People at Applied are curious and experimental. It’s what drives us to turn ideas and projects that seem so complex they are unfeasible into real systems. Systems that become normalised and ingrained into day-to-day lives, like Legible London’s city walking identity, Google’s global workplace wayfinding, or the harmonised standard for Toronto’s regional transit system…

Establishing the Innovation Lab

Fueled by this passion for simplifying the complex, Applied’s experience is grounded in project delivery and countless hours of experimentation – testing and developing new tools, methods and workflows. Much of this exploration has, until now, taken place informally or within teams. Our Innovation Lab has been established to bring this work together, giving it structure, visibility and a shared direction. It aims to advance our work in building systems that empower people to navigate and to make those systems easier to implement and manage.

As R&D Strategy Lead at Applied, my role is to connect emerging technology and research with practical outcomes that improve how we design, deliver and maintain our projects. Our goal at the Innovation Lab is to support people experimenting and collaborating in a way that links our creative vision to business priorities and social initiatives – making sure good ideas and research don’t get lost in the rush of delivery deadlines.

It also ensures that we stay ahead of rapid technology change, especially with AI, by identifying opportunities early and driving innovation in wayfinding, navigation, information design and place identity.

Strengthening our research with BridgeAI

While exploring ways to strengthen the Lab’s R&D, we forged a relationship with Innovate UK BridgeAI, a programme designed to help UK businesses adopt and apply AI responsibly. Together with strategic partners, such as The Alan Turing Institute, BridgeAI connects organisations with leading academic and industry expertise, offering hands-on support for testing and developing early-stage ideas in collaboration with universities and researchers. BridgeAI focuses on sectors including transport, infrastructure and the creative industries – all core to our work at Applied. What stood out was its emphasis on practical collaboration: short, targeted projects that validate ideas quickly and deliver tangible results.

It has proven to be an ideal match – a clear, structured way to combine Applied’s design and data expertise with academic rigour.

Matching with Loughborough University and Professor Diwei Zhou

Through BridgeAI, we were matched with Professor Diwei Zhou of Loughborough University, whose expertise spans applied statistics, AI and data analysis. 

Diwei has advised us on our wider AI research and on building effective collaborations with universities. She has given us a strong sense of how and when to involve academics and doctoral researchers in our data-led initiatives to accelerate progress and sharpen thinking. Our conversations have turned experimental briefs into measurable, practical and prioritised projects. 

Next steps at the Innovation Lab

The Lab has several key projects in development. I’m looking forward to sharing more details as these become codified, as well as updates from our team on their use of emerging technology and automation in design, mapping and wayfinding.

For now, I’ll leave you with a few thoughts on effective operations of innovation:

Start small: The quickest way to learn is to design small experiments that can fail safely and teach you fast. Evidence grows from experiments – not assumptions.

Collaboration works best when it’s intentional: Professor Diwei Zhou and BridgeAI have reaffirmed how powerful it is to bring academic partners into industry work early and with purpose – to align methods, not just outcomes.

Rigour is a creative asset:Academic frameworks bring structure that strengthen design work, helping translate complex, creative ideas into measurable, credible outputs.

Knowledge (especially failure!) only counts if it’s shared: The Lab’s job isn’t simply to prototype; it is also to support knowledge sharing. When innovation is captured, structured and shared, it compounds rather than resets. That is how innovation becomes organisational muscle, not just a side project.

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