The truth about AI in law enforcement: From body cameras to final reports

Law enforcement has always been a documentation-intensive profession. The sheer volume of audio and video content now created by modern police work, from handwritten incident reports to digital evidence management can be overwhelming. Officers and others who are adopting AI responsibly and implementing it in a variety of use cases, such as AI-powered law enforcement transcription, are seeing real benefits.

Currently, officers spend an average of four to five hours transcribing each hour of recorded content into written text, creating what many departments describe as an unsustainable administrative burden. The scope of this challenge has also expanded dramatically. With 80% of police departments now using body-worn cameras and nearly 240 million calls made to 911 in 2024, the documentation workload has reached levels that strain department resources and officer wellbeing. 56% of officers spend over three hours each shift completing paperwork and reports that could potentially be automated. The human cost is significant, with more than 25% of police officers reporting experiences of depression or burnout.

Artificial intelligence can come in to solve this documentation crisis. Departments implementing AI report writing solutions have saved an average of 54 hours per month on employee time alone, freeing officers to focus on community policing rather than paperwork. The technology has moved beyond simple transcription to optimize how officers document incidents in the field.

From body camera footage to final incident reports, AI tools are becoming essential infrastructure for police departments seeking to manage their documentation requirements while maintaining the thoroughness that effective law enforcement demands.

The rise of AI in law enforcement

Police departments across the country are experiencing what many describe as an AI adoption wave. While officers investigate crimes that increasingly involve AI technology, departments simultaneously recognize that incorporating these same tools can expand their operational capabilities and efficiency. The technology has moved beyond experimental phases to become integral infrastructure for data processing, decision support, and case management.

How AI changes daily police operations

Modern AI systems enable law enforcement agencies to process information faster and with greater accuracy over traditional methods. Deloitte research indicates that cities implementing smart technologies could reduce crime by 30-40% and decrease emergency service response times by 20-35%.

AI for law enforcement can be used in three primary ways:

• Assisting officers with complex tasks
• Expanding human analytical capabilities
• Automating routine processes

The technology serves as what experts call a force multiplier, allowing departments to accomplish more with existing personnel and budgets. Machine learning algorithms analyze patterns in arrests, crime locations, and clearance rates to help predict potential hotspots before incidents occur.

Current AI applications in policing

Law enforcement agencies have adopted AI tools across multiple operational areas according to Deloitte research:

• Facial recognition and biometrics (used by 84% of cities)
• Body cameras and in-car systems (55% adoption)
• Drones and aerial surveillance (46% implementation)
• Crime reporting and emergency apps (39% usage)

Beyond these visible applications, AI powers natural language processing for report writing, autonomous robots for dangerous investigations, and process automation for computer-aided dispatch. The FBI has even implemented AI for video analytics, vehicle recognition, and processing speech samples to detect criminal activity efficiently.

Why transcription has become essential for law enforcement

Transcription has emerged as one of the highest-impact AI applications for police departments. Officers using AI-powered transcription consistently report that it “saves hours of time normally spent on report writing.” When an officer uploads body camera footage, AI can analyze the audio content to produce a structured report draft in minutes rather than hours.

Major crime investigators who once spent entire shifts manually transcribing interview recordings now use automated transcription processes that handle this work in the background. The technology converts unwieldy audio recordings into searchable, organized text files that can be shared, analyzed, and filed as evidence.

For one, Verbit’s transcription solution addresses these specific law enforcement needs by combining AI speed with human expertise, providing departments with secure, CJIS-compliant transcription services that maintain chain of evidence requirements while dramatically reducing documentation time.

AI applications across law enforcement documentation

Police departments nationwide are adopting specialized AI transcription tools to address distinct challenges across different areas of their law enforcement work.

Emergency call processing

Emergency dispatch centers face the challenge of converting chaotic 911 calls into actionable intelligence. Modern AI systems like HARMONY AI process calls in over 190 languages, organizing critical information from high-stress situations. Effective AI technology enables telecommunicators to identify mission-critical keywords such as “apartment,” “fire,” and “screams” and generate summaries that reduce cognitive overload during emergency response.

