The federal government needs help making fast, accurate decisions in environments where failure carries real consequences.
That’s why the most immediate AI opportunities are sitting inside operations centers, air traffic towers, military command units, and emergency response teams. These are contexts where every second counts, where AI helps people act faster and more precisely.
The most mature example is the Pentagon’s Project Maven. Originally built to process drone footage, it’s now fusing imagery, audio, and text streams to generate live maps for battlefield decisions. The goal: commanders want to vet and approve up to a thousand target assessments per hour. AI handles the triage; humans stay in the loop.
The FAA is moving in a similar direction. With air traffic controller staffing still under pressure, they’re testing AI to monitor real-time airspace activity and surface anomalies before they become threats. It’s backup for tired humans managing crowded skies.
The throughline is clear: real-time environments are a natural fit for AI. But the opportunity is for durable tools that process noisy data, make judgments fast, and hold up under pressure.
If you build for that, they’re listening.
If you're evaluating opportunities in federal AI procurement but lack ground-level visibility into how defense, aviation, or emergency operations teams actually make decisions, Emerging Strategy can help you map the real workflows these tools need to support.
Need our Deep-Dive Report?
“Inside the Federal AI Buying Cycle: What Commercial Vendors Need to Know”
This is for you if you’re:
- B2B SaaS founders and GTM leaders targeting federal
- Enterprise AI companies exploring public sector growth
- Product, research, or strategy leads validating market fit for gov use cases
Scroll to the end of the article for a table of contents.
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Document Intelligence at Scale
The federal government generates more paperwork than any other institution on Earth. Forms, filings, applications, case notes, legal memos, compliance reports—the flood never stops. And for the first time, agencies are getting serious about using AI to read, sort, and summarize it all.
The U.S. Patent and Trademark Office has already made it mandatory for patent examiners to run AI-based similarity checks before reviewing an application. They’re also piloting LLM tools to help write the dense, structured reports that accompany every decision.
The IRS, quietly, is doing the same. Internal chatbots are being trained on the agency’s sprawling manuals, helping staff find relevant rules faster. But the bigger play is audit automation: using AI to flag irregularities, surface key records, and even pre-write parts of case files. Treasury leadership wants AI to handle every back-office function it can.
The scale is massive, but the need is simple: accuracy, consistency, speed. And not in a one-off prototype. In real, operational deployments that can handle a hundred thousand cases without falling apart.
That’s the bar. If your product can clear it, there may be a contract opportunity.
Emerging Strategy helps vendors understand how manual workflows in legal, compliance, and tax functions are evolving, especially where AI adoption is tied to internal resistance, procurement cycles, or case-level accountability.
Workforce Multiplication, Not Just Automation
Most federal agencies aren’t chasing full automation. They’re trying to stretch fewer staff across growing responsibilities. AI is being brought in as a pressure valve.
At the FAA, a leaner air traffic control workforce is managing busier skies. AI is being tested to take over background monitoring: tracking aircraft that haven’t yet entered anyone’s visual field, spotting patterns that signal early trouble. Controllers stay focused on pilot communication and coordination. The machines handle the margins.
The Department of Veterans Affairs is running hundreds of AI systems behind the scenes. Some triage health records to identify urgent mental health risks. Others score claims to prioritize faster reviews. These aren’t experiments—they’re deployed tools, already live in the workflow.
And at the IRS, the strategy is even more explicit. Leadership is restructuring back-end functions—IT, HR, case processing—with the assumption that AI will carry most of the load. The objective is capacity enhancement.
This is where AI companies with practical, human-in-the-loop tools can win. Not by pitching wholescale replacement, but by showing how their product lets one analyst do the work of five.
We work with product and strategy teams to pressure-test whether their AI-enabled tools can credibly scale inside constrained, human-in-the-loop government environments—especially in health, benefits processing, and infrastructure oversight.
Security, Screening, and Surveillance
AI is already part of the U.S. government’s security infrastructure.
At more than 200 airports, TSA facial recognition kiosks are matching IDs in real time. Officers are still there, but the algorithm checks the face first. Internal studies claim 99%+ accuracy across demographic groups, though critics still question the system’s performance across edge cases. Meanwhile, new kiosk models are being tested to let pre-checked passengers pass through with almost no interaction.
