• 4 min read
AI policing boom fuels a new gold rush
Police tech vendors are pushing AI deeper into reporting, surveillance, and dispatch as departments sign on and concerns over oversight grow.
Image: The Verge
At the International Association of Chiefs of Police Technology Conference in Fort Worth, Texas, this May, vendors pitched what they called the future of policing: AI systems that can write reports, process surveillance feeds, field non-emergency 911 calls, analyze case histories, and help decide how departments deploy officers.
The Verge reports that the sales message is familiar from the broader software industry: let machines handle routine work so people can focus on higher-value tasks. In policing, though, that “busywork” includes core parts of the legal process, and automating them can directly affect people’s lives.
Among the products on display were facial-recognition cameras, automated license plate readers, body cameras, chatbots, gunshot detection systems, drones, and report-writing tools.
Real-time crime centers and the new police tech stack
A major push is around real-time crime centers, or RTCCs — platforms that combine data from sources such as 911 dispatch, CCTV cameras, and license plate scanners to give officers a live summary before they arrive on scene.
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Jason Truppi, a former FBI special agent who cofounded ForceMetrics in late 2020, told The Verge that police departments are overwhelmed by aging record systems and too much incoming data.
“All the systems of record [used by police departments] are essentially antiquated.”
ForceMetrics sells an AI-driven RTCC platform called Velocity. Truppi said his company avoids the language of predictive policing after earlier systems such as CompStat and PredPol became notorious examples of tech that promised objectivity but often reinforced existing problems.
“We don’t use the 'p word' at all, because it failed.”
Critics argue the new branding does not solve the old issues. Nina Loshkajian, a fellow at the New York University Center on Race, Inequality, and the Law, told The Verge that police were already using supposedly data-driven systems for years before 2020, without preventing violent encounters.
Axon, Motorola, and the rush into police AI
The biggest players remain Axon Enterprise, Motorola Solutions, and Flock Safety, but startups are piling in. Andrew Guthrie Ferguson, a professor at Georgetown University Law School, said the goal is to become the default platform for policing.
“We’re seeing a gold rush into selling [AI] technology to police with the promise that it will all make their jobs easier and more efficient.”
According to Amber Schroader, about one-quarter of attendees on the conference showroom floor were from equity firms scouting investments.
Axon has been particularly aggressive. In early 2024, it acquired Fusus and launched Axon Fusus, adding RTCC software to a lineup that already included TASERs, body cameras, automated license plate readers, Draft One, Axon Air, and an AI chatbot. In late 2024, it introduced the AI Era Plan, a subscription that bundles current and future AI tools.
On an investor call, Axon said AI Era Plan subscriptions rose 140 percent between the first quarter of last year and the same time this year, while AI product revenue grew 700 percent year over year.
“We are determined to become the AI company in public safety, and we are well on our way.”
One reason these tools are landing: paperwork. A 2024 Axon study found the average police officer spends 40 percent of a typical shift writing reports. John Mackey, a patrol sergeant with the Avon Police Department in Colorado, said that appeal is obvious.
“We didn’t sign up to sit behind a keyboard. That wasn’t why I became a police officer.”
But AI-written reports bring obvious risks. Axon says Draft One is based on a modified version of ChatGPT with creativity “turned down to zero,” yet The Verge notes that no major model maker — including OpenAI, Anthropic, and Google — has eliminated hallucinations. Earlier this year, Draft One reportedly wrote that a Utah officer had turned into a frog after background audio picked up The Princess and the Frog.
That example is absurd, but the underlying issue is not. A human officer can be cross-examined about why a report says what it says. A black-box system cannot — and police departments are increasingly being asked to trust vendors on exactly that point.
AI Editor
Ava covers the rapidly evolving world of artificial intelligence, from foundational models and research labs to the real-world economics of intelligence. With a background in computational linguistics, she cuts through the hype to find out what actually works. She firmly believes that benchmarks are just marketing until reproduced in the wild.
via The Verge
