For years, the conversation around AI in law enforcement was largely theoretical. Pilot programs, proofs of concept, cautious experimentation. That phase is over.
A recent piece published by AFCEA‘s Signal Media captures just how far and fast adoption has moved. Drawing on testimony from FBI, CBP, and Fairfax County Police Department leaders at a major law enforcement and public safety technology conference, it paints a clear picture: AI is now embedded across scores of use cases, and the primary benefit is speed.
The FBI’s Criminal Justice Information Services division alone has 28 active AI use cases, spanning data summarization, threat detection, coding, and research assistance. Fairfax County Police is deploying commercial AI tools for body camera translation, voice-to-text report generation, and video analysis. CBP reported saving 11,000 hours of staff time in a single month through AI-assisted coding, and is actively using AI to flag anomalies in cargo scans.
The throughline across all of it: AI reduces the time between information and action.
Speed is valuable. Trust makes it sustainable.
What stands out in the AFCEA piece is not just the pace of adoption, but the carefulness that accompanies it. Every organization cited placed significant emphasis on human oversight, accuracy, and accountability.
The FBI’s Chief AI Officer put it directly: the goal is to deliver AI capabilities at mission speed in a responsible way that does not harm investigations. The Fairfax County chief described a deliberate approach of piloting, building on early successes, and bringing community stakeholders along before expanding further. Former FBI assistant director Jason Richards framed AI as a corroborating tool, one that helps confirm or rule out leads alongside other evidence, not one that replaces investigative judgment.
This is the distinction that matters most as AI becomes more central to law enforcement operations. Faster is only better when the information driving faster decisions is accurate, contextual, and delivered to people who remain responsible for what happens next. A system that creates speed by generating noise or automating decisions that require human judgment does not make agencies more effective. It creates new problems.
What this means for video intelligence
Nowhere is this tension more visible than in video. The AFCEA article highlights it directly. AI tools for sorting through photographs and video are described as a differentiator, with the FBI’s assistant director of Operational Technology referencing the Boston Marathon bombing as an example of how AI could have dramatically accelerated a major investigation involving tens of thousands of digital images.
The challenge is scale. Law enforcement agencies capture enormous volumes of video every day. Most of it goes unreviewed. Not because it is unimportant, but because there is no practical way to analyze it systematically with human attention alone.
AI changes that equation. Computer vision can structure video data, identifying behavioral patterns, tracking individuals across scenes, flagging anomalies that would take hours to find manually. What was previously unstructured footage becomes searchable, analyzable intelligence.
But the same principles the FBI and Fairfax County are applying broadly hold here too. The system needs to operate within a secure environment, with data that stays inside the agency’s own boundaries. It needs to surface actionable information, not generate false positives that consume the time and attention it was meant to free up. And the people using it need to remain in control of the decisions that follow.
How Koshee is built for this moment
The approach law enforcement leaders described at AFCEA maps directly onto how Koshee Protect is designed.
Koshee Protect processes video on-site, within your own network, behind your firewall. Data stays inside your environment by design, meeting the same boundary requirements the FBI’s Chief AI Officer described as non-negotiable for their own deployments. Our models learn the specific environment they operate in, which improves accuracy over time and reduces the false positives that erode trust in automated systems.
The output is not a raw feed of alerts. It is structured, contextual intelligence delivered to the people responsible for acting on it, in real time, with the clarity needed to make fast decisions with confidence.
AI is bringing speed to law enforcement. Koshee is built to make sure that speed is backed by accuracy, security, and human control.
Read the full AFCEA article: AI Brings Speed to Law Enforcement
Learn how Koshee Protect delivers real-time video intelligence for law enforcement and security teams: contact us here