Download Now: The Multi-Model Enterprise: Managing Risk When You’re Running OpenAI, Anthropic, And More Simultaneously

Most enterprises didn’t plan to run multiple AI models at once. It happened anyway.

A dev team chose GPT. Legal chose Claude. An EU division picked a regional model for data residency. A SaaS vendor embedded a model no one on the security team has ever reviewed. The result: a sprawling portfolio of foundation models, each with different capabilities, contracts, and data practices — and a governance program that was never built for any of it.

One policy per model isn’t a policy. It’s a patchwork — and patchworks leak.

This ebook gives enterprise security, IT, and AI governance leaders a practical framework for managing a multi-model environment: how to classify model risk consistently, how to build a governance infrastructure that doesn’t have to be rebuilt every time a new model arrives, how to handle vendor risk and procurement, and how to make governed AI easier to adopt than ungoverned AI.

• Multi-model environments are already the norm — and most governance programs weren’t built for them.

• Model-by-model governance doesn’t scale. Inconsistent controls and invisible gaps are the predictable result.

• Not all provider risk looks the same. A consistent evaluation framework makes the differences actionable.

• Model risk classification creates a repeatable process out of what is typically a one-off decision.

• The right governance architecture doesn’t break when you add a new model. It adapts.

• Diversification creates its own concentration risk — if it isn’t managed deliberately.

Download the eBook to learn more.