RAIER02-BP02 Summarize critical information and review with appropriate internal stakeholders

Pull together your release documentation into one package that includes your use case definition, risk assessment results, how you did on your release criteria tests, dataset quality reports, and system design details. Organize everything into a single source of truth that gives decision-makers the information they need to make an informed choice about releasing your system.

Check that you've addressed risks across responsible AI areas including safety, fairness, privacy, security, robustness, veracity, explainability, transparency, controllability, and governance. Document what mitigations you put in place and make sure they tackle the specific risks you identified earlier in your process.

Calculate a single readiness score that combines your confidence in meeting the release criteria. Start with your statistical confidence that the quantitative criteria will pass (using methods from PG-SC03-BP03). This gives you one clear number that shows overall system readiness for release.

Write an executive summary that hits the highlights including your key findings, whether you passed or failed each release criterion, what risks are still left after your mitigations, and a clear recommendation about whether you should go ahead with the release. Back up your recommendation with reasoning that stakeholders can understand.

Set up review meetings with internal teams like your legal experts, technical leads, risk management teams, compliance-aligned teams and business owners. Walk them through your findings and get their input on whether you're ready to release, since they might catch issues you missed or have concerns you have not considered.

Write down your final release decision and update your system registry with whether it's a go or no-go, why you made that decision, who signed off on it, and conditions or monitoring requirements you'll need to follow after release.