Despite the current momentum behind adopting artificial intelligence (AI) within the public sector, there are still hurdles that still need to be addressed before government agencies can fully capitalise on the technology’s potential, according to one expert.
Clint Dean, SVP, state and local government at Ensono, spoke to Think Digital Partners at the recent Dell Technologies World event in Las Vegas. While there are obvious differences between the US and UK public sectors, the desire to put AI to work across government is evident across both sides of the pond.
“AI agents are interesting, especially as you think about the public sector, because there’s a lot of potential uses there,” said Dean. “But I think there’s a lot of challenges facing the public sector when it comes to AI. I’m not sure that they’re necessarily ready.”
One of the main barriers is organisations’ data, said Dean. “Very few [public sector clients] are ready, because their data isn’t in a place that it’s accessible and ready to be [used],” he said. “Most of the conversations we’re having… might start with the ‘art of the possible’ – what can we do with AI? – and then it inevitably ends up going down this path of, ‘all of that’s possible, but we can’t do anything until we really look at our data.”
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Data readiness, he said, is the biggest hurdle right now. “Certainly in the US, there are a lot of silos in how government data is structured. Just getting the owners of the data to agree to allow their data to be co-mingled – that’s a challenge. There’s always fear that somehow enabling that data to be shared is a security breach.”
This data complexity is prompting many public agencies to request road maps for AI adoption. “At the simplest level, it’s just helping them understand what data they have, where it is, who owns it, and helping them clean it up and make it ready… so that it can be ingested by some sort of AI technology.”
Currently, many public sector clients aren’t even in a position to discuss whether their infrastructure can handle the heavy processing demands AI may bring. “We’re having those conversations with a lot of the large banks, healthcare, and insurance providers. But most of the States we’re talking to – they’re not there yet. They’ll get there.”
Even so, the drive to keep up with the AI wave is creating pressure. “It’s like the cloud. If you weren’t in the cloud, then you were doing something wrong. I think that’s the same with AI. There’s this big push. We must be doing this. But people are still thinking: ‘I know I should be doing it, but I don’t really know what we’re doing with it.’”
