As artificial intelligence becomes more integrated into daily policing operations, it is critical that law enforcement leaders distinguish between technology designed for consumer use and technology built specifically for public safety environments. Even then, not all providers are created equal.
Public-facing AI tools like ChatGPT have undeniable value in everyday settings. However, when applied to law enforcement work, these platforms raise fundamental concerns around data security, privacy, and compliance. Law enforcement agencies are held to a much higher standard—and rightly so.
The decision to adopt AI tools in policing must be rooted in one principle above all others: TRUST. Trust between officers and their technology. Trust between agencies and their communities. Trust that sensitive data will not be misused, exposed, or compromised.
Here are three critical factors every agency must evaluate:
- Privacy and Zero Data Retention
Public AI platforms typically retain interactions—sometimes indefinitely—and use the content to refine their models. Even anonymized data can pose risks when aggregated at scale.
For law enforcement, this is unacceptable. Officer conversations with AI must be treated as protected information, just as evidence or interview transcripts are.
Zero data retention policies are essential to ensure that officer interactions are never stored, shared, or used for any secondary purposes.
Audit trails that record access, not conversation content, can provide accountability while preserving confidentiality.
When officers engage with an AI assistant, they must be able to trust that their queries, notes, or report drafts will never be repurposed beyond their original intent.
- Automatic Protection of Personal Identifiable Information (PII)
Officers handle sensitive personal information daily—citizen names, addresses, witness statements, social security and medically sensitive data and more. Any AI platform supporting law enforcement must have built-in, automatic redaction of personal identifiable information (PII) to prevent accidental exposure.
Without auto-redaction, there is a real risk that private citizen data could be mishandled, inadvertently released, or become vulnerable to breaches. This not only jeopardizes individual privacy but also undermines the agency’s credibility and legal standing.
Compliance with privacy standards should not be just a feature; it should be regarded as a foundational requirement.
- National Security: 100% U.S.-Based Development and Hosting
With growing concerns about data sovereignty and foreign access to sensitive information, agencies must also consider where and how their AI systems are built and hosted.
Many public AI platforms operate globally, often with development and server infrastructures spread across multiple countries. This can create vulnerabilities that law enforcement agencies cannot afford.
AI tools used in policing should be:
- Built in the United States, to ensure they are governed by U.S. laws.
- Hosted within U.S. borders, to guarantee that data is not subject to foreign surveillance or interception.
- Operated by U.S. personnel, with security practices that meet or exceed FBI Criminal Justice Information Services (CJIS) standards.
Data security is not only about protecting individual cases; it is about maintaining public trust in law enforcement.
The Bottom Line
Adopting AI in policing is inevitable. In fact, I predict that every officer will have an in-car AI assistant within the next three years. However, this technology must be acquired and deployed responsibly.
Agencies must intentionally consider whether the tools they use protect officer privacy, shield citizen information, and secure agency operations within the most stringent legal frameworks.
At TRULEO, we believe that AI built for policing must go beyond innovation—it must embody the ethical and operational standards that define the profession. That is why our AI assistant is 100% CJIS-compliant, enforces zero data retention, auto-redacts sensitive information, and is built and hosted entirely in the United States.
