#Operating Model

Articles about Operating Model — exploring patterns, best practices, and real-world implementations in production systems.

2 posts tagged with operating model. ← All posts

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Pratik Dhanave · ·7 min read

Standing Up a Governance Function — From Zero to Running

Every idea in this series is worthless until someone builds the function that runs it. The most common failure in AI governance isn't picking the wrong framework — it's never getting past the framework to an operating capability, or building such a heavy one that the organization routes around it. This closing post is a practical path from zero: what to build first, how to make governance an enabler rather than a blocker, and how to grow the function as AI adoption grows. It turns the series into a plan.

Every idea in the series is worthless until someone runs it. A practical path from zero: start with visibility (inventory, then risk-tier, then a minimal owner-assigning policy), build controls highest-leverage-first in runnable layers, and make governance an enabler — the easy path — so it accelerates trustworthy AI rather than blocking it.

#AI Governance#Operating Model#Strategy#Leadership#Risk Management#Accountability
Pratik Dhanave · ·6 min read

The AI Governance Operating Model — Who Owns What

AI governance fails most often not because an organization lacks principles, but because nobody owns them. Fairness, safety, and accountability are everyone's job in the abstract and no one's job in practice, so they fall through the cracks between data science, legal, risk, and engineering. This series is about governance as an operating model you can actually run — and it starts with the unglamorous foundation: clear ownership, defined roles, and the mechanisms that turn good intentions into enforced practice.

AI governance fails from an ownership gap, not an absence of principles. The operating model: decision rights and accountability via the three lines of defense, named roles laddering to an executive owner, and the mechanisms that give them teeth — an AI system registry, risk tiering, and lifecycle gates.

#AI Governance#Operating Model#Risk Management#Accountability

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.