Frameworks map

Frameworks do not replace architecture. They give risk, legal, and engineering a shared checklist aligned to NIST AI RMF or ISO 42001.

Map each control to a pattern on reference architecture patterns you can show in a workshop, not principles alone.

Sponsors use framework language in board packs. Engineers use it to prioritise telemetry, evals, and OpenAI safety best practices.

Pick one primary framework for external messaging, then crosswalk vendor responsible AI programs in an appendix.

Govern covers accountability, policies, and change control for prompts, indexes, and models.

Translate Govern into a RACI for the AI council (NIST AI RMF Govern), a prompt change process in CI, and production readiness (checklist guide) gates.

Auditors ask who approved go-live per production readiness conversation and how HITL overrides are logged.

Your programme office should maintain govern artefacts per NIST Govern, not scatter them across wikis.

Map covers context, use-case boundaries, and data flows per NIST playbook Map function.

Use choosing cloud stack and Copilot coexistence to show where the system starts and stops.

Document prohibited uses and data classes per Microsoft Copilot data protection.

Update maps when you add tools or connect a new system of record.

Measure covers evaluations, monitoring, safety metrics, and operational KPIs.

Run golden set (OpenAI evals) evals before each prompt promotion and track citation rate, unknown answers, and tool safety.

Observability examples show latency via Foundry monitor and OpenAI evals dashboards.

Define thresholds upfront so debates use golden set numbers, not opinions.

Manage covers incident response, human override, decommissioning, and continuous improvement.

human-in-the-loop (OpenAI safety best practices) approval patterns show how writes are proposed then executed after supervisor sign-off.

Incident examples illustrate disable-tools drills per NIST Manage.

Decommission retired pilots from Teams and Entra to prevent shadow usage.

ISO 42001 (standard overview) is an AI management system standard useful when procurement asks for certified process, not only technical controls.

It aligns with production readiness conversation, NIST AI RMF Govern roles, and management review.

Do not claim certification because you read a guide. Show artefacts ISO 42001 expects.

Map ISO clauses to ITIL processes and NIST AI RMF Playbook control IDs to reduce duplicate paperwork.

Each major provider publishes responsible-AI guidance complementing NIST AI RMF and ISO 42001.

Reference vendor programs when aligning with choosing cloud stack anchor.

Use Content Safety and Guardrails as implementation detail, not substitute for evals.

Track transparency when models change (Anthropic scaling policy).

In a 90-minute session, pick one use case from NIST AI RMF and fill a one-page control map.

Each row lists framework control, owner, reference architecture patterns pattern, and eval or log evidence.

Participants leave with assignments aligned to NIST AI RMF Govern intake.

Store output in AWS AI compliance folder the same day.

Translate controls into outcomes: who is accountable, what is logged, how overrides work, and how models change over time.

Avoid jargon without definitions. Say human approval for CRM writes, not only HITL (OpenAI safety best practices).

Provide trend metrics month on month via OpenAI evals, not a launch-day snapshot.

When auditors visit, open AWS AI compliance index first.

Keep a folder per pilot: architecture, data-flow, eval report, Bedrock logs, HITL screenshot, runbook.

Name files so reviewers find NIST Govern vs Measure artefacts quickly.

Redact customer data per data privacy. InfoSec needs realistic event types.

Version folder when prompts change. Auditors compare point-in-time NIST AI RMF Playbook evidence.

Good looks like engineering and risk using the same control IDs in Jira and AWS AI compliance.

Good looks like reference architecture patterns demos matching pilot scoping boundaries.

Good looks like NIST AI RMF accelerating decisions, not duplicate paperwork.

Good looks like retired pilots removed from maps per NIST Manage decommission checklist.

Teams paste NIST AI RMF text into slides without linking to running systems.

Teams claim ISO 42001 alignment with no NIST AI RMF Govern management review.

Teams ignore Map when adding tools, then fail prompt injection reviews.

Teams measure only launch-week quality, then cannot answer OpenAI evals trend questions.