3 November 2026
Conference investigates AI transformation to reshape how organisations create value
The xGov Low Code community’s annual conference provided an opportunity for the community to network and exchange knowledge and ideas.
“This is not just about saving time and money for the organisation. It’s also about creating a ‘social’ return on investment.”
David Macaree, STFC Scientific Computing's Head of Operations
More than 200 attendees and speakers from across UK Government came together this summer for the xGov Low Code community’s annual conference. It was hosted at the Science and Technology Facilities Council’s (STFC) Rutherford Appleton Laboratory (RAL) at Harwell, Oxfordshire, and provided an opportunity for the community to network and exchange knowledge and ideas around open-source code principles; Artificial Intelligence (AI) adoption – such as Copilot and agents; citizen development; and governance challenges across large organisations. Two STFC specialists were among the conference speakers.
Anton Lawrence, Interim Director, STFC Digital Infrastructure, kicked off the day by setting a focus on impact, best practice and collaboration for Government digital transformation. He positioned UK Research and Innovation (UKRI), STFC and RAL as major enablers of research, innovation, and economic growth.
He advised that, with an investment in 2024/25 of £8.4 billion, UKRI is the UK’s biggest investor in research and innovation, while RAL reported over 3,000 new jobs and more than £1 billion of private investment into campus businesses in recent years.
“We have a dynamic portfolio of investments that supports a creative and agile research and innovation system, which helps to create economic, societal, environmental and cultural benefits, as well as opportunities for everyone,” he said.
Talks throughout the conference discussed the shift from traditional coding workflows to AI-assisted development.
David Macaree, Head of Operations for STFC Scientific Computing, has been exploring AI’s transformation into practical, real-world solutions. He explained how his team’s journey began back in 2023 with a practical challenge – to replace analysing fragmented historical data and labour-intensive reporting with a system that would support faster insight, stronger capabilities and better-informed judgement.
He said, “At that time we didn’t have the AI platforms we have today, so we tried early AI models and discovered both the promise and the limits they provided. Speed and accessibility can be transformative, but without trusted sources, repeatable processes and effective governance, outputs remain inconsistent and adoption fails. When Microsoft CoPilot became available, we pivoted – and all the things we wanted to do suddenly became possible.
“For instance, some of our project data goes back decades and there is a lot of information locked up in Word and Excel files. We wanted to document ‘lessons learned’ from these projects, so we pulled together a team to take on that challenge.” They found it time-consuming and resource -intensive but after a week or so they had produced a fairly comprehensive document.
The team later ran the same challenge using MS CoPilot and found they had a similar answer within a couple of hours, along with some additional points to consider.
“The value of that is enormous and we are now moving on to creating benefits in operating systems and starting our journey on workflow automation,” said David.
“We have found there is insatiable demand for agentic AI. The problem is that people need to be shown real world examples of how this technology can be used before they are willing to commit time and energy into AI, and foundational demonstrators enable that.”
Through Microsoft CoPilot Studio, and more recently through Microsoft Foundry and using their Azure cloud platform, David’s team has been developing AI agents with enterprise level capabilities – ie. they are robust enough to be used securely, reliably and at scale across large organisations. They have started rolling them out across the large-scale multi-disciplinary facilities located at RAL.
“People are excited about AI’s potential to improve operating systems, such as helping teams make reliable changes to firewall settings.
“But this is not just about saving time and money for the organisation. It’s also about creating a ‘social’ return on investment,” said David.
“The real measure of success is much broader than just cash savings. It includes better decisions, better safeguards, increased confidence, stronger skills, ethical practice and social value. We need to treat AI as an operating tool to create value, looking carefully at what we automate and where human responsibility needs to remain.”
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