Enterprise Governance, Compliance, and Human Review
Governance is the system that decides who may take which risk with whose data. Convert policy and regulatory obligations into owned technical controls. Classify data and map it across prompts, tools, storage, logs, and review. Design human review from risk, authority, and reversibility. Evaluate bias, fairness, transparency, and contestability in context. Build evidence for approval, monitoring, incident response, and audit. A healthcare team proposes a Claude workflow that summarizes patient messages, recommends a routing category, and drafts a response. The design document says: "The model does not retain data, all outputs are reviewed by a human, and the system complies with HIPAA." None of those statements is an architecture. Data may appear in API payloads, files, caches, batch storage, logs, traces, support systems, and reviewer tools. "Human review" says nothing about reviewer qualification, evidence, workload, or authority. Compliance depends on the specific use, contracts, configuration, region, controls, and legal analysis. An architect cannot declare it with one sentence. The right response is not automatic rejection. It is a governed design with a data map, risk decisions, control owners, evidence, and escalation to security, privacy, legal, clinical, or compliance experts where required. This lesson teaches architecture judgment. It is not legal advice. Governance begins by identifying: decision or action the system influences. people who can benefit or be harmed. data classes…
Enterprise Governance, Compliance, and Human Review: Governance is the system that decides who may take which risk with whose data.
This free lesson is part of the AI Engineering from Scratch curriculum. Read the full explanation, run the lesson code, and verify the result in the interactive reader or from the repository source.
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