Body camera and dashboard footage analysis

Officers now routinely narrate situations in real-time, creating audio that AI can process into detailed incident reports. Tools like Axon Auto-Transcribe and Verbit can handle the challenging acoustic environments common in police work, from wind and sirens to multiple speakers and produce accurate transcriptions from bodycam audio. Officers can also search transcripts by keyword with these technologies to locate specific moments in recordings, eliminating the need to review hours of footage manually.

Interview and interrogation documentation

Suspect interviews and witness statements require precise documentation for case development. AI transcription captures every verbal exchange, including subtle details that officers might miss during intense questioning. These systems convert crucial conversations into searchable, formatted documents that investigators can reference throughout case preparation. The comprehensive record strengthens both case accuracy and courtroom presentation.

Incident reporting automation

Report-writing technology connects directly to body cameras, allowing AI to draft structured incident reports from officer narration. The process of course requires human review. Officers can examine AI-generated drafts, add necessary details, and verify accuracy before submission. These transcript editing features are key to using AI transcription successfully. Some departments have reduced incident report completion time by up to 67% using this approach.

Inmate communication monitoring

Correctional facilities use AI systems to transcribe hours of inmate phone calls within minutes, alerting investigators to potential evidence. Advanced tools like WireTap process conversations faster than inmates can make them, even when defendants use coded language or slang. However, this application raises significant privacy concerns, particularly regarding protected attorney-client communications.

Choosing the right approach to transcription for law enforcement

The use cases are many, but law enforcement agencies face a critical decision when selecting transcription methods and solutions. Each approach – AI-powered transcription, human-transcribed, or hybrid transcription – serves different operational needs and accuracy requirements.

AI transcription capabilities and limitations

AI transcription excels in speed and cost efficiency. These cost-efficient systems process hours of recordings in minutes. The technology handles routine documentation tasks effectively, enabling departments to process large volumes of audio content quickly.

However, generic AI systems face notable challenges in law enforcement environments. They sometimes struggle with heavy accents, background noise, or specialized terminology. More concerning for departments building court cases, some AI systems have been documented inserting fabricated content in approximately 1% of transcriptions.

That’s where professional transcription solutions made for law enforcement like Verbit’s AI come into play. Verbit utilizes a domain-trained automatic speech recognition (ASR) model for law enforcement, which is trained on hours of related content and dialogue to perform well even in difficult audio scenarios.

When human transcription remains essential

Court-admissible evidence requires 99%+ accuracy, and formerly human transcriptionists provided this gold standard. Their nuanced understanding of context, accents, and law enforcement terminology ensures precision in critical situations. Perhaps most importantly for legal proceedings, human transcribers can testify about their work if questioned in court — something AI cannot do.

The human element becomes crucial for high-stakes cases where accuracy can determine outcomes and where every word matters for justice. However, law enforcement don’t need to abandon AI to reach the 99% accuracy they need.

Hybrid models: balancing efficiency with precision

Hybrid transcription offers a practical middle ground for many departments. The process begins with AI generating a draft transcript, followed by professional human review. This approach captures the speed benefits of AI while ensuring human oversight for accuracy. Companies like Verbit provide the extra layer of human quality control that law enforcement needs.

Hybrid models prove especially valuable when initial AI screening identifies critical evidence that requires human verification. Departments using this method report significant time savings while maintaining the reliability needed for court proceedings.

A specialized approach: Verbit for law enforcement transcription

Verbit’s technology uses AI trained specifically for law enforcement scenarios. Unlike generic transcription tools, the system is optimized for challenging audio conditions common in police work – from radio chatter to crowd noise. Combined with human review, this specialized approach delivers both operational efficiency and court-ready 99% accuracy.

The solution addresses the unique needs of law enforcement documentation while maintaining the security and compliance standards that departments require.

Contact us to find out more about our law enforcement AI and discover the use cases for law enforcement transcription you can consider.

