Unpacking AI Use in Law Enforcement Document Completion: How Specific Customization and Aligning with Best Practices Can Make Agencies More Efficient and Effective

With the widespread growth of artificial intelligence products focused on enhancing efficiency across all sectors of industry, it was only a matter of time before they found their way to government, and more specifically, law enforcement. And, being an industry burdened by a never-ending recruiting and retention crisis, what better place to implement this emerging technology, to assist our country's guardians in performing better, while also allowing their leaders to remain good stewards of the public purse. But, with new law enforcement AI products popping up daily, and questions of efficacy and safety emerging from academia and advocacy groups alike, how can law enforcement professionals wade through the multitude of issues in adopting this emerging tech for the betterment of its workforce?

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There are numerous roadblocks which agencies experience when looking to adopt and implement this and other emerging technology.  These roadblocks are found both internally and externally and both must be addressed to ensure agencies can bring on this effective tool optimally.  For the internal obstacles, any cop will tell you our industry is slow to adapt and innovate. The age-old law enforcement adage of “this is how we’ve always done it,” is the bane of any forward-thinking law enforcement officer. This lack of forward thinking though, is also countered with some agencies being too innovative, adopting every and all emerging technology in the field, dumping new programs on overburdened cops, with the technology often only having applicability with certain members of the organization.

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But just as much as law enforcement administrators can create these internal obstacles, we cops are too, what I like to frequently say, “our own worst enemies.”  We often complain about the way things in our industry and organization are done, but the minute a change is made which jostles the apple cart and hurts our “delicate sensibilities” (yes, a shameless Departed reference), our jadedness emerges, and we complain about the change, even when it’s for the best.  To combat these internal barriers, agencies must properly vet new technology solutions, finding what is best for the agency, and when implementing, ensure that there is proper understanding of the product, that robust training is conducted, and that a continued partnership with the technology provider is present.  Otherwise, adoption rates and continued utilization are low, and the tech becomes another unused product, lost in the infinite desktop shortcuts, browser bookmarks, and line items of agency budgets.

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This is where Policereports.ai comes in. As a company founded by a former law enforcement officer, with a team made up of former cops and public safety professionals, we understand these internal burdens and the day-to-day of the job, building our technology platform to touch all aspects of the profession; from the street cop taking a late reported burglary, to the FTO finishing a D.O.R., to the first-line supervisor finalizing the endless quarterly evaluations at shift change, to the investigator combing through a subpoena return, and the Chief writing a monthly activity report to city council.

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At Policereports.ai, we integrate ourselves into the existing agency workflows, partnering with our clients to understand how each section of the organization operates, optimizing the completion of each members’ tasks, the way the agency and its members want it to be completed. We build unlimited custom modules for our clients for each specific task as desired. Our product is not an AI wrap, as offered by other providers; each client gets custom development to ensure their report or documentation output is formatted as desired, rather than a generic response which oftentimes needs to be altered. Our ability to customize for all agencies’ nuances remains a point of pride for the company; we know not every law enforcement agency writes, formats, and completes tasks in the same manner, so this customization for each client is necessary to ensure adoption of use and the most efficient and productive outcomes.

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But how does Policereports.ai address certain concerns from stakeholders outside of the law enforcement organization regarding AI use?  In what has become the seminal study on AI use for law enforcement report writing, No man’s hand: artificial intelligence does not improve police report writing speed, Adams et al. (2024) studied and addressed AI vendors’ claims of increases to efficiency by reducing report writing time.  In the study, the authors conducted a randomized controlled trial of the utilization of AI in police report writing, with a product focused on body worn camera transcription to report generation for patrol officers. Through the study, the authors found a reduction of 29.66 minutes when using the system; however, with a large standard error of 39.62, the reduction in report writing time was statistically insignificant due to the large variability in the data from the trial (Adams et al., 2024).  While the study attempted to control for the many obvious variables present with reporting writing, the discussion highlighted several explanations for why there was not a statistically significant reduction in time.

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For instance, Adams et al. (2024) suggest many agencies utilize templated versions of police reports which already aids in lowering report writing time. Additionally, while the narrative crafting of the report writing process is arduous, the AI system utilized did not also complete various other fields (i.e., property files, crime codes, etc.) within the agency’s record management system, another time-consuming piece of report writing (Adams et al., 2024).  The study and analysis, however, did not discuss the limitations with body worn camera transcription to report generation.

