When businesses began outsourcing critical operations to third-party providers in the early 2000s, they needed confidence in external vendors without visibility into their security controls. SOC 2 solved this through independent third-party validation of operational security. It remains the gold standard.

As AI agents now make autonomous decisions, process sensitive data, and interact with customers, we face a similar trust gap: traditional compliance can't assess whether AI will hallucinate, leak data through prompt injection, or cause brand disasters. We need an industry standard for AI agents maintaining the pillars that made SOC 2 universally trusted.

What SOC 2 got right

SOC 2 became the gold standard because it solved three fundamental problems:

→ Independent validation enterprises could trust → Common language between buyers and vendors → Covered the concerns that mattered to buyers to unblock deals

These principles work and we’ve kept them in AIUC-1.

Where SOC 2 falls short - and how AIUC-1 solves it

15 years of applying SOC 2 has also shown its shortcomings:

The result: the trust layer for enterprise AI adoption

By keeping SOC 2’s best practices and evolving on its shortcomings, AIUC-1 is positioned to bridge the trust-gap between AI vendors and enterprises today.

For AI vendors, AIUC-1 is a concrete way to ensure and demonstrate that your AI systems are robust and resilient to the risks unique to AI. A certificate will bring back the focus on building frontier technology instead of spending valuable resources in lengthy compliance and security reviews.

For enterprises, AIUC-1 makes AI adoption possible by offering assurances that all of the most important AI risks have been mitigated, and independent third-parties have tested that these mitigations work in the real world.

Get in touch to learn more about AIUC-1.