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Executive Summary:
Partner Chen Liu attended CivStart's GovTech conference which highlighted how local governments are becoming more selective about technology investments and how they are prioritizing solutions that deliver clear operational benefits as budgets tighten and staffing challenges continue. Along with this, the conference called out how AI adoption is increasingly focused on practical uses that help existing employees work more efficiently, rather than broad or highly ambitious applications. For GovTech providers, success will depend on integrating AI into important workflows, demonstrating measurable results, and building the trust needed to support government operations.
The conversations at this year's CivStart GovTech conference felt notably different from those of the past few years.
Artificial intelligence (AI) continues to dominate headlines, but local government leaders are becoming far more pragmatic about where and how they invest. With pandemic-era funding largely exhausted and budget pressures mounting, agencies are evaluating technology through a simpler lens: Does it help us deliver better outcomes with the resources we already have?
Across sessions and conversations with government leaders, technology providers, and investors, three themes consistently emerged. First, efficiency must be measurable. Second, AI is increasingly finding its place in everyday government workflows. And third, trust remains the deciding factor between a successful pilot and broad adoption.
These dynamics reinforce many of the trends we have highlighted in our broader GovTech research, including our perspective on how modernization is reshaping GovTech investment opportunities and our recent discussion of AI opportunities and challenges across the GovTech ecosystem.
Related: Education & Public Sector
The Era of "Modernization for Modernization's Sake" Is Fading
Local governments continue to face growing demand for services while managing persistent labor shortages and rising operational costs. At the same time, agencies no longer have the same level of funding flexibility that existed during the height of pandemic stimulus programs.
As a result, technology purchases are receiving greater scrutiny. Whether evaluating a new platform or renewing an existing contract, buyers increasingly want to understand how a solution provides tangible operational benefits.
Technology still remains a priority, but the conversation has shifted from modernization to outcomes. Solutions tied to mission-critical workflows and measurable operational benefits are proving easier to justify than those positioned around broad transformation narratives alone.
For GovTech providers and investors, this raises an important question: Can the value proposition be articulated in terms that resonate with budget owners, department leaders, and procurement stakeholders?
AI's Most Immediate Opportunity Is Helping Existing Teams Do More
While AI was a central topic throughout the conference, the most compelling use cases were surprisingly practical.
Rather than pursuing ambitious autonomous systems, agencies are focusing on applications that help employees work more efficiently. A few areas of interest were focused on supporting public records requests, improving employee training, preserving institutional knowledge, and prioritizing inbound service inquiries.
What ties these use cases together is staff capacity. Local governments are searching for ways to help existing teams handle growing workloads without requiring significant additional headcount.
For providers, this reinforces a lesson being observed across many software markets: broad AI functionality may attract attention, but workflow-specific applications create measurable value. When governments can directly compare improvements and operational impact before and after implementation, the return on investment becomes much easier to demonstrate.
The same theme is increasingly influencing how investors evaluate software businesses. As we have discussed in
our framework for evaluating AI disruption risk in GovTech software businesses, differentiation is likely to come less from generic AI capabilities and more from how effectively those capabilities are embedded into critical workflows.
Trust Remains the Gateway to Adoption
Despite growing enthusiasm around AI, government leaders remain appropriately cautious.
Questions around transparency, governance, accountability, cybersecurity, and public perception were frequent topics of discussion throughout the conference. Even when a use case appears compelling, agencies must be confident they can explain how decisions are made, how outputs are validated, and who remains accountable when mistakes occur.
That reality is making pilot programs increasingly important.
Rather than pursuing enterprise-wide deployments immediately, many agencies are testing AI within clearly defined workflows where outcomes can be measured and human oversight remains straightforward. Successful pilots create a foundation where efficiency gains can be achieved in practice.
Ultimately, trust may prove just as important as technical capability in determining which solutions gain meaningful traction.
Adoption Will Happen One Workflow at a Time
Another recurring discussion primarily centered around governance models for AI adoption.
Many organizations appear to be moving toward a hybrid approach of centralized oversight combined with departmental experimentation. Under this model, technology leaders establish security, governance, and compliance requirements while allowing individual departments to identify opportunities most relevant to their operational needs.
Even then, adoption is unlikely to occur uniformly.
Every municipality brings a different combination of infrastructure, data maturity, budget constraints, and change management capabilities. In many cases, one department may be ready to deploy an AI-enabled workflow while another is still modernizing foundational systems.
For vendors, this creates a need for flexibility. Success will increasingly depend on meeting customers where they are rather than expecting standardized adoption across jurisdictions.
What It Means for Investors and Providers
As AI lowers the cost and complexity of developing software, product functionality alone may become a less durable source of competitive advantage.
Instead, long-term differentiation may come from factors such as trusted customer relationships, deep workflow integration, proprietary data, strong governance practices, and a demonstrated ability to deliver results in government environments.
For investors evaluating GovTech businesses, that means looking beyond headline AI narratives. Key questions to consider include:
- Can customers clearly quantify the product's impact?
- Does the solution help agencies navigate budget constraints?
- How difficult is implementation and adoption?
- Does the provider have the trust required to support mission-critical operations?
These questions increasingly sit at the center of successful GovTech investing.
The message from CivStart was focused on how local governments remain committed to modernization, despite the threshold for adoption rising. The providers best positioned for growth will be those that solve tangible operational problems, strengthen existing teams, and earn trust through measurable results and responsible deployment.
About Grant Thornton Stax
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