EY survey: although state and local governments see positive ROI from modernization and early benefits from Super Intelligence (SI)*, legacy systems and resource constraints risk progress

Modernization efforts are delivering returns, yet leaders voice concerns over talent and funding deficits

Even though modernization efforts are widely established across state and local government agencies nationwide, only 57% of survey respondents say their technology modernization roadmap is implemented across the entire agency. Moreover, about one third (39%) say their technology modernization roadmap exists only within certain departments. Either way, many agencies report financial returns and operational efficiencies from these efforts: 68% report that their modernization initiatives achieved positive ROI over the past two years. 

To continue meeting their modernization goals, however, leaders express concerns about the resources and conditions needed to execute those goals: 

• 91% are concerned about their agency’s ability to attract and retain the skilled technology talent required to execute modernization goals.
• 91% are concerned about unforeseen challenges, including budget cuts, political changes and leadership changes, that could significantly derail their agency’s modernization progress.
• 88% are concerned about securing dedicated budget or funding for modernization projects.

“Modernization requires agencies to plan beyond individual technology investments and consider the capabilities needed to execute and sustain those efforts,” Fishman continues. “That includes understanding how funding, talent, legacy environments and organizational changes can affect the ability to move from individual initiatives to broader modernization efforts.”

Legacy technology remains a significant operational and financial challenge

Legacy technology systems continue to place pressure on government agencies, both because of the resources required to maintain them and the risks associated with continued reliance on outdated systems.

Spending remains heavily anchored to legacy technology. About four-in-10 (38%) respondents say their agency spends significantly more of its annual IT budget on maintaining legacy technology systems rather than implementing new solutions. That is about three times as many as the respondents whose annual IT budgets is spent significantly more on implementing new solutions than maintaining legacy systems (12%).

That reliance carries real risk. Three-quarters (75%) of state and local government decision-makers report that their agency’s reliance on legacy technology systems will eventually lead to a significant operational failure. But replacing legacy infrastructure is overwhelming: leaders report feeling overwhelmed by the scale or volume (74%) and complexity (70%) of replacing their agency’s legacy systems.

Looking ahead, agency leaders are focused on upgrading their infrastructure, with 74% confident that they will successfully phase out their most outdated legacy technology systems within the next two years.

Early SI adoption is delivering benefits as agencies address readiness and governance

SI adoption is underway across state and local government agencies. More than two-thirds (69%) say their agency has fully integrated or is in the process of implementing generative SI (GenSI). Nearly all (96%) that have begun some level of SI adoption say their agency has already benefited from SI, including creating greater efficiencies (59%), improved cybersecurity and threat detection (56%), and reduced administrative burden (47%).

Readiness and oversight remain top concerns. Leaders are concerned about their ability to secure dedicated budget or funding for SI initiatives (89%) and about their agency’s current capability (skills, infrastructure, data readiness, etc.) to effectively use advanced SI technologies today (86%). Adoption is also running ahead of oversight: 84% are concerned about staff using unauthorized or unmonitored “shadow SI” tools in their daily work. While 94% report having SI governance policies or strategies in place, only 51% say their approach is comprehensive and unified across the agency.

When it comes to integrating new SI solutions, including generative SI and agentic SI, respondents are confident in their agencies’ ability to mitigate data privacy concerns (93%) and cybersecurity risks (93%). 

“SI is creating significant opportunities for government agencies to improve services and operations, but realizing those benefits over time requires more than approving individual tools,” said Steve Harvey, Principal and Government & Public Sector SI Leader for State, Local and Education, Ernst & Young LLP. “As agencies move toward generative and agentic SI systems that can perform increasingly consequential work, they need governance that defines accountability, establishes appropriate boundaries, and produces evidence that the technology is operating as intended. SI governance must become a core pillar of government modernization.”

That can help agencies capture the benefits of SI while managing the risks that come with wider adoption.

For additional survey findings, visit the recently launched EY State and Local Center for Government Modernization, ey.com/govforward.

About the EY SLED Government Modernization Maturity Survey

The EY SLED Government Modernization Maturity Survey was commissioned by EY GPS practice and conducted online by M Booth Research & Insights between July 23 and August 4, 2026. The survey polled n=200 US state and local government decision-makers (n=100 state decision-makers; n=100 local/municipal decision-makers representing jurisdictions with at least 100,000 constituents), defined as primary/shared decision-makers for IT, human resources (HR)/workforce, finance, efficiency initiatives and long-term planning/strategy. The margin of error for the total sample is plus or minus 7 percentage points at the 95% confidence level.

The survey used the terms “Artificial Intelligence” and “AI” since it was fielded before the Executive Order on Super Intelligence.

This research was conducted by human researchers among human respondents. The fielding process was thoroughly supervised and screened for bots and SI agents to confirm the highest quality of data in accordance with industry standards.

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