Lead enterprise AI transformation
Set product direction, align senior stakeholders, and connect AI ambition to the operating model, data, decisions, and accountability required to deliver it.
Enterprise AI, product & transformation leader
I turn enterprise AI from promising pilots into trusted operations.
For more than a decade, I've led product, data, and digital transformation across Mars, Shell, BP, Citi, and Deloitte. Today, I combine that enterprise experience with hands-on AI architecture and original research to build the verification, observability, and governance that make AI useful in production.
Enterprise product, data, and transformation leadership across
MarsShellBPCitiDeloitteKraft Heinz
5 regionsaligned around enterprise planning at Mars
+45%product engagement at Shell · +5% revenue
+25%decision speed at BP · 20% shorter cycle time
Where I add value
From enterprise ambition to dependable operation.
I work where product direction, transformation, and technical architecture have to become one coherent operating change.
Move AI from pilot to production
Turn a promising demonstration into a trusted operation by designing for workflow integration, ownership, verification, observability, and adoption from the start.
Design trusted AI operating architecture
Shape the identity, permissions, approvals, evidence, and human-control paths that allow agents and AI systems to act safely at enterprise scale.
Selected enterprise work
View all work →Evidence from transformation in practice.
5 regionsaligned around enterprise planning
Aligning global enterprise planning around a product-led operating model
Global enterprise-planning transformation across five regions, with AI-enhanced forecasting embedded into live supply-chain cycles.
Read the case study+45%product engagement · +5% revenue
Turning integrated customer data into measurable marketplace growth
Customer-data integration, segmentation, and offer optimisation that increased engagement and revenue.
Read the case study+25%decision speed · 20% shorter cycle time
Accelerating global supply-chain decisions with AI analytics and process mining
AI-powered planning dashboards, cloud analytics, and order-to-cash process mining that improved decision speed and cycle time.
Read the case studyWhat I’m building
A hands-on proving ground for trusted AI operations.
I’m building and operating a governed multi-agent platform to test the architecture around the model: identity, permissions, approvals, evidence, observability, and independent completion verification.
It is evidence that I can build the systems I write and advise about. Its internal operating measurements are not presented as client adoption or market traction.
Read the Arqera case study →01Promising pilotCapability demonstrated
02Operating architectureIdentity · workflow · permissions
03Evidence & controlVerify · observe · approve
04Trusted operationUseful at production scale
Executive Briefings
All briefings →The research, translated into decisions.
The Constraint Is Never the Model
Why buying a smarter AI won't transform your enterprise — and what actually will.
Read the briefing →Why Enterprise AI Stalls at the Pilot
The demo dazzles; the rollout dies. A short diagnostic for leaders.
Read the briefing →Featured research
All research →Original evidence on how AI scales.
The AI Economics of Scale
How autonomous production collapses while verification, observability, and trust do not.
Conclusion: AI collapses the cost of producing work, but verification, observability, and trust do not collapse with it. Those non-production costs place a hard bound on how far model capability alone can scale enterprise value.
Read →PDF ↓