"One of the appropriate uses of AI in this service delivery space is the ability to look at the many different sources that an agency might have and help determine where the conflicts are and help quickly assist an agency in coming to grips with developing that universal knowledge system," Evan Davis, Executive Managing Director for Strategic Growth at Maximus, told Federal News Network host Heckman.
Frontline agencies facing tighter budgets and higher demand
The Internal Revenue Service, the Social Security Administration, and the Department of Veterans Affairs are cited as examples of federal agencies on the front lines of citizen service delivery that are operating under increasing strain. According to the source, those agencies confront smaller budgets, rising expectations, an aging population and a tightening economy — conditions that combine to ask agency workers to deliver more services, manage more complicated cases across multiple channels, and provide the right answers the first time.
Evan Davis and Maximus: practical framing, not platitudes
Evan Davis, identified in the source as Executive Managing Director for Strategic Growth at Maximus, framed the problem and sketched solutions in a conversation with Federal News Network. He emphasized turning the large volume of existing interaction data into actionable knowledge rather than guessing at citizen needs. Davis characterizes the mission as making it easier for agencies to help citizens access benefits and resolve problems as they arise, using tools agencies already possess.
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End the scrambleTurn captured inquiry data into a universal knowledge system
The core recommendation is straightforward: use the data agencies have already captured about citizen inquiries and interactions as the starting point. That dataset can be analyzed with AI and applied across channels so commonly asked questions are answered correctly and immediately — on a website, by a human agent, or by a chatbot. Davis said AI is particularly useful for reconciling conflicting sources and helping agencies "come to grips with developing that universal knowledge system," a phrase he used to describe a consolidated, agency-wide repository of authoritative answers.
Predictive services: customer stories as the engine
Davis advocated moving beyond one-off answers to build predictive services that map an individual citizen's journey over time. He explained: "Being aware of customer stories — what they’ve done in the past, what it looked like, and what came next for them — empowers agencies to then say, ‘I’ve got a pretty good idea of where you are, now that you’ve reached out. And not only what you’ve been dealing with, up until now, but what’s likely to come next for you.’ And if you can get ahead of what’s likely to come next, then you are hitting on one of those rare silver bullets in the service delivery world, where you can both begin to dramatically cut down on costs and increase efficiency while still delivering better customer experience," Davis added.
What this means for technologists, policymakers, and citizens
- Technologists and agency service teams: The immediate task is integrating disparate inquiry logs, contact-center transcripts, web analytics and chatbot records into a single, queryable knowledge base that AI tools can analyze and reconcile.
- Policymakers and regulators: Budgetary and oversight decisions will determine whether agencies have the resources and governance structures needed to standardize authoritative answers and to deploy AI across channels without introducing new contradictions.
- Citizens and service users: If agencies deploy the approach Davis describes, users should see faster, more accurate answers across websites, phone lines and chat interfaces — and potentially fewer repeat contacts for the same problem.
The prescription in the source is unambiguous: exceptional citizen service doesn't start with guessing; it starts with knowledge. Agencies, Davis argues, already have the raw material — interaction data — and can apply AI to reconcile conflicts, automate correct responses, and anticipate what comes next for individual citizens. The concrete challenge that remains is operational: assemble the data, agree on a "universal knowledge system," and move from reactive fixes to predictive service journeys.
Read the original story: https://governmenttechnologyinsider.com/delivering-exceptional-citizen-services-and-experiences-doesnt-start-with-guessing-but-with-knowledge/
