How artificial intelligence could help police departments reduce administrative work and give officers more time to focus on investigations.
Artificial intelligence is becoming a bigger part of the conversation around policing. There is plenty of discussion about how it could transform investigations, automate processes and change the way police departments operate. At the same time, concerns around accuracy, bias and the reliability of AI-generated information are raising important questions about how the technology should be used.
For police departments already managing heavy workloads and limited resources, however, the most useful applications of AI may be far more practical.
Rather than using AI to make investigative decisions or replace experienced officers, there is an opportunity to reduce the administrative work that takes up valuable time.
Whether it is a large metropolitan department managing hundreds of investigations or a small rural agency where officers take on several responsibilities, the challenge is often the same. There is more work to do than there are hours available.
The question for police chiefs and department leaders is therefore less about what AI could do instead of their officers, and more about how it could help them make better use of the resources they already have.
Start with the operational problem
Police departments have invested in technology for years, often with the promise of improving efficiency and reducing workloads. While some systems have delivered genuine improvements, others have introduced additional processes, administration and training requirements.
AI needs to be approached with the same level of scrutiny.
Before introducing a new capability, departments should consider what problem it is intended to solve. Will it reduce the time spent on routine tasks? Make information easier to access? Help investigators work through evidence more efficiently?
These are the areas where AI could offer immediate practical value.
There are several parts of an investigation where officers spend considerable time organizing, reviewing and processing information. Much of that work is necessary, but not all of it requires the same level of professional judgment as interviewing a witness, assessing evidence or making an investigative decision.
That creates opportunities for AI to support existing workflows without taking responsibility away from the officer.
- Reduce the time spent reviewing interviews
A victim or witness interview involves considerably more than asking questions and recording answers.
Officers need to listen carefully, establish a sequence of events, identify inconsistencies and recognize information that may require further investigation. They also need to consider the circumstances of the person being interviewed and adapt their approach accordingly.
These are skills developed through training and experience, and they remain essential to a good interview.
However, the work does not finish when the interview ends.
Recordings may need to be reviewed, notes prepared, key details identified and information organized before the investigation can progress. An hour-long interview can create several additional hours of work, particularly when multiple interviews are involved.
AI-generated summaries could help reduce some of that administration by identifying important topics, names, locations, dates and actions discussed during an interview.
Rather than starting from scratch, an investigator would have a structured overview to review and verify against the original recording.
For smaller departments, this could be particularly useful. An officer may need to conduct an interview before returning to patrol or responding to another incident. Reducing the time spent preparing and reviewing interview notes would allow them to move on to other responsibilities sooner.
The same benefits apply to larger investigations, where officers may need to review information from dozens of interviews.
In both cases, the original recording remains the primary source, with the officer responsible for checking the accuracy of any AI-generated information.
- Help identify information that may have been missed
Even experienced investigators can find it difficult to cover every relevant subject during an interview.
Conversations rarely follow a fixed structure. Witnesses may move between events, introduce unexpected information or remember important details later in the discussion.
Although officers often work from investigative plans, procedures or interview checklists, keeping track of everything while maintaining a natural conversation can be challenging.
One potential application of AI is to provide prompts when a relevant subject or required area of questioning appears to have been overlooked.
For example, if an interview involves a series of events but the officer has not established a particular time or location, an AI-assisted system could highlight that missing information for consideration.
The intention would not be to direct the interview or determine which questions must be asked. Instead, it would provide an additional check that the investigator could use when appropriate.
This could be useful for officers who conduct interviews less frequently or work in departments without dedicated investigative specialists.
Any prompts would still need to be assessed by the officer, who is best placed to understand the context of the conversation and decide whether further questioning is necessary.
- Make transcripts easier to work with
Automatic transcription is already helping investigators reduce the time spent manually documenting interviews and reviewing recordings.
However, producing a transcript is only part of the process. Officers still need to work through the information, identify relevant details and determine what requires further investigation.
AI could make transcripts more useful by helping investigators locate and organize information within them.
For example, it could assist with identifying:
- People, vehicles and locations mentioned during an interview.
- Important dates, times and sequences of events.
- Information that may require further investigation.
- Differences or inconsistencies between accounts.
- Evidence referred to during an interview that has not yet been obtained.
For an investigator reviewing several witness accounts, being able to locate references to a particular person, vehicle or location could save considerable time.
It may also help identify connections between interviews that would otherwise require extensive manual review.
There are limitations, of course. Transcription errors, unclear speech and differences in how people describe events can all affect the accuracy of AI-generated analysis.
For that reason, transcripts and AI-assisted findings should be treated as tools for reviewing evidence, rather than substitutes for the original recording.
Officers must still be able to return to the source material to confirm what was said and assess its significance.
- Manage growing volumes of digital evidence
Digital evidence is now a routine part of many police investigations.
Body-worn camera footage, surveillance video, photographs, mobile phone recordings, audio files and social media content can all contain information relevant to a case.
While access to this material can help investigators establish what happened, it also creates a considerable review workload.
An investigation involving several hours of video footage, for example, may require officers to spend significant time locating a relatively short sequence of events.
AI-assisted analysis could help investigators manage this process by identifying potentially relevant content, grouping similar material and making large collections of evidence easier to search.
