Q004 — Query Definition¶


Research	R0021 — Prompt engineering definitions
Run	2026-03-25
Query	Q004

Query as Received¶

How do regulated industries such as financial services, healthcare, and aviation currently test and validate AI systems before deployment in production environments?

Query as Clarified¶

Subject: Testing and validation frameworks for AI systems in safety-critical regulated industries
Scope: Financial services (banking/insurance), healthcare (medical devices), and aviation
Evidence basis: Regulatory guidance, frameworks, standards, and published requirements from FDA, FAA, Federal Reserve/OCC, NIST, and EASA

Ambiguities Identified¶

"Test and validate" could mean pre-deployment testing only, or ongoing monitoring. This research covers both.
"AI systems" encompasses ML models, LLMs, and traditional algorithmic systems — regulatory frameworks may treat these differently.
"Currently" implies 2024-2026 practices, which are rapidly evolving.

Sub-Questions¶

What does the FAA require for AI safety assurance in aviation?
What does the FDA require for AI/ML in medical devices (SaMD)?
What do banking regulators (Fed/OCC) require under SR 11-7 for AI model validation?
What framework does NIST provide for AI risk management?
Are there common elements across all three industries?

Hypotheses¶

ID	Hypothesis	Description
H1	Regulated industries have rigorous, specific AI validation requirements	Each industry has detailed, enforceable testing and validation standards for AI systems
H2	Validation requirements are minimal or vague	Regulators have not kept pace with AI and requirements are insufficient
H3	Requirements exist but are adapting and incomplete	Frameworks exist and are being applied, but they were designed for traditional systems and are being extended (sometimes awkwardly) to cover AI