Artificial intelligence is changing how investigators work. Tasks that once required hours of manual review, such as summarizing reports, sorting through records, and identifying potential connections, can now be completed much faster with AI-assisted tools. 

For someone managing several active cases, those time savings can be significant. Less time spent organizing information may mean more time following leads, coordinating with colleagues, and engaging with the people and communities they serve. 

Still, faster access to information brings new questions. How reliable are the results? What happens when important records are missing? And how can agencies make sure that new technology supports sound investigative decisions? 

These are important considerations as law enforcement explores AI’s growing role in public safety. 

AI Is Changing the Investigative Landscape

Law enforcement agencies are encountering AI from two directions. 

Investigators are exploring tools that can help them review large amounts of information, recognize patterns, and reduce time spent on administrative tasks. Meanwhile, criminals are finding new ways to use the same technology. 

AI-generated impersonations, fraudulent communications, and synthetic media can make it more difficult to determine whether information is authentic. 

According to the FBI’s 2025 Internet Crime Report, the Internet Crime Complaint Center received 22,364 complaints containing AI-related information, with approximately $893 million in associated reported losses. These figures demonstrate how frequently AI is appearing in reported cybercrime, although they do not establish that AI caused every loss. 

The implications extend beyond cybercrime units. Investigators working on financial fraud, organized crime, public safety threats, and other complex cases may increasingly encounter AI-generated content during their work. 

At the same time, AI offers opportunities to support investigations through:  

  • Summarizing lengthy reports and documents 
  • Identifying connections between people, locations, and events 
  • Organizing tips and incoming intelligence 
  • Reviewing large volumes of information 
  • Reducing repetitive administrative work 

Used appropriately, these capabilities can help investigators focus their time where it matters most. Their effectiveness, however, depends on the information available and the processes agencies use to evaluate the results. 

Three Priorities for Responsible AI-Assisted Investigations

Agencies evaluating AI should consider how the technology will fit into their investigative environment. Three areas deserve particular attention: access to information, consistent workflows, and accountability. 

1. Making Relevant Information Accessible 

Technology procurement involves a lot of considerations: budgets, security requirements, technical specifications, vInvestigations often involve information from multiple sources. 

A narcotics case, for example, might include surveillance reports, confidential tips, vehicle records, financial information, and intelligence shared by neighboring jurisdictions. 

When these records are difficult to locate or compare, investigators must spend time piecing together the broader picture. 

A connected investigative environment can make it easier to find relevant information, recognize relationships, and maintain context as a case develops. 

This also supports more effective AI-assisted analysis. Tools that summarize records or identify potential connections need access to appropriate, reliable information to produce useful results. 

Before expanding AI use, agencies should consider whether their systems support secure information sharing and collaboration among authorized personnel. 

2. Keeping Investigative Workflows Consistent

AI-assisted tools can help identify potential leads, but investigators still need clear processes for reviewing and acting on those findings. 

Imagine an AI tool flags a possible connection between two individuals mentioned in separate reports. 

That observation could provide a useful starting point. Investigators would still need to examine the underlying records, assess the context, and determine whether the connection is meaningful. 

Consistent case management workflows help teams document those steps and coordinate their work. They also make it easier for investigators, analysts, supervisors, and partner agencies to understand what has been reviewed, what remains uncertain, and what should happen next. 

As agencies introduce AI-assisted capabilities, maintaining those established practices can help ensure that new information is evaluated carefully. 

3. Maintaining Accountability and Human Oversight

AI-generated outputs can contain errors, overlook relevant context, or express uncertain findings with more confidence than the evidence supports. 

These limitations matter in investigations, where decisions can affect individuals, families, and communities. The National Institute of Standards and Technology’s Generative AI Profile outlines considerations for managing generative AI risks, including governance, documentation, and human oversight. 

For law enforcement agencies, this means developing clear expectations around how AI-assisted information is reviewed and used: 

A phased approach might include: 

  • Investigators should be able to distinguish between original evidence, AI-generated analysis, and findings verified through investigative work. 
  • Agencies should also consider how they will document the information and reasoning behind important decisions. 

These practices help support accountability within the agency. They also matter to the public. 

Community trust is built through consistent, fair, and transparent practices. As law enforcement adopts new technology, maintaining that trust requires careful attention to how tools are used and how decisions can be explained. 

For additional guidance, Kaseware explores these considerations in how to buy and deploy AI without losing control. 

What AI Investigative Readiness Looks Like in Practice

The value of connected information and consistent workflows is already visible in agencies working to modernize their investigative operations: 

A Kaseware case study featuring a multi-jurisdictional drug task force illustrates how improvements to case management can support investigators working across jurisdictions. The task force needed a more efficient way to organize information, coordinate investigations, and prepare case materials. Previously, personnel spent considerable time searching for documents and gathering information from different sources. By adopting a centralized investigative case management platform, the task force improved its ability to organize records, track case activity, and prepare consistent documentation. 

The case study describes benefits that included less time spent searching documents, more efficient preparation of felony case packets for prosecutors, and controlled access to sensitive informant information. 

It also follows an investigation from an initial public tip through a search warrant, arrest, and submission of materials to the district attorney. 

Although the case study does not describe an AI deployment, it offers a useful example of the operational foundation agencies may need as they consider new investigative technologies. 

When information is easier to access and investigative work is well documented, teams are better positioned to evaluate new tools and incorporate them into existing processes. 

Five Questions Law Enforcement Leaders Should Ask

As agencies consider expanding AI use, leaders can begin with a few practical questions. 

1. Can investigators access the information they need? 

Consider whether relevant case records, intelligence, and supporting information are available to authorized personnel when they need them. 

2. How will AI-generated findings be reviewed? 

Establish expectations for verifying summaries, suggested connections, and other outputs before they influence investigative decisions. 

3. Can investigators explain how decisions were made? 

Teams should be able to identify the information supporting a finding and document the steps taken to evaluate it. 

4. Are appropriate security controls in place? 

Agencies should understand how AI tools handle sensitive information, who can access the data and outputs, and how the technology aligns with agency policies. 

5. Will the technology support existing workflows? 

Consider whether a tool makes the overall investigative process more effective, including the work that happens before and after an AI-assisted task. 

These questions can help agencies identify practical opportunities for AI while remaining attentive to operational needs and public expectations. 

Kaseware explores this balance further in how AI is transforming public safety from hype to help. 

Preparing for the Next Phase of AI in Law Enforcement

AI will continue to influence the threats that law enforcement encounters and the tools available to investigate them. 

Its ability to process information quickly offers promising opportunities, particularly for agencies managing growing volumes of records, intelligence, and investigative activity. 

Realizing those benefits will require thoughtful implementation. 

Connected information, consistent workflows, and human oversight can help agencies use AI-assisted capabilities while maintaining the standards expected of public safety organizations. 

The merger of Kaseware and OSINT Combine reflects this approach, bringing together advanced investigative case management with open-source intelligence (OSINT) software and training. These capabilities support a more connected approach to gathering intelligence, managing investigations, and coordinating investigative work. 

For law enforcement leaders, the opportunity is to introduce technology in ways that help personnel work effectively, make informed decisions, and serve their communities responsibly. 

As AI capabilities evolve, those priorities will remain important. 

Build a Stronger Foundation for Modern Investigations

Kaseware helps law enforcement and public safety organizations organize investigative information, manage cases, and collaborate across teams. 

Explore Kaseware’s investigative case management capabilities to learn how a connected approach can support investigative efficiency, coordination, and accountability. 

Request a Kaseware demo to discuss your investigative needs.