At the Department of Defense, object recognition systems are being used to process drone feeds and satellite imagery in active operations. Commanders get visual input with suggested classifications, heatmaps, and confidence scores. In some cases, strike planning is supported directly by those systems. Human judgment remains final, but machine recommendations are central.
These use cases share two traits: structured environments and high stakes. That’s where AI thrives. Airports, base perimeters, drone footage, checkpoint systems—they all run on known inputs and repeatable decisions. It’s a constrained world. And that makes it automatable.
Systems with an edge will be able to spot an anomaly, verify an identity, or surface a pattern with fewer false positives than a tired human.
From Pilots to Procurement
The experimentation phase is ending and AI is being written into budgets.
The Department of Defense just added $795 million in new funding for Maven Smart System. USPTO made AI-based prior art checks mandatory. The IRS is restructuring entire functions around the assumption that AI will run core processes.
The federal government has shifted from “can this work?” to “how fast can we scale it?” The Trump administration’s new framework accelerates that shift by removing risk-averse review labels and replacing them with a fast-track category called “high-impact.”
This is where most commercial vendors fail. They stay in pitch mode, talking capability instead of showing deployment. But agencies need tools that work inside procurement constraints, with clear implementation paths and credible references.
If you’re building something real, measurable, durable, already used in sectors that resemble government—you’re in a better position than you think.
You need field-level research with procurement influencers, program managers, and agency stakeholders to help validate demand, de-risk positioning, and navigate the reality behind “AI mandate” language in policy statements. We can help.
Selected, Department-Specific Use Cases
- DoD: Maven, Smart System (Palantir), logistics optimization, battlefield data fusion.
- FAA: AI for predictive maintenance, anomaly monitoring, safety analysis.
- TSA: Facial recognition, automated screening kiosks, threat detection.
- IRS: Audit review, fraud detection, internal LLM-powered systems.
- USPTO: Prior art similarity search, LLM drafting for examiners.
- VA: Suicide risk prediction (REACH VET), healthcare triage, case scoring.
Emerging Strategy helps B2B SaaS companies play offense in markets where the rules are shifting and the path to adoption is anything but obvious. We work with executives navigating complex sales cycles, crowded landscapes, and high-stakes demand—and we give them an edge.
Our B2B SaaS Practice supports:
- Revenue owners who need clear answers in ambiguous markets, so they can prioritize, position, and close with confidence.
- Strategy, product, and intelligence teams who don’t have time for generic research—and need precise, decision-ready insight, fast.
We don’t just track trends. We map power, surface buyer behavior, and help our clients see what others miss. We enable you to take an aggressive competitive posture in your market by identifying customer opportunity and competitor vulnerability.
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Deep-Dive coming soon:
“Inside the Federal AI Buying Cycle: What Commercial Vendors Need to Know”
Everyone’s talking about “AI in government.” Almost no one understands what the buying process actually looks like.
Who It’s For:
- B2B SaaS founders and GTM leaders targeting federal
- Enterprise AI companies exploring public sector growth
- Product, research, or strategy leads validating market fit for gov use cases
What’s Inside:
1. Where the Budgets Are Going
Breakdown of agency-level AI funding movements (e.g., DoD’s Maven Smart System, IRS modernization, USPTO mandates), tied to actual line items, RFPs, and vehicles.
2. AI Adoption Timelines by Function
When and where AI is expected to move from pilot to scale across domains like logistics, risk scoring, document intelligence, and surveillance.
3. Decision-Maker Maps
Insight into who really owns the AI decision—central IT? Functional leaders? Procurement?—and how that differs by agency.
4. Procurement Pathways That Actually Move
Summary of contracting mechanisms that commercial vendors can use to bypass red tape: OTAs, SBIR/STTR, BPA call-ups, CIO-SP4, Alliant 3.
5. Key Buyer Concerns
From explainability to integration risk to false positives—what agencies want to see before approving new AI deployments.
6. Where Commercial Vendors Are Winning
Profiles of companies already landing meaningful deals (e.g., Palantir, Lauretta.io, Anduril, Paravision)—what they did right, and how others can replicate.
7. Signals to Watch in FY2025-FY2026
How policy, budget allocations, and internal mandates are shifting—and what vendors should track to stay ahead of the next RFI/RFP wave.
Our subscribers receive priority access to a this deep dive, breaking it down agency by agency, use case by use case—along with a map of where the real demand is, who controls it, and how to get in.
