Pilots without a path
IDC found that 88% of AI pilots never reach production. The models usually perform; what is absent is the ownership, the controls and the unit economics that would make deployment a defensible decision.
Data, AI and decision systems
Clarity forconsequentialAI and datadecisions.
Most AI programmes stall between a working demo and a system someone will own. The reason is rarely technical — RAND found that the root causes are organisational in over 80% of cases. We work on that gap: the evaluation, the controls, the operating path and the cost model.
Occam Labs engagements since 2016, across healthcare, insurance, entertainment and consumer.
4,000+users on an EMEA healthcare analytics platform
35+technology initiatives under one governance model
20+markets working from shared data definitions
The current reality
The technology moved quickly. The operating questions got harder.
McKinsey reports that only 12% of CEOs see both cost and revenue benefits from AI — despite near-universal adoption. The models work. What is missing is the operating layer around them: who owns the outcome, how it is evaluated and what happens when it is wrong.
Platforms without adoption
Gartner's CxO survey found that only 27% of executives have a comprehensive AI strategy. Without that frame, well-built systems go unused — teams do not adopt tools whose purpose has not been articulated from the top.
Governance without movement
78% of enterprises are unprepared for EU AI Act obligations — not because controls are hard to build, but because most governance frameworks tell teams what they cannot do without showing them what they can.
What we do
Four things we are actually hired to do.
Value and portfolio strategy
We score competing initiatives on expected value, technical risk, dependencies and evidence quality — then turn the result into a sequence that leadership can defend when capacity or priorities shift.
AI and data product delivery
We take one consequential workflow and build it to production: retrieval, agent orchestration, evaluation harness, human review path and the cost model that decides whether it should exist.
Architecture and governance
We design the data contracts, evaluation sets, logging standards and risk tiers that let a team ship a second and third system without renegotiating approval each time.
Adoption and operating models
We redesign the roles, rituals and incentives around the new system, then train the people who will own it after we leave. If adoption depends on a change-comms deck, the design is wrong.
Selected work
Three engagements, described honestly.
A Fortune 500 analytics platform, a Lloyd’s-backed reinsurer’s risk workflow, and CTO portfolio governance across 35+ initiatives. Clients are anonymised; the numbers and the mechanics are not.
Healthcare · Enterprise analytics4,000+ users · 20+ markets
From specialist reporting to 4,000 people making decisions
A Fortune 500 medical devices group had capable analysts in every market and no shared definition of a customer. A governed platform and a self-serve data catalogue grew organic adoption ~80% year on year.
Insurance · Decision intelligenceRegulated, multi-source
Giving underwriters one place to compare a scenario
At a Lloyd’s-backed reinsurer, scenario logic sat in actuarial models, exposure sat in portfolio systems and judgement sat in email. Discovery with underwriters and actuaries produced a single traceable workflow.
Entertainment · Portfolio strategyAdopted in 6 weeks
35+ initiatives, one basis for comparing them
A Fortune 500 gaming and hospitality group ran 35+ concurrent technology initiatives with no common view of risk or return. The CTO and eight senior leaders adopted the resulting model as primary governance within six weeks.
Organisations we have worked with since 2016
CAESARSHOXTONSAMSUNGZIMMER BIOMETUKA
How we work
Make the hard decisions explicit—early.
We put the sponsor, the product lead and the engineers in the same room and force the disagreements out while they are still cheap. On the reinsurance work, running discovery with underwriters and actuaries together surfaced a definitional conflict that would otherwise have shipped.
Photo: Jo Szczepanska / UnsplashLatest thinking
What we think, with the reasoning attached.
AI delivery7 min
The AI pilot is not the product
A demo proves feasibility under conditions you chose. Five decisions stand between that and something an organisation can depend on.
AI governance6 min
Governance that accelerates adoption
Counting completed reviews tells you nothing about whether a system is trusted. Better signals exist, and they change what governance teams build.
Agentic AI8 min
The new economics of agentic AI
An agent has no unit cost until you define a successful outcome. Retries, retrieval and human correction usually dominate the token bill.
AI architecture11 min
Remember me? GenAI long term memory architectures
A language model without memory restarts every conversation from zero. The architectures that close this gap are well understood — the hard part is deciding what a system should forget.
Start a conversation
Bring us the decision you are stuck on.
Tell us what is changing, where the difficulty sits and what a good outcome would look like. We reply within two working days.