AI can help with reading, summaries, and drafts. It can help teams understand long rulemaking documents and identify questions. But drone compliance has a hard boundary: a model must not make the dispatch decision.
A release decision needs to be reproducible. The same mission facts should produce the same result. If a configuration is invalid, the finding should say why. If a person is not current, the system should point to the missing record. If a rule applies, the output should cite the authority.
Summaries are not controls
A summary explains a rule. A deterministic check enforces a condition. Those are different jobs. When a system decides whether a flight may launch, the operator needs an answer that can be inspected, tested, versioned, and defended.
Inputs, rule version, finding, severity, citation, and outcome should be visible. If a rule changes, the operator should know which checks changed and which missions or records are affected.
Where AI can still help
AI can help around the gate. It can assist with research, draft explanations, compare versions, and help humans inspect large evidence sets. The gate itself should remain deterministic.
Sources
Build the record while you keep flying.
Ledger runs deterministic checks before release and keeps proposed Part 108 readiness evidence in shadow mode while you operate under today's authority. See Part 108 compliance software for those deterministic release checks. Part 108 remains proposed; the checks run in shadow mode.