Digital CX and
AI Transformation
Not three separate practices. One fused capability, applied across marketing, sales and service.
Not three separate practices. One fused capability, applied across marketing, sales and service.
How I Think About This
Most businesses know they need to do something with AI. The ones that struggle are not short of ambition or budget. They are missing the end-to-end picture: the right technology, the right operating model, and a clear understanding of how the transformation actually works in practice. Those three things have to move together. Doing one without the others is how you get a pilot that never scales.
My work sits at the intersection of three areas that are often treated as separate problems but are really one. AI transformation needs the right data to work. Customer data needs the right digital channels to become useful. And digital experience needs AI to be relevant and efficient at scale. When those three things connect, that is when the results show up.
Most organisations approach AI as a technology problem. It is not. It is an operating model problem. The question is not which AI tools to buy. It is how your marketing, sales and service teams actually work differently because of AI, and what it takes to get there: the workflows, the governance, the data foundations, and the change management that makes adoption stick rather than stall.
Where I come in is end-to-end. I help businesses define where AI creates real value across customer functions, design the operating model around it, choose and deploy the right technology, and build the capability so teams can run it themselves. The goal is not an AI strategy document. It is AI that is actually working six months later.
In most organisations, the responsibility for serving the customer is fragmented. Marketing owns one set of touchpoints, sales owns another, service owns a third. Each has its own data, its own systems, and its own definition of what a good customer experience looks like. The customer does not see any of that structure. They just see a brand that either knows them or does not.
The work here is breaking down that fragmentation: connecting the channels, aligning the teams, and building the digital infrastructure that lets you serve customers consistently and at scale. That means strategy and operating model design as much as it means platform selection. Getting the technology right without fixing the structure underneath it does not solve the problem.
This is where a lot of AI and personalisation ambition quietly falls apart. Businesses want to use AI to understand their customers better and act on that understanding in real time. But their customer data sits in silos: CRM in one place, web behaviour in another, transactional data somewhere else, with no reliable way to connect it. You cannot build a single view of the customer by accident.
The second problem is the gap between insight and action. Most organisations can generate reports. Far fewer can take what those reports are telling them and turn it into something that changes what happens in a campaign, a conversation, or a customer journey. That is where CRM and data connect back to AI and digital: the insight has to feed back into the experience, automatically and at scale. Building that loop is what I help businesses do.
Platforms and Technologies
Get in Touch
If you are working through an AI transformation, a digital CX challenge, or a customer data problem and want an experienced perspective, get in touch. A first conversation is straightforward: you explain what you are trying to do, I tell you honestly what I think.