Security, compliance, and AI ethical considerations

The adoption of AI transcription tools in law enforcement brings with it security requirements that departments cannot overlook. Criminal justice information demands the highest levels of protection, and the technology solutions departments choose must meet rigorous standards designed specifically for sensitive law enforcement data.

CJIS and regulatory compliance: CJIS-compliant transcription services adhere to strict federal security protocols, implementing encryption, access controls, and secure transmission methods to protect sensitive data. These providers conduct background checks and require CJIS-specific training for all staff handling law enforcement contracts. This compliance framework reduces agency liability by ensuring outsourced transcription meets all regulatory guidelines.

Algorithmic bias in documentation: Ineffective AI systems can introduce bias into police documentation, particularly when processing audio from diverse communities. Facial recognition systems demonstrate striking racial error disparities. These disparities raise important questions about AI’s reliability in creating accurate, unbiased reports across different populations.

Human oversight requirements: Effective safeguards must prohibit relying on AI outputs as the sole basis for arrests or enforcement actions. Human oversight remains essential. AI should augment police operations, never replace human judgment. Departments need thorough testing throughout an AI system’s lifecycle to validate performance and mitigate potential bias.

Secure implementation standards: Verbit prioritizes security through end-to-end encryption and secure cloud storage while maintaining compliance with government security standards. Verbit’s AI-powered solution offers secure, scalable transcription specifically designed for complex law enforcement data, so departments can adopt efficient documentation tools without compromising the confidentiality requirements that define responsible police work.

A summary of AI transcription for police and legal needs

AI documentation tools represent a smart solution to law enforcement’s growing administrative burden. Police departments implementing these technologies report significant time savings, which frees officers to focus on community safety rather than paperwork. The benefits extend beyond efficiency gains to improvements in officer wellbeing and case management capabilities.

The choice between transcription approaches requires careful consideration. AI-only solutions offer impressive speed and cost benefits, but many face accuracy challenges in real-world conditions. Human transcription or human quality review on AI-generated transcripts delivers the precision needed for court-admissible evidence. Hybrid models have emerged as an optimal approach, combining AI efficiency with human oversight to ensure both speed and courtroom reliability.

Security considerations cannot be overlooked. CJIS compliance, bias mitigation, and proper oversight must accompany any AI implementation in law enforcement. These technologies should augment operations, not replace human judgment.

Verbit’s hybrid transcription solution, which combines human review and law enforcement domain-trained ASR address the requirements for law enforcement scenarios coupled. This approach delivers court-ready accuracy while providing the efficiency police departments need to manage their expanding documentation requirements.

The volume of body cameras, 911 calls, and digital evidence will continue to grow. Departments that adopt balanced approaches to AI transcription, combining technological efficiency with human oversight when needed, position themselves to meet these demands while maintaining the accuracy and security standards that effective law enforcement requires.

Police departments now have practical tools to address their documentation challenges while preserving the human judgment that remains essential to public safety.

Contact Verbit’s team to receive more guidance as you consider adopting AI for police work and law enforcement needs.

Key takeaways

AI transcription is revolutionizing law enforcement by dramatically reducing documentation time and allowing officers to focus on community safety rather than paperwork.

• Massive time savings: Officers spend 4-5 hours transcribing each hour of audio/video content, but AI solutions save departments an average of 54 hours per month on documentation.
• Domain-trained AI or hybrid models deliver optimal results: Opt for AI that’s domain-trained on law enforcement use cases for speed, but a partner that offers human review options when needed for court-ready precision for critical evidence transcription.
• Multiple applications transform operations: AI transcription powers 911 calls, body cameras, interrogations, incident reports, and jail call monitoring across law enforcement.
• Security and compliance are non-negotiable: CJIS compliance, bias mitigation, and human oversight remain essential safeguards when implementing AI transcription systems.
• Officer wellbeing improves significantly: Departments report reduced burnout and depression rates as AI handles time-consuming paperwork, freeing officers for core duties.

The transformation from manual transcription to AI-powered solutions represents more than just technological advancement. It’s a fundamental shift that enables law enforcement to work smarter, not harder, while maintaining the accuracy and security standards critical to justice.