enterprise-wide AI Governance Committee, then designing a human-centred guardrails framework and a quantitative risk-scoring model. Rolled out across all nine business units, it gave the company transparent approval flows and cut unvetted tool use by 40%.
Governance wasn’t a brake on innovation here. It was the thing that let ideas move fast enough to become revenue.
To turn ideas into products, they founded and led the Innovation Discovery Group, an internal innovation engine running a monthly design-sprint framework that put product, engineering and business-unit leaders in the same room to identify, prototype and fast-track the AI opportunities worth funding.
To remove the technical bottleneck, they architected and led the build of a secure FedRAMP/IL5 “safe AI enclave” on AWS and Azure, paired with a new data-classification programme. That infrastructure cut deployment lead time in half and became the foundation every subsequent AI product was built on.
From siloed experiments to a £30M roadmap.
Governance, secure infrastructure and a dedicated innovation engine turned dispersed experimentation into a single, repeatable model for building AI products securely and fast. What started as siloed, unvetted experiments is now a three-year strategy endorsed by the executive team, on track to deliver £30M in new ARR.
* Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.
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*Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.