COMPUTER COPS: Inside the big business of selling AI to the police

I stood before a hulking glass and brick structure in the heart of Fort Worth, Texas. Thousands gathered inside to see what had been billed as “the future of policing in the digital age.” As press, I was prohibited from entering, but from a number of nearby locations, I met with attendees who told me what was being sold within. And I learned that AI is threatening to seize the very heart of policing in America. The promise of AI at this year’s International Association of Chiefs of Police (IACP) Technology Conference focused on automating routine parts of the job, which also happen to be critical steps in the legal process. It’s a similar sales pitch to the one that’s been exhaustively broadcast to businesses in recent years: Let the machines handle the busywork, so you can focus on more meaningful tasks. But in law enforcement, the automation of seemingly innocuous “busywork” — like taking the time to carefully fill out a police report or review a suspect’s case history — can have immense consequences on people’s lives. Among the AI products on offer at the conference’s showroom this May were facial-recognition cameras, automated license plate readers, body cameras, chatbots to field non-emergency 911 calls, gunshot detection platforms, drones, and report-writing tools. As the country has reckoned with law enforcement becoming detached from actual, human police presence in neighborhoods, the industry is continuing to embrace automation. [Image: Fort Worth Convention Center, 2018. https://platform.theverge.com/wp-content/uploads/sites/2/2026/06/shutterstock_1160515732-2.jpg?quality=90&strip=all] The decision-making process itself in police departments is increasingly being handed over to algorithms. A legion of tech startups are now selling AI to police as a kind of automated air traffic control system, a centralized digital brain that can process the vast quantities of data now being collected — oftentimes by other surveillance and automation tools sold by those very same companies — and help departments delegate resources accordingly. Even police aren’t necessarily thrilled about these pitches. “A lot of it is sales gimmicks that don’t actually deliver on what the promise is,” Abrem Ayana, a police captain in Brookhaven, Georgia, told me. In the absence of comprehensive federal oversight or industry standards — and due to the novelty of the tech itself — law enforcement officials like Ayana often have no choice but to take companies’ word that their products are safe and that they work as advertised. Police departments have used technology for decades to analyze data and, in theory, make more informed decisions in the field. In some notorious cases, it’s completely backfired. CompStat and PredPol (short for “computer comparison statistics” and “predictive policing,” respectively), for example, were two early experiments that sought to mitigate fallible human judgement through the use of supposedly unbiased statistics. Instead, they ended up exacerbating the very problems they were meant to solve. But while those early experiments failed to usher in a new era of unbiased policing as their proponents had hoped, human beings were at least still at the helm, making the most important decisions. The sales pitch behind this new wave of AI products is that the mistakes of the past were enabled by a lack of objective, real-time data. AI can, in theory, now help to bridge the gap by ramping up the amount of public safety data that’s collected and the level of analysis to which it’s subjected. Many public safety advocacy groups and legal experts, however, warn that an influx of black box algorithms into law enforcement will erode transparency and accountability at a time when much of the public’s trust of the police is already dangerously frayed. Jason Truppi, a former FBI special agent specializing in cybercrime, told me that police are drowning in a sea of data. Truppi, wearing a pair of Meta Ray-Ban Smart Glasses, spoke quickly and excitedly in sentences peppered with corporate buzzphrases. In late 2020, he cofounded ForceMetrics, a software company offering an “AI-powered decision-assist platform, enabling public safety agencies to increase operational efficiency and better serve their communities in real time,” as described by its LinkedIn page. All of the record-keeping systems that police departments have been using for the past two decades, from emergency call logs to parole record files to body camera footage databases, have, according to Truppi, created a burdensome information overload. “All the systems of record [used by police departments] are essentially antiquated,” he told me. ForceMetrics offers police departments a platform called Velocity, which “uses AI to turn overwhelming amounts of public safety data into clear, actionable insights,” according to the company’s website. In police-tech industry-speak, Velocity is what’s known as a real-time crime center, or RTCC. First adopted by the New York City Police Department over 20 years ago, RTCCs are designed to aggregate police data coming in from multiple streams — like 911 dispatch, CCTV cameras, and license-plate scanners — to provide officers with a summary of what to expect when they arrive on a scene. The theory is that the more real-time data you can give officers, the less likely they’ll be to go in “guts and guns,” as Truppi puts it. It’s a cheeky euphemism for when things go bad and people get killed. In the past, RTCCs were overseen by human analysts whose job was to collect all the incoming digital data, organize it, and send it to the officers on patrol. But as Truppi suggests, the proliferation of new data-collection technologies within policing over the years has made it effectively impossible for any department to stay afloat in the deluge of information. By 2019, the NYPD was collecting around two years’ worth of body camera footage every week, according