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04.3.25 —

The Challenges I Faced as an Investigator—And How AI Can Help

As digital evidence proliferates and comes from increasing sources, law enforcement agencies are increasingly pressured to find new ways to tackle this challenge while facing staff shortages and limited budgets. Artificial intelligence (AI) solutions have become advanced and secure enough for the public sector to adopt to enhance investigations, streamline workflows, and combat crime more efficiently. 

In a recent interview, I shared my insights as a former homicide investigator on how AI transforms investigative work, the challenges agencies face in adopting these technologies, and the future of AI-driven law enforcement. 

Challenges in modern policing

While serving as an investigator with the Antioch Police Department (APD) in Northern California, I experienced firsthand many of our agency’s challenges, which are not unique to APD but ubiquitous across the country. These included hurdles such as staffing shortages and technological gaps. 

During my decade-long tenure, the number of officers remained nearly the same despite a 30% increase in the city’s population and rising crime rates. Investigators like me had to prioritize cases, often focusing on violent crimes over property crimes due to limited resources. This prioritization was an unfortunate result of a lack of resources, leading to delays in solving those cases. 

Another significant challenge was keeping pace with criminal technology. Investigators had to sift through large amounts of digital evidence, including mobile phone data, social media records, and extensive surveillance footage. Traditional policing methods need to evolve so that digital evidence review is more streamlined and less time-consuming for modern investigators. 

AI’s role in streamlining investigations

AI-driven tools are now available to assist law enforcement in handling the massive influx of digital evidence. These technologies can:

  • Analyze hours of surveillance footage in minutes, identifying critical moments or matching suspects to known images. This enables investigators to focus on solving the crime rather than other time-consuming tasks. 
  • Extract and organize data from mobile devices and social media, reducing manual review time so they can track down the suspects faster and make connections they couldn’t otherwise. 
  • Assist in redacting sensitive information from video and audio recordings for legal and public transparency, enabling greater trust by showing the efficacy of the agency’s efforts to solve crimes and keep their communities safe. 

For example, there was a high-profile homicide case that took over a year to solve. If investigators had AI tools, they could’ve identified a key suspect’s vehicle from surveillance footage much earlier, potentially reducing the investigation timeline by several months and saving significant resources.

Ensuring security and scalability

Security concerns are a major factor when implementing new technologies in law enforcement. Solutions like Veritone’s iDEMS (Intelligent Digital Evidence Management System) comply with strict security protocols such as CJIS (Criminal Justice Information Services) and FedRAMP (Federal Risk and Authorization Management Program), ensuring that sensitive data remains protected.

Another critical aspect is scalability. Cloud-based solutions, like those hosted on Amazon Web Services (AWS), provide the flexibility agencies need to handle high-profile homicide cases and smaller-scale investigations efficiently.

Addressing resistance to AI adoption

While AI presents clear benefits, some law enforcement professionals remain skeptical. Concerns range from data security to the reliability of AI-generated insights. Integrating new technology no doubt requires trust, and agencies must ensure that AI enhances human decision-making rather than replacing it. Best practices for implementation include:

  • Ensuring compatibility with existing systems.
  • Adhering to legal and ethical guidelines.
  • Keeping a human in the loop to verify AI-generated leads.

The Future of AI in Law Enforcement

AI-driven tools will continue to evolve, further improving law enforcement efficiency. In the next five to ten years, we can expect AI to:

  • Automate more aspects of digital evidence analysis, allowing officers to focus on strategic decision-making.
  • Enhance predictive policing by identifying crime patterns and trends.
  • Improve transparency and accountability through automated redaction and documentation tools.

Ultimately, AI is becoming an essential force multiplier for law enforcement agencies, enabling them to solve more cases with fewer resources while ensuring justice and public safety remain top priorities. Law enforcement can enhance its investigative capabilities by embracing AI responsibly and securely and better serve their communities.