A global, multi-division enterprise had AI activity in every corner and no shared view of any of it. We built one measured baseline, a common language for adoption, and the enterprise conditions to scale, then set up a second track to take it into production.
A global enterprise spread across divisions and regions had AI initiatives springing up everywhere: pilots, tools, and pockets of real progress. What it did not have was a shared view of any of it.
No two divisions measured maturity the same way, and no one could say, with evidence, how ready the group really was.
Fragmented, uncoordinated adoption is slow and expensive. Without a common baseline, a shared language, or a safe way to govern AI, every division was likely to keep going its own way, duplicating effort and leaving value on the table.
The group needed one clear, evidence-based picture and the conditions to move together.
We ran a bespoke maturity assessment across the whole group, scoring every division on the same framework to create a measurable baseline that leaders actually agreed with.
Alongside it we shaped policy and the key platform calls through a set of decision briefs, established a common language for adoption, surfaced and promoted early wins to build momentum, and found existing assets that could be reused across regions rather than rebuilt. Not a report on a shelf: the conditions an enterprise needs to adopt AI at scale.
The group gained its first shared, evidence-led view of AI maturity, adopted and signed off by divisional leaders as the common standard. A shared language and a reusable asset base meant divisions stopped working in isolation.
Governance was reframed as an enabler that runs alongside delivery rather than a gate. It all came together into a single strategy that anchored the case for investment.
We built for independence: the assessment, the language, the governance approach and the reusable assets all live inside the enterprise, owned by its own people. The group can keep scoring, comparing and adopting without depending on us.
Anyone can list what was built. What matters to a buyer is the judgement: what we chose, what we rejected, and why.
With the conditions for adoption in place, the second track builds a real thing and takes it into production, then measures the value back against the business case.
* Client identity withheld by agreement. Details generalised to protect confidentiality; outcomes are as delivered.
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