Social safety nets have proven to be especially vital during the ongoing coronavirus pandemic. But in some cases, the underlying legacy IT infrastructure supporting the modern delivery of those services has failed them.

Artificial intelligence and machine learning, however, have played an increasingly important role in helping agencies adapt to the challenges of the pandemic — particularly with volume and scale.

“Volume is a significant problem for all of the social safety net programs. They are seeing record numbers of applications and because the systems that support those programs are typically older legacy systems — some of them as old as 40 years old — they can't scale to meet that demand,” Winkler says.

On top of that, the CARES Act — which provided relief in response to the coronavirus — created some new programs that the inflexible legacy systems could not readily incorporate.

“The real issue is how does technology — and how will agencies — continue to serve this high volume of clients as we begin to reopen and recover?” she says in the podcast. Sponsored by Google Cloud.

Guest: Denise Winkler, Strategic Business Executive, Global Public Sector Group, Google Cloud

Host: Wyatt Kash, SVP, Content Strategy, Scoop News Group

Look for more coverage from the "Future-Ready Government” series on www.fedscoop.com/listen and www.statescoop.com/listen

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