Those issues surfaced repeatedly during a recent Georgia Technology Authority (GTA) GOVChats discussion focused on generative AI-assisted search, where speakers from Google Public Sector and Georgia’s Office of Digital Services and Solutions (ODSS) team unpacked how AI-generated summaries actually work for governments — and where common assumptions tend to miss the mark. One of the first misconceptions they addressed was how often those summaries even appear.
AI overviews, or AI-generated summaries, are short, synthesized answers that appear at the very top of Google search results, above traditional blue links. The summaries pull from multiple sources using large language models to help users quickly understand complex or open-ended questions — particularly how-to or guidance-based searches. Users are most likely to encounter them when searching for longer, more nuanced queries, such as how to complete a government process or understand eligibility requirements, rather than when looking for a single, definitive fact.
Those summaries are not designed to replace traditional search results or appear for every query. Instead, as the speakers explained, they surface under specific conditions, most often when users are seeking direction rather than a single, definitive answer. Gabby Burke, a Google Public Sector industry architect, described these as “no right answer” questions — searches that are “more nuanced … more in a gray area,” and therefore more likely to trigger an AI overview.
For government agencies, that distinction matters because AI summaries tend to appear when residents are uncertain about their next steps, not when they already know exactly what they’re looking for. As a result, the focus shifts away from competing for clicks and toward simplifying information.
The objective, Burke said, is to make government websites “the most unambiguous, authoritative source of information on the topic,” with content that residents — and large language models — can readily understand and trust.
Pages that clearly lay out steps, requirements and timelines — using plain language and structured formatting — are easier for AI systems to interpret, according to the Google architect. By contrast, dense PDFs that may be outdated, long narrative explanations or sprawling policy pages create more room for ambiguity. And even once-accurate pages can become liabilities if they remain online without clear updates or context, particularly in high-demand service areas — potentially impeding trust in government information.
As Burke said, government sites are already trusted, but that trust isn’t automatic or permanent. When information is unclear, outdated or incomplete, it creates openings for third-party sites to step in — some of which charge residents for services that are free or low cost through official channels.
Burke suggested a more proactive approach, encouraging agencies to “create content that actively debunks” material not created by government. Clear scam warnings, “myth versus fact” pages, and plainly written explanations don’t just help residents avoid confusion — they also give AI systems better source material to surface.
The emphasis on substance over shortcuts also extends to how agencies think about visibility in this evolving search environment. As entities begin to grapple with what this shift means, questions about paid promotion inevitably come up — as they did during the GTA roundtable. But when it comes to AI summaries, the answer from Google Public Sector was unequivocal. Paid ads play no role in how AI overviews are generated.
According to Burke, that’s a “hard no,” pointing to “a really strict separation between the ad business and organic search.” Sponsored content remains clearly labeled and segmented, reinforcing a familiar lesson for government agencies: Credibility comes from content quality, not promotion.
But as AI-assisted search continues to evolve, agencies may also notice changes in website traffic — particularly fewer clicks from search results. That evolution, speakers said, shouldn’t automatically be read as a negative signal. In fact, Burke suggested that traditional engagement metrics may become less meaningful over time.
“You might not care that a person spent 20 minutes on your page,” she said, adding that “it might actually be a bad thing.” Instead, the conversation pointed toward outcomes: whether someone completed a task, avoided an unnecessary call or finished a transaction without friction.
Despite concerns about declining traffic, speakers emphasized that AI isn’t replacing government websites — it’s changing when and why people arrive. Agencies should assume, Burke said, that users are “coming to your website more informed,” often “ready to take an action” once they get there. That shift places a premium on action-oriented design, requiring fewer clicks and with less emphasis on lengthy explanations once someone is ready to move forward. And increasingly, visitors are ready.
“There’s a lot of intent going in. People tend to know,” Amanda de Zayas, lead content strategist for ODSS, said. “They may not know specifically what service they need, but they know what they need to get done. So they really just want very brief, ‘OK, what do I have to do?’”
Ultimately, the GOVChat conversation suggested that AI search may not pose a direct threat to government websites — but could be a catalyst for change. And as AI becomes another layer between residents and services, agencies that invest in clear, current and task-focused content may be better positioned in the long run.
