https://sanaamironov.com/tags/ai-governance/AI GovernanceHugoBlox Kit (https://hugoblox.com)enFri, 10 Jul 2026 00:00:00 +0000https://sanaamironov.com/media/sharing.pnghttps://sanaamironov.com/tags/ai-governance/https://sanaamironov.com/publications/serim-2026-llm-identity-risk/Fri, 10 Jul 2026 00:00:00 +0000https://sanaamironov.com/publications/serim-2026-llm-identity-risk/https://sanaamironov.com/blog/ai-governance-as-engineering-work/Sat, 23 May 2026 00:00:00 +0000https://sanaamironov.com/blog/ai-governance-as-engineering-work/<p>AI governance is often described as policy, oversight, or compliance. Those pieces matter, but governance also has to become engineering work.</p> <p>A useful governance process should connect risks to artifacts: model behavior, data quality, system boundaries, logs, prompts, tests, permissions, and human review paths. Without those artifacts, governance becomes a document rather than an operating practice.</p> <p>My current interest is in risk mapping that gives teams practical ways to ask better questions: what could fail, what evidence would reveal it, and what controls can reduce the risk before deployment?</p>