The Federal AI Market is Large - But Where You Fit Depends on Agency Maturity

Harvey Morrison: Co-Founder/CEO, Marion Square

We recently conducted a webinar with Carahsoft where we analyzed the federal market for artificial intelligence. The discussion wasn’t based on general market narratives or high-level strategy it was grounded in something much more practical: the AI use cases that federal agencies are required to publish.

These inventories, driven by policies such as Executive Order 13960 and the Advancing American AI Act, provide a directional view into where AI is actually being deployed across government.

They are not perfect. They are incomplete, and in some cases lag reality. But they give us something most markets don’t offer visibility into where AI has moved beyond discussion and into real programs.

That’s the foundation for understanding what’s actually happening.

The Market Is Large—But Where You Fit Depends on Agency Maturity

From the outside, it looks like the federal government is broadly investing in AI. That part is true. The market is large, and momentum is real.

What’s misunderstood is how uneven that adoption is.

AI is not being implemented the same way across agencies. It varies significantly based on where an organization is in its maturity both technically and operationally. Some agencies are still exploring early-stage use cases, while others are integrating AI into mission-critical programs with defined funding and ownership.

At the same time, the types of technologies being deployed differ depending on that maturity. Early efforts tend to focus on pilots and experimentation. More mature environments are focused on applying AI to specific mission problems where outcomes can be measured and justified.

This creates a fragmented market not in terms of demand, but in terms of how and where that demand can actually be accessed.

For companies entering the federal space, success comes down to alignment. Not just to the agency, but to where that agency is in its adoption curve.

AI Is Being Applied to Mission Problems, Not Bought as a Capability

Across agencies, AI consistently shows up in environments where there is already pressure to improve outcomes.

That includes areas like financial oversight, operational awareness, and high-volume process automation functions where performance, cost, and efficiency are already under scrutiny.

These are not greenfield opportunities.

They are existing programs with:

• defined budgets

• accountable owners

• and clear expectations for results

That’s why AI is gaining traction there.

Most companies approach this in reverse. They lead with a capability and look for a place to apply it. Agencies are starting with a mission problem and looking for ways to improve it, sometimes using AI.

If you’re not aligned to that starting point, it’s very difficult to gain traction.

The Real Gap Isn’t Awareness—It’s Execution

There is no shortage of AI strategy across the federal government right now. Agencies understand that AI matters and, in many cases, have already identified where it could be applied.

What they don’t have is a clear path to operationalize it.

They are being asked to interpret mandates, manage risk, integrate with legacy systems, and move forward without disrupting ongoing operations. That creates a very specific type of demand—less about introducing new technology, and more about enabling execution.

This is where we are seeing real opportunity emerge.

Not in convincing agencies to adopt AI, but in helping them figure out how to move from intent to implementation in a way that aligns with how they actually operate.

Procurement Is Starting to Shape the Market

As AI adoption matures, procurement is beginning to formalize around it.

Organizations like the General Services Administration are introducing more structure around how AI is evaluated, acquired, and governed. This includes increased focus on risk, accountability, and alignment with existing federal frameworks.

This is an important shift.

It signals movement away from experimentation and toward repeatable acquisition. As that happens, the market becomes more defined but also more constrained by how government actually buys.

Companies that understand contract pathways, partner ecosystems, and program ownership will have an advantage. Those that approach this as an open-ended innovation market will struggle to convert interest into actual work.

What This Means for Go-To-Market

For companies looking to sell into the federal AI market, the implication is straightforward.

This is not a market you enter broadly. It’s one you align into.

That means:

• understanding which programs already have funding

• identifying where AI is adjacent to existing efforts

• aligning to specific mission outcomes

• and positioning your capability as a way to accelerate something that is already underway

It also means recognizing that your fit will vary depending on agency maturity. The same offering will not land the same way across different organizations.

This is where most go-to-market strategies break down. They assume uniform demand in a market that is anything but uniform.

Closing Thought

The federal AI market is real, and it is growing.

But it is not a single market.

It is a collection of programs, priorities, and maturity levels that require alignment to access. The companies that understand that and adjust their approach accordingly are the ones that will find traction.

Watch the Webinar Recording: