A defensible policy isn’t about buzzwords. It’s about structure, clarity, and enforceability.

A growing number of law enforcement agencies are being told: “You need an AI policy.” Some grab a boilerplate and move on. Others draft something internally and hope it covers the bases. But when the public, press, or a legal inquiry puts pressure on that document, most fall apart.

The question is simple: If your AI policy was submitted in discovery, FOIA, or testimony—would it hold?
If not, you’re exposed.

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What Doesn’t Hold Up

Vague Definitions

If your policy doesn’t clearly define “AI,” “automated decision-making,” or “risk,” you can’t enforce it—and neither can anyone else.

One-Size-Fits-All Rules

Treating a dispatch tool the same as a suspect analysis algorithm is a mistake. Courts and oversight bodies expect different levels of scrutiny for different types of risk.

No Assigned Oversight

A policy that says “staff will review outputs” without naming roles, workflows, or logs isn’t a policy. It’s a placeholder.

No Reference to Contracts, Vendors, or Suspension

If your policy doesn’t link to your procurement terms or include language about system deactivation during investigation, it won’t survive a real-world failure.

What a Strong Policy Includes

• Definitions that match federal and state frameworks (not just marketing terms)
• Risk-based governance that separates low-risk tools from high-risk deployments
• Assignment of roles (command, legal, IT, HITL, vendor)
• Kill switch and audit protocols for incidents, errors, or complaints
• Appendices and checklists that make the policy operational—not theoretical