Government's biggest technology problem isn't AI

If you've attended a government technology event or followed the industry conversation this year, you've probably noticed that nearly every discussion eventually comes back to artificial intelligence. Agencies are exploring new use cases. Software providers are adding AI capabilities to their platforms. Industry leaders are considering how the technology could reshape the delivery of public services.

AI will clearly play an important role in the future of government. But from where I sit, there's another technology challenge that deserves just as much attention.

It's not AI. It's integration.

For government entities, integration is not simply a technical consideration. It shapes how quickly agencies can respond to citizens, how confidently staff can make decisions, and how easily public services can adapt as expectations change.

Across permitting and licensing, utility billing, community development, courts, and other government services, agencies are under pressure to deliver faster, more intuitive digital experiences. At the same time, they must provide the reliability, accountability, and accessibility that citizens expect from public institutions. Yet many of the systems powering those services still operate independently, creating disconnected workflows for staff and fragmented experiences for citizens. And that creates a problem that AI alone cannot solve.

"AI can make a good process better. It can also make a disconnected process more complicated."

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AI is only as powerful as the systems behind it

AI can automate routine tasks, surface insights, and help agencies improve service delivery. But it cannot fix the underlying problems created by disconnected technology. When I talk with agencies and software providers, I hear many of the same challenges:

• Staff spend too much time managing workarounds and moving information between systems instead of focusing on serving citizens and higher-value priorities.
• Critical information remains spread across separate applications, making it harder to gain a complete view of operations, revenue, and how citizens interact with government services.
• Citizens are often forced to navigate multiple systems to complete what should feel like a single service or transaction.

These challenges become even more significant as agencies move from experimenting with AI to embedding it into everyday operations. According to a recent NASCIO study, only 20% of public-sector organizations reported having mature data governance practices in place.

Without trusted, connected, and well-managed data, even the most advanced AI tools can struggle to deliver meaningful results.

The issue isn't whether government has enough technology. In many cases, it has plenty. The issue is whether that technology can work together. Deloitte's 2026 Government Trends report points to a broader shift toward adaptive operating models, redesigned workflows, and technology that can support continuous change. Avasant's State and Local Government Digital Services 2026 RadarView similarly emphasizes interoperability, integrated service delivery, and connected data as agencies move AI from experimentation into everyday operations.

The takeaway is simple: Adding smarter technology won't fix problems created by disconnected technology.

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Government is asking a different question

Much of the AI conversation starts with a single question: "How do we add AI?" But I believe the more important question is:

"How do we make our systems work together?"

Citizens don't think about government in terms of departments, applications, or technology providers. They simply expect services to work. Whether they're applying for a permit, renewing a license, paying a utility bill, or submitting a service request, they expect the experience to be straightforward and connected. That expectation is changing the conversation for software providers, too.

For years, government software was primarily evaluated on its ability to solve specific operational challenges. Today, agencies are increasingly looking beyond individual features and asking a bigger question:

"How easily can this solution fit into the way we already work?"

That shift changes what makes a technology solution valuable. Providers that can integrate with existing environments, connect workflows, and reduce operational complexity may ultimately create more value than those with the longest feature lists.

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Payments show what integration looks like

Consider a citizen applying for a permit. They complete the application online, upload the necessary documents, and reach the point of payment, only to leave the application and navigate to a separate payment site.

Technically, the transaction works. But from the citizen's perspective, it doesn't feel like one service. It feels like a handoff. And handoffs are where friction enters the digital experience.

When embedded payments are built directly into the software that an agency and its citizens already use, payments become part of the service rather than another disconnected step. It can help agencies simplify reconciliation, reduce administrative work, and create a more consistent digital journey for citizens.

For software providers, that means payments are no longer simply a feature added at the end of a workflow. They are part of the workflow itself.

But the same principle applies far beyond payments. Whether it's permitting, licensing, utility billing, or other citizen services, the goal is the same: eliminate unnecessary handoffs, connect experiences, and make it easier for staff and citizens to accomplish what they came to do.

That is the opportunity created by integration. We see it in practice through organizations like Black Mountain Software, which embedded payments directly into its utility billing solution to create a more seamless experience for both agencies and the citizens they serve.

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Looking beyond the AI conversation

AI will continue to dominate the headlines, and rightfully so. But the agencies that ultimately get the most value from it may not be the ones that adopt it first. They may be the ones who have built the connected systems, trusted data, and streamlined workflows needed to support it.

Before government can fully benefit from smarter technology, it needs technology that works together. That doesn't mean slowing down AI adoption.

It means approaching AI as part of a broader modernization strategy, one that connects the systems, data, and workflows AI depends on.

The future of government technology won't be defined simply by how much AI agencies deploy. It will be defined by how well their technology works together.