AI Consulting / Enterprise AI Adoption
Helping organisations deploy AI at scale — across strategy, architecture, governance, and the change management that makes adoption stick.
Engagement
From readiness to deployment.
AI Readiness Assessment
An honest evaluation of where your organisation sits: data quality, infrastructure, team capability, and cultural readiness. Most AI projects fail because this step is skipped.
Strategy & Prioritisation
Identifying where AI creates genuine value versus where it adds complexity without return. Helping leadership teams make defensible decisions about where to invest and in what order.
Architecture & Governance
Designing the technical architecture and governance framework that makes enterprise AI sustainable — data access, model management, compliance, and auditability built in from the start.
Deployment & Change Management
Moving from pilot to production is the hardest part. I help organisations navigate the organisational and technical challenges that determine whether an AI investment actually delivers.
Approach
The pilot worked. Now what?
Most organisations have run an AI pilot. Fewer have successfully deployed AI in a way that changes how the business operates. The gap between proof-of-concept and production is where most investment disappears.
The questions that determine success are not technical: what problem are we actually solving, who owns it, how do we measure whether it is working, and what happens when it fails. These need answers before any architecture decision is made.
I have consulted for, or held advisory positions at, over 50 companies across enterprise and deep tech. The pattern is consistent: AI adoption succeeds when it is treated as an organisational change, not a technology project.
Common questions I help answer: how much should we budget for AI implementation, how do we evaluate OpenAI versus Anthropic versus open-source models for our use case, and what does a realistic timeline look like.
Work together
Ready to move beyond the pilot?
Whether you are building an AI business case for leadership, scaling a successful experiment, or trying to understand why adoption has stalled — let's talk.