Governance determines whether a generative AI program remains a set of pilots or becomes a durable capability. I treat governance as engineering work. The goal stays simple. The system should behave within policy, every day, under change.
I define governance by design as the practice of encoding policy into build and runtime controls that enforce access, constrain actions, capture evidence, and measure drift. Policies become executable rules. Evidence becomes a byproduct of normal operation. Teams ship faster when governance runs as part of delivery.
Enterprises already understand this pattern. Payment systems embed controls for fraud and chargebacks. Customer data platforms embed consent and retention. Generative AI needs the same approach because it touches data boundaries, produces content, and increasingly takes actions through tools.
Adnan Masood
Start with a threat model that reflects real usage