This might include locating references to particular words or phrases in audio recordings, identifying objects within video footage or highlighting files that appear relevant to an investigation.
Such capabilities could help officers prioritize the material requiring closer examination, particularly when dealing with large volumes of information.
However, identifying something as potentially relevant is not the same as establishing its evidential significance.
AI can help direct an investigator’s attention towards material worth reviewing, but the officer must still assess what that material shows and how it relates to the wider investigation.
- Support the assessment of digital evidence authenticity
AI is creating opportunities to improve the way investigators work with digital evidence, but it is also making that evidence more difficult to assess.
Images, audio and video can now be manipulated or synthetically generated using increasingly accessible tools. As a result, investigators may encounter material that appears genuine but does not accurately represent what happened.
This creates an additional challenge for departments already dealing with growing volumes of digital information.
Alongside helping officers review evidence, AI-based tools could also assist in identifying indicators of manipulation or synthetic content.
For example, a video submitted during an investigation may contain visual or technical characteristics that warrant further examination. An automated assessment could help flag those concerns so that the appropriate checks can be carried out.
However, AI detection tools are not definitive. They can produce incorrect results, and the absence of a warning does not establish that a file is authentic.
Any findings need to be considered alongside other available information, including the file’s origin, metadata, provenance and chain of custody.
This is where the distinction between analyzing evidence and establishing trust in that evidence becomes particularly important.
AI may help investigators identify material that deserves closer attention, but confidence in digital evidence also depends on being able to demonstrate where it came from and whether it has changed.
Why this matters for smaller police departments
The potential benefits of AI are relevant to police departments of all sizes, but smaller and rural agencies face particular operational challenges.
Larger departments may have access to dedicated digital forensics teams, intelligence analysts, specialist investigators and technical support.
Smaller agencies often have to manage many of the same responsibilities with far fewer people.
An officer might respond to an incident, interview a witness, collect evidence, prepare a report and continue with regular patrol duties, all within the same shift.
In these circumstances, reducing administrative work could make a noticeable difference to how available time is used.
However, smaller departments also need technology that is practical to implement and straightforward to operate.
AI capabilities should not require complicated systems or extensive technical resources before officers can benefit from them.
Departments also need confidence in how the technology works. AI-generated information should be clearly identified, original evidence must remain accessible and officers should be able to review and verify any automated findings.
The ability to control which AI capabilities are used, and how they fit within departmental policies and procedures, will be equally important.
Technology is most valuable when it supports the way officers work rather than creating additional tasks for them to manage.
Keeping officers in control
There is a difference between using AI to assist an investigation and allowing it to make investigative decisions.
AI can help organize information, produce summaries, identify patterns and highlight material that may require further attention. These capabilities could reduce some of the time officers spend working through routine processes.
But policing involves decisions that cannot be made on the basis of automated analysis alone.
Witness accounts may conflict, information may be incomplete and circumstances can change as an investigation develops. Officers need to consider the wider context, apply their training and make judgments based on the evidence available.
AI-generated outputs can also contain errors or overlook important details, making human review an essential part of any investigative application.
For departments considering AI, maintaining that oversight should be a fundamental requirement rather than an additional safeguard introduced later.
The objective should be to give officers better access to information and more time to use their expertise effectively.
Giving officers more time to investigate
The discussion around AI in policing often focuses on major technological developments and what they could mean for the future of law enforcement.
Yet some of the most useful improvements may come from relatively straightforward changes to existing investigative processes.
Reducing the time needed to review an interview, helping an officer locate relevant evidence or making it easier to identify information requiring follow-up could all contribute to more efficient investigations.
Individually, these improvements may seem modest. Across multiple officers, investigations and departments, however, the time saved could be substantial.
For police agencies managing increasing demands with limited resources, that additional capacity is valuable.
AI will not remove the need for experienced investigators, professional judgment or reliable evidence. But used appropriately, it could reduce some of the administrative burden that prevents officers from spending more time on the work that matters.
Ultimately, the value of AI in policing should be measured by how effectively it supports officers and improves investigative processes, rather than how many tasks it can automate.
About Mea Digital Evidence Integrity
The Mea Digital Evidence Integrity suite of products has been developed by UK based consultancy, Issured Ltd. Benefitting from years of experience working in defence and security, Issured recognised the growing threat from digital disinformation and developed the Mea Digital Evidence Integrity Suite of products to ensure digital media can be trusted.
MeaConnexus is a secure investigative interview platform designed to protect the evidential integrity of the interview content. With features designed to support and improve effective investigations, MeaConnexus can be used anytime, anywhere and on any device, with no need to download any software.
MeaFuse has been designed to protect the authenticity and integrity of any digital media from the point of capture or creation anywhere in the world. Available on iOS, Android, Windows and MacOS MeaFuse digitally transforms the traditional chain of custody to ensure information is evidential.
Disclaimer and Copyright
The information in this article has been created using multiple sources of information. This includes our own knowledge and expertise, external reports, news articles and websites.
We have not independently verified the sources in this article, and Issured Limited assume no responsibility for the accuracy of the sources.
This article is created for information and insight, not intended to be used or cited for advice.
All material produced in the article is copyrighted by Issured Limited.
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