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Beyond the specific agency customization, Policereports.ai offers a multitude of mediums for officers to input data to complete their desired task.  While many providers focus solely on body worn camera audio transcription, Policereports.ai understands this may not always be the best and most efficient way to generate a document. Our platform allows for the ability to dictate live into the system, upload voice memos, insert body camera or audio/video recorded interviews, as well as upload documents and audio for analysis, in order to generate necessary documents. By covering a broad spectrum of workflows, users can more efficiently utilize their skills and resources to better document occurrences.  By not relying solely on body camera transcriptions to generate reports, officers can provide facts and circumstances as desired, in their own voice and style, providing a better and more robust output.

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Additionally, we understand how current technology providers are often engrained in an agency’s culture; our technology solution bridges the gap between technology providers, and has the ability to integrate with them, further enhancing workflow optimization and efficiency, beyond solely report narrative completion. We also complete agency forms which exist outside of records or document management systems, auto-completing forms from officers’ inputs, cutting back on duplicative workflows. In addition to the questions of efficiency raised by researchers, recent literature by organizations such as the Electronic Frontier Foundation (EFF) and the American Civil Liberties Union (ACLU) have highlighted some of the potential pitfalls of AI-generated police reports. These include concerns about the ability to audit AI-generated content and the potential for perpetuating biases in reporting. At Policereports.ai, we take these concerns seriously and have implemented specific measures to address them.

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Unlike some competitors, Policereports.ai is designed with transparency and accountability in mind. Our system maintains a clear record of all user inputs and generated reports, ensuring that reports can be easily audited and verified.  While many jurisdictions commonly consider these draft documents, which usually would not be saved or subject to public records disclosure, Policereports.ai gives all agencies the ability to maintain all iterations of the reports and documents generated. All maintained iterations of the documents are secure and encrypted, and we never train on agency report data, ensuring PII, CJIS, and law enforcement sensitive investigation information is not used within the AI models.  This approach aligns with best practices in AI governance and helps to maintain public trust in law enforcement documentation, especially as legislative bills in multiple jurisdictions are suggesting requirements for this.

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Additionally, we've developed our AI models with a focus on reducing bias. By training our systems on a diverse range of data sources and implementing regular bias checks, we strive to ensure that our AI-generated content is as objective and fair as possible. Additionally, through our customization and with the ability for officers to input their own information, in their style and voice, we do not leave report outputs to be open to interpretation by the AI model, which could potentially insert biases.  We also provide agencies with the ability to customize our models to their specific needs and local regulations, further reducing the risk of inadvertent bias or inaccuracies.  We also build quality assurance checks for agencies’ individual reports and crime types, again better ensuring a more comprehensive product is being submitted by officers.  These findings underscore the importance of developing AI tools that not only increase efficiency but also maintain or improve the quality of police reports. This is where Policereports.ai distinguishes itself as a more comprehensive solution.

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By improving the efficiency of report writing, we enable officers to spend more time engaging with their communities and responding to calls for service. This not only enhances public safety but also contributes to better police-community relations. By ensuring the accuracy and completeness of police reports, we help to strengthen the integrity of the criminal justice system as a whole. As we look to the future of law enforcement, it's clear that AI will play an increasingly important role. However, the success of this integration will depend on our ability to harness the power of these technologies while addressing legitimate concerns about their use. At Policereports.ai, we're committed to leading the way in responsible AI implementation, working closely with law enforcement agencies, community stakeholders, and oversight bodies to ensure that our solutions meet the highest standards of ethics and effectiveness.

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-Chris Ryan is a former law enforcement officer command staff member and the current Chief Product Officer at Policereports.ai

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References: 
Adams, I.T., Barter, M., McLean, K. et al. No man’s hand: artificial intelligence does not improve police report writing speed. J Exp Criminol (2024). https://doi.org/10.1007/s11292-024-09644-7

Guariglia, M., & Maass, D. (2025, July 10). Axon’s draft one is designed to defy transparency. Electronic Frontier Foundation. https://www.eff.org/deeplinks/2025/07/axons-draft-one-designed-defy-transparency

Stanley, J. (2024). Police Departments Shouldn’t Allow Officers to Use AI to Draft Police Reports (pp. 1–6). https://assets.aclu.org/live/uploads/2024/12/Automated-Police-Reports-1291.pdf

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