AI Digital Eagles: Why Human Champions Make AI Programmes Succeed

What Barclays learned about digital transformation that every organisation deploying AI needs to understand

The iPad Paradox

In 2012, Barclays Bank made what was then the largest corporate iPad purchase in the world. Ten thousand devices, in Barclays blue, distributed across their entire branch network. WiFi installed everywhere. The message was clear: we are a digital-first, mobile-first bank.

The iPads sat unused.

Simply put, staff weren’t comfortable with the technology. They didn’t know what to do with them. The devices gathered dust while branch workers continued doing things the way they always had. Barclays had just deployed iPads and WiFi into every branch, aiming to be the most digital bank in the UK but they quickly discovered the human reality: people weren’t comfortable with digital, and no amount of hardware would change that on its own.

This may sound eerily familiar. Across the globe, organisations are deploying AI tools with the same assumption that gave Barclays their expensive paperweights: if we provide the technology, transformation will follow.

It won’t.

The Numbers Don’t Lie

The failure rate for technology-driven change programmes is sobering. Gartner reports that 80 per cent of digital transformation projects fail. And for AI specifically, their 2023 research found that 85 per cent of AI projects fail to deliver on their objectives.

These are not failures of technology. The tools work. The algorithms are sound. The infrastructure is solid. What fails is adoption. What fails is the human element.

Gartner identified the primary causes: difficulty integrating with existing business processes, management resistance, internal politics, lack of skills and governance challenges. Read that list again. Every single factor is a people problem.

Organisations are currently spending millions - if not billions - on AI platforms, models and infrastructure while treating the human side of the equation as an afterthought. It is the digital transformation playbook all over again, and the results will be predictably identical.

How Barclays Changed Everything

Barclays then tried something different. The transformation team persuaded leadership to let them have a tiny pilot group for six months. Their job was simple: to visit branches and personally show staff how to use their new iPads. No training sessions in conference rooms. No online modules. Real people, sitting alongside their colleagues, demonstrating how the technology could help them.

They called them Digital Eagles.

The multiplier effect was remarkable. Within two months, those initial Eagles had recruited volunteers – staff who had become comfortable with digital tools and wanted to help their colleagues experience the same. The programme grew organically, and eventually over a third of the entire workforce became digital ambassadors. The ratio matters more than the raw numbers: a small initial investment in trained champions created exponential peer-to-peer adoption.

The Human Reality Behind the Statistics

To understand what that Barclays programme actually meant, consider Margaret. She had worked at the Nuneaton branch for twenty-three years and knew every regular customer by name. She could process a mortgage application faster than anyone in the region. Yet when the Barclays blue iPad had first arrived on her desk, she was terrified.

Not of the technology itself, but of what she didn’t understand. Was this going to replace her? Was she supposed to know how to use it already? What if she asked a stupid question in front of younger colleagues? The safest course of action, Margaret decided, was to leave it in the drawer and hope it went away.

Multiply Margaret by thousands of branch workers across the country. This was Barclays’ adoption challenge. And it is precisely your AI adoption challenge today.

Then Sam arrived. Sam had been at the branch for just two years, but had recently volunteered for the Digital Eagles programme. Sam wasn’t from IT. Sam wasn’t a technology expert. Sam sat at the next desk and handled the same customer enquiries Margaret did. But Sam had spent a week learning not just how to use the iPad, but how to help colleagues feel comfortable with it.

Sam showed Margaret how to look up a customer’s account history without walking to the back office. How to demonstrate mobile banking to customers who were curious but nervous. How the iPad made the job easier rather than replacing it. Margaret asked Sam a question she would never have asked the IT helpdesk: “What if I press the wrong thing and break it?” Sam smiled, showed her the reset button and sat with her while she tried her first customer demonstration.

This is what actually drove adoption. This is the Digital Eagles model.

Building Your AI Digital Eagles Programme

The Barclays model translates directly to AI adoption. Your leadership team can mandate AI usage and set ambitious targets, but if employees do not feel supported and capable, those mandates will produce compliance at best and resentment at worst. Shadow AI – unsanctioned tools used without IT knowledge – emerges precisely because official channels feel inaccessible or intimidating.

How to Identify Your Eagles. Look for employees who have already shown curiosity about AI, regardless of technical background. Enthusiasm and credibility with peers matter more than expertise. The accounts manager experimenting with ChatGPT is a better candidate than the data scientist who already uses AI professionally.

Train for confidence as much as competence. Your Eagles need to understand not only how to use approved AI tools but how to answer their colleagues’ fears. What data is safe to use? Will this replace jobs? These are the questions people actually have and your Eagles need credible answers.

Make it peer-to-peer. The power of the Digital Eagles model was that help came from colleagues, not IT. A fellow team member showing you how to use an AI tool carries different weight than a training video from corporate. Preserve this dynamic.

The Culture Comes First

Barclays did not become a digital-first, mobile-first bank just by buying iPads. They became a innovative bank by investing in people who helped their colleagues become comfortable with change. The technology was table stakes. The culture was the competitive advantage.

The same is true for AI. Your organisation can have the most sophisticated models and the most ambitious transformation roadmap. None of it matters if your people are not ready to embrace it – and most of your employees are more like Margaret in Nuneaton than the enthusiastic early adopters in your pilot programme.

So here is the question every organisation deploying AI needs to answer: who is your Margaret? Who is your experienced, capable, valuable employee who is quietly terrified and hoping the whole thing goes away?

And more importantly: who is going to be your Sam?