AI at DCC: why we’re finding our best innovators beyond the data lab

AI’s growing at DCC and AI careers are open to a variety of people. Aodhán Burnell, Group AI programme lead in DCC’s Digital and AI Hub, tells more

“We’re always thinking about how we can innovate and stay ahead of our competitors. And adopting AI, particularly in the more traditional businesses we own, can give us that competitive advantage,” says Aodhán Burnell, Group AI programme lead in DCC plc’s Digital and AI Hub.

The advanced machine learning platform at the core of DCC’s business helps spot patterns so teams can achieve things like uplift in revenue and reduction in customer churn. Having AI as a tool creates value not just for the group, but for employees too – vital in a rapidly changing careers landscape.

“AI isn’t going to take your job. But someone else using AI in a really good way might,” says Aodhán. “So if you can be AI literate and retain your traditional commercial soft skills as well, that keeps you – and the business you work for – a step ahead.”

Aodhán uses his practical problem-solving skills in his role implementing AI, rather than technical expertise. “To leverage AI now, you don't need to be a data scientist. You don't need to have a PhD in machine learning to use it well,” he says. “It’s more useful to have a foundational understanding of what AI's capable of, and what it can do for people.”

A Politics, Philosophy and Economics graduate from Manchester University, Aodhán pivoted from a first job post the DCC graduate programme on the procurement team with SP Services (a former DCC Healthcare business) to his role in DCC’s Digital and AI Hub a year and a half ago.

“My procurement role involved working with kind of messy, inefficient processes and asking questions like, ‘Why are we doing this manually? Can we make it quicker? Can we make it easier for people?’” he says.

“These are exactly the questions we ask when we’re investigating whether AI can improve a business process or workflow.

“Given the similar approach, it was a logical step to get involved when Mike Webster was forming the centralised AI Hub for DCC,” he explains.

AI’s not something Aodhán thought he’d be involved with when he applied for the DCC graduate programme in 2020, enticed by a free pair of sunglasses at a careers fair.

But the ownership graduates on the programme are given straight away set him up for his current responsibilities. “We had autonomy and were trusted to make decisions, which can be daunting at first,” he says. “What DCC was looking for was people who can take the initiative and build their own path.”

“Another great thing about the graduate programme is that you retain that network of other alumni,” he adds. “I can now leverage that to ask questions about different DCC businesses and how they operate when scoping an AI project. I think that’s quite unique for a devolved group like DCC, to have a cohort who, although they don’t work together, can call on and learn from each other.”

The AI team and businesses on the ground take a collaborative approach to projects. “Areas of focus include things like helping sales teams reduce customer churn or streamlining processes so they’re more efficient,” he says.

“We start by taking a dump of all of the business's data and the external data scientists we work with do a quick analysis to identify the value pools available,” Aodhán says. These centre on customer needs and are a way of sizing up potential for value creation beyond existing markets or current revenues.

“We build a prototype and aim to stand up a working model in 12–16 weeks from first contact,” he says. “This might be something like a ‘you may also be interested in’, so suggestions for product cross-sells based on previous transactions that call-centre sales agents can use in real-time when speaking with customers.

“Or it could be a dynamic pricing engine that adjusts for market conditions and cost shifts to give customers the best deal,” says Aodhán.

Once models are built into workflows, the crucial final step is to ensure people use them. “For that last bit, we need to show incontrovertible proof of performance, so people trust the data and adopt what it’s telling them,” Aodhán says. “That means keeping a close eye on the model and retraining it so it’s always up to date.”

His work is different every day. He describes it as “quite ambiguous and abstract. You really need to embrace that and sometimes just learn on the job, which I find enjoyable, but it’s not necessarily for everyone.”

“Having said it’s abstract, I should add that AI doesn’t belong in the data lab. It has real-world impact and the people who’ll leverage AI in the most effective way are the people who think about real-world opportunities and outcomes. That’s what we’re focused on at DCC: not ‘We’ve got this cool thing over here that’s shiny and new,’ but ‘This is how you reap the benefits.’”