AI Risk Management Framework

This question asks whether you have a formal process for identifying and managing risks when building or using AI in your product. An AI risk model is like a safety checklist that helps you spot potential problems - such as biased decisions, privacy violations, or system failures - before they harm your customers or your business. It's your systematic approach to making AI safer and more reliable.

An AI risk model is your insurance policy against catastrophic failures and your ticket to enterprise deals. Without it, you're flying blind - risking discrimination lawsuits, regulatory fines, and reputation damage. Having a documented risk framework accelerates security reviews, demonstrates maturity to investors, and helps you catch expensive problems early. It's the difference between being seen as innovative versus reckless.

The biggest mistake is creating a generic risk document that doesn't address your specific AI use cases. Companies often focus only on technical risks while ignoring legal, ethical, and business risks. Another common error is developing a risk model once and never updating it as your AI capabilities evolve or new regulations emerge.