to the transcript of a 2019 Committee on Public Safety hearing — too much for even the most diligent human employee to meaningfully analyze. Modern RTCCs like Velocity are designed to quickly extract patterns from oceans of data with the goal of improving situational awareness for cops. According to Truppi, the “unfortunate events” that have so disastrously damaged Americans’ trust in police departments in recent years, especially during the pandemic, can largely be attributed to a lack of what he calls “a data-driven approach” to policing. Nina Loshkajian, a fellow at the New York University Center on Race, Inequality, and the Law, is wary of this claim. “The reality is that police departments had already been using predictive algorithms, which companies touted as data-driven, for years before calls to defund the police revved up in 2020,” she told me. “These algorithmic systems did not prevent violent encounters between police and civilians then, and we shouldn’t be tricked into thinking they’ll make a meaningful difference in the future.” Truppi’s company is competing with two of the biggest players in the modern police-technology industrial complex: Motorola Solutions and Axon Enterprise, both of which make not only their own RTCCs, but also many of the data-collection and surveillance technologies they rely on. In early 2024, Axon — originally called TASER — acquired surveillance technology company Fusus to launch a RTCC, which was officially branded as Axon Fusus. By that time, Axon was already a well-known purveyor of stun guns, body-worn cameras, and automated license plate readers. The company also offers a popular AI-powered report-writing tool called Draft One, drones for police departments through a program called Axon Air, and even its own AI chatbot. [Image: https://platform.theverge.com/wp-content/uploads/sites/2/2026/07/268595_AI_policing_SPOT2_CVirginia.gif?quality=90&strip=all] Axon and Motorola are part of a very small group of companies competing to effectively monopolize the entire modern police technology stack, from the collection of data at crime scenes to the strategic decision-making capabilities of AI-powered RTCCs. Police departments today often sign onto multiyear contracts with these providers, who in turn offer free trial periods for new tech, along with what are known as sole-source procurement agreements, which enable them to continue selling new products to departments without having to bid against competing offers from other vendors. In late 2024, Axon launched its AI Era Plan, a subscription that allows customers to pay a flat annual fee to gain access both to the company’s current AI tools, like Draft One, as well as others it might launch in the future. AI Era Plan subscriptions skyrocketed by 140 percent between the first quarter of last year and the same time this year, according to the transcript of a company earnings call with investors: “we are seeing AI move from early interest to a standard part of how large agencies think about their future technology stack,” Axon President Joshua Isner said in that call. “We are determined to become the AI company in public safety, and we are well on our way.” According to the transcript, Axon’s AI product revenue grew 700 percent year over year. While bigger companies like Axon, Motorola, and Flock Safety currently dominate the police technology-industrial complex, it’s facing growing competition from the army of newer tech startups that were exhibiting at the IACP tech conference in Texas. “The entire game of all of these companies is to become the platform for policing,” says Andrew Guthrie Ferguson, a professor at Georgetown University Law School and the author of multiple books on the intersection of policing and technology. “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.” That gold rush has also attracted an influx of outside investors: About one-quarter of attendees on the showroom floor at the conference were from “equity firms looking to invest in the latest tech,” according to Amber Schroader, a tech entrepreneur whom I spoke with in Fort Worth during the event. “That was a surprise.” The sales pitch has been working. Draft One and other AI-powered report-writing tools, for example, have significant appeal at a time when the average police officer spends 40 percent of a typical shift writing reports, according to a 2024 study conducted by Axon. Many of those are for mundane incidents like traffic stops and noise complaints. “We didn’t sign up to sit behind a keyboard,” said John Mackey, a patrol sergeant with Colorado’s Avon Police Department, which uses Field Notes, an AI-powered report-writing tool made by a company called Truleo. “That wasn’t why I became a police officer.” Draft One comes with design features intended to force a degree of human oversight. The system will intentionally leave certain details blank, for example, forcing officers to go in and fill them in manually. The platform is built upon a modified version of ChatGPT trained specifically to generate police reports and that, according to the company, is hallucination-free: “The creativity is turned down to zero,” Noah Spitzer-Williams, senior principal product manager at Axon’s generative AI division, has said. That claim should be taken with a very large grain of salt, however, since even frontier labs like OpenAI (the company behind ChatGPT), Anthropic, and Google have not yet figured out how to completely eradicate hallucination from even their most advanced models. And indeed, in one infamous incident from earlier this year, Draft One wrote that an officer in Utah had morphed into a frog, after having picked up audio from the Disney movie The Princess and the Frog, which had reportedly been playing in the background at the scene. It’s easy to laugh at that incident, but real-world outcomes from AI-written police reports could be deadly serious. When a human o

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