Governance, growth and the AI question for government

The past three decades have seen public sector organisations navigate successive waves of emerging technologies – from early internet services and virtual reality to blockchain and cryptocurrencies.

Yet one feature distinguishes the current Artificial intelligence (AI) moment: sustainability has become part of the conversation.

“I’ve seen a lot of disruptive technology,” said Ishmael Burdeau, lead sustainability business architecture at DWP Digital. “Along the way we had virtual reality, blockchain, bitcoin – and nowhere along any of those previous disruptive technologies did I hear about sustainability or the environment being mentioned.”

AI, he suggested, has changed that dynamic by forcing organisations to confront the wider consequences of digital innovation.

Moving beyond tactical AI adoption

Burdeau was speaking at a recent panel at the GDSA Summit (pictured), where he was joined by speakers from HMRC, the Royal Society, consultancy firm Kainos and Amazon Web Services (AWS) to explore how governments can prepare for disruptive technologies more strategically.

For Jeremy Davis, deputy director, head of user-centred design at HMRC, the key lesson from early AI deployments in government is clear: organisations need to move faster, and think more strategically.

“I would move faster,” he said when asked what he would do differently. “Government finds it hard to look beyond the next parliamentary cycle.”

Many current AI deployments remain focused on improving operational efficiency rather than transforming services.

At HMRC, for example, the department receives around 37–38 million phone calls a year. Advisors must write summaries after each call – a process that AI can dramatically accelerate.

“Having AI listen to that call, summarise it, but that’s the advisor in about a fifth of the time to do that,” Davis explained. “Times 37 million – it’s a pretty big number.”

While these efficiency gains are valuable, Davis believes the bigger opportunity lies elsewhere.

“So rather than getting 37 million calls from people who almost certainly do not want to call – they just have to – how do we proactively reach out to people by understanding the data that we hold?” he asked.

“That sort of systemic transformation… is really interesting. But it’s hard to rise above the tactical objectives.”

The growth dilemma in emerging technologies

Alongside the opportunities of AI, speakers also explored the structural tensions shaping its development.

Alison Griswold, senior policy adviser at the Royal Society highlighted the economic incentives driving many AI innovations – particularly the pursuit of rapid growth.

“The nature of Silicon Valley and the AI systems that we currently are developing is in pursuit of hundreds of billions of dollars of growth for the sake of growth itself,” she said.

That model can create friction with sustainability goals.

“It’s not that all growth is at odds with sustainability,” said Griswold. “But endless, unfettered growth is inherently at odds with sustainability and living within constrained planetary boundaries.”

She also warned that narratives around emerging technologies often exaggerate their inevitability.

“There will always be a new, sexy technology that the proponents are telling you is essential and needs to have all things moved out of the way to make it possible,” she said.

“That doesn’t mean that technology isn’t valuable – but we need to separate that narrative from the reality of what is useful.”

Embedding sustainability from the start

For Seto Adenuga, AI governance & ethics manager at Kainos, the challenge lies in integrating sustainability into governance frameworks at the very start of technology development. Too often, organisations treat sustainability as an afterthought – something addressed after a system has already been built.

“Governance is not a popular topic,” said Adenuga. “But it’s actually there to promote and support innovation.”

The key, she argued, is embedding sustainability considerations alongside security, privacy and other operational risks.

“If you embed that from the point of design… you’re getting ahead of it,” she said.

Organisations should also ask fundamental questions before deploying AI systems.

“One of the first questions we always ask… is: do we really need this tech? Is AI the right answer?”

Without those early discussions, organisations risk introducing avoidable costs, risks and environmental impacts later in the lifecycle.

The role of technology providers

Faye Holt, director, pan-UK public sector at AWS also noted that sustainability must be embedded from the very beginning of technology development.

“We can’t do it as a map before. We have to build this into our development from the start,” she said.

At the same time, Holt highlighted the potential for AI itself to improve infrastructure efficiency.

“We’re using AI to actually improve the back-end technology systems,” she said, citing improvements in datacentre cooling systems that have reduced water usage while increasing operational efficiency.

“You can drive operational businesses… but you have to be sustainable in everything.”

Preparing for the next disruption

The panel concluded that governments must prepare for disruptive technologies earlier rather than reacting once they arrive.

For Davis, the lesson from AI adoption is simple: “Start earlier and get ahead of it,” he said.

Burdeau echoed that sentiment, reflecting on how digital infrastructure itself may evolve in the coming decades.

“I’m hoping at some point the whole datacentre conversation becomes less contentious. It should move more to things on the edge – more stuff in people’s devices and homes,” he said.

Whatever the next wave of digital disruption looks like, the panel agreed that the central challenge will be ensuring innovation serves society, while staying within environmental and social limits.