PACT: Can Enterprise AI Assistants Be Trusted Under Pressure?

The PACT (Pressure-Applied Compliance Testing) benchmark addresses a critical gap in enterprise AI adoption by systematically evaluating Large Language Model (LLM) agents' adherence to compliance rules, particularly under various forms of pressure. This research highlights the legal concerns associated with deploying AI in sensitive domains like hiring, healthcare, and finance, where rule violations could have significant repercussions. The PACT framework tests AI agents across twelve regulated enterprise domains and forty-eight scenarios, aiming to identify models prone to non-compliance.

This research is strategically important because it directly addresses the escalating legal and reputational risks associated with the uncritical deployment of AI in regulated industries. Ensuring AI systems adhere to specified compliance rules, even under duress, is foundational for maintaining trust, avoiding regulatory penalties, and sustaining operational integrity in increasingly automated environments.

Corporate AI adoption is expanding into sensitive contexts, including hiring, healthcare, and finance.

Forward consideration, not a verified fact.