AI tools are already in your agency. The question is whether you're ready to manage them.

Most law enforcement leaders don’t realize they’ve already deployed artificial intelligence. Maybe it’s buried in CAD or RMS. Maybe it’s in a vendor pitch using terms like “predictive analytics” or “automated transcription.” You didn’t sign off on “AI,” but it’s in your tech stack all the same.

That’s not the problem. The problem is when the public, the press, or the courts ask:

“What policy governs this system? Who approved it? Where’s the audit trail?”

If your answer is “We’re figuring that out,” you’re not alone. But it’s not going to hold up much longer.

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Three Questions Every Agency Needs to Answer

1. Do you know which systems you're using that qualify as AI?

Vendors often avoid the word “AI” because it triggers legal and public scrutiny. But if the system makes recommendations, detects patterns, or generates output from large datasets — it likely fits federal and state definitions. If you don’t inventory these systems, someone else will.

2. Have you classified your AI systems by risk?

Not all tools are equal. A system that routes calls is low risk. A system that flags people for follow-up is high risk. Agencies need a framework to separate what’s harmless from what needs oversight — before it becomes a front-page issue or a discovery request.

3. Can you show that your staff are trained and accountable?

In today’s environment, “the system did it” isn’t a defensible answer. Chiefs need to know who’s reviewing outputs, how decisions are logged, and what happens if something goes wrong. Training and HITL (human-in-the-loop) review need to be more than buzzwords — they need to be policy.