15 minutes with: Rory Scott

How would you describe your job to someone you’d never met before?

I lead our AI engineering team, particularly focusing on public services. In practice, that means I work at the intersection of client delivery and commercial responsibility. I keep my finger on the pulse of the big picture issues affecting the public services market, informing our approach to work in the sector.

As the AI engineering capability team lead, I’m not afraid to get down into the weeds to understand what needs to be done, what technologies can be the most useful and impactful, and ensure AI implementation opportunities are always explored to deliver the best outcomes for our clients. For me, the best outcomes come from working alongside clients rather than presenting to them.

What makes PA stand out in its approach to solving client challenges?

At PA, people genuinely recognise the value of innovation. If I come up with a new idea, I can bring it to any of my colleagues and I’m always met with a great sense of enthusiasm to make it a reality. My colleague Becky Noble is a particularly big champion of innovation. She’s fantastic at connecting the dots with the right people at the right places to bring new ideas to life.

With such a range of experts with complementary skills and interests across PA, when we come together to solve the most complex challenges for our clients with our different ideas and perspectives, something pretty special happens. Strategists, designers, engineers, scientists, and sector specialists working together to go beyond just a strategy or recommendation.

When talking to our clients, it really comes down to the relationships before anything else. Our collaborative approach ensures we always innovate with them, not at them.

What’s the biggest challenge that your public sector clients face?

Resource constraints, slow procurement, and capacity issues continue to create barriers to progress in public services, and that’s before you even try to bring AI into it. Grappling with regulation, statutory delivery, and strict security classifications on data all make AI adoption far from straightforward.

As the rate of change in AI technology rapidly accelerates, it’s more important than ever for me to stay up to speed so I can experiment with the realms of what’s possible in the hopes of overcoming some of these barriers for our clients.

Those pressures are precisely the reason why we should focus on the highest value problems: start small, prove what works, and build momentum from evidence rather than hype. The real opportunity isn’t automating existing work, it’s redesigning how services operate and using data far better to improve outcomes.

How do you deliver innovation and transformation in your work for clients?

I always like to meet any project, client, or challenge head on. My approach is defined by listening to my client’s problem and not being afraid to ask basic questions to really get under the hood of the issue. One of my favourite things is being dropped into a room with a client because a colleague thinks I can bring a useful perspective to the client’s challenge. Coming at an issue with totally fresh eyes gives me a sense of perspective to explore my curiosity as I uncover the challenge piece by piece – like a puzzle I’ve got to solve in real time.

I always try and make innovation feel tangible through rapid prototyping, designing, building, and experimenting, keeping me focused on what could become a reality for clients so they can see, test, and react to it. However, it’s important to always look past the prototype. Often, it’s not the big idea that’s holding back transformation, it’s the prerequisites that enable the transformation to happen.

What needs to put into place to get this idea up and running? Thinking ahead, defining what the next two or three months of the roadmap will be, and laying these foundations is essential for AI transformation, especially in public services. If you get this right, the pay-off is the real-world impact, which is why I love this job.

What’s a trend you are seeing in AI right now?

AI is changing the conversation around what’s possible. For people who aren’t familiar with how AI programmes work, the technology feels pretty close to magic, which means they can dream big. My job is turning that ambition into something real and trustworthy.

Agentic coding is a great example of this, making it possible to create something truly impactful in a matter of days, making experimentation genuinely accessible.

I’ve recently been experimenting with developing an adaptive strategy using the UK government’s ambition to halve violence against women and girls by 2030 as a case study. By taking this plan and finding all the data points available to assess progress, this model can help direct attention where it’s needed to keep the plan on track.

This alone is not a revolutionary idea – it’s project management 101. The difference now is how agentic coding can pull data across remits, from the Crown Prosecution Service to the Office for National Statistics. AI can then synthesise all this data together and create a pipeline in a matter of minutes that would have taken a full team of developer months, if not years, to build.

But technology is never the whole answer, and I’m careful that the team never treats it as one. The value comes from combining AI’s speed and power with trusted data, responsible governance, security, and a clear operational purpose. Applied responsibly, that’s what lets public servants deliver better, faster, and more personalised outcomes for the people they serve.

Of the projects you’ve worked on, which have delivered the biggest impact?

One of the reasons I love working at PA is the variety of projects you work across provides a constant source of inspiration for innovation.

One project in particular stands out because I could directly see the tangible health benefits for people. We worked with a surgical robotics manufacturer, who make robots that complete the most difficult, intricate, risky surgeries imaginable.

They were struggling with one of the robot’s joints, most like a wrist in its flexibility and degrees of freedom. The joint kept wearing out more quickly than others, but they couldn’t figure out the cause.

Our team of data scientists did a deep investigation, trialling a bunch of different methods to diagnose the issue. In three months, we built a classifier with 84 percent accuracy at spotting whether that joint was starting to degrade mid-surgery. This let the team pinpoint the cause and fix it so the robots could keep delivering life changing operations.

What advice would you give to someone who wanted to get into your line of work?

It might sound cliché, but if you can work on something you genuinely really enjoy doing, that also happens to be good for your career and useful to people – that’s the sweet spot.

I’d also encourage you to put yourself out there, network, and meet as many different people as you can. Linking up with colleagues across disciplines and industries can help spark ideas. You might think you’re having an inconsequential conversation about an idea over coffee with a colleague, but a few months down the line that very topic becomes an issue their client needs to solve, and they’ll instantly think of you.

What are you looking forward to?

I’m involved in a new Department for Education initiative – the AI tutoring tools pioneer programme – which is going to be really cool. PA is one of eight organisations working collaboratively to improve educational attainment for children who receive free school meals, tutoring them to use AI to achieve better outcomes at school. When AI is applied in the right way, it has the potential to be a hugely powerful tool for learning, so I’m excited to make this a reality for the next generation.