Why Human Judgment Still Decides Whether Your AI Agents Are Safe

Petar Besalev is the EVP of Cybersecurity and Compliance Services at A-LIGN.

​AI agents are moving out of pilot programs and into production, taking on decisions in procurement, security and customer operations. As that shift accelerates, there is an irony at the center of it: The standards built to govern these systems still depend on humans to validate them.​

The industry has spent the last year asking whether AI will replace compliance professionals. But that’s the wrong question. The right question is who’s accountable when the AI gets it wrong. And right now, the answer is still a human being.​

The conversation has already shifted.​

Not long ago, most conversations in this industry started and ended with “we have AI.” Today, the more useful framing is: “We have people with experience and professional judgment, supported by technology.”​

That shift reflects where the technology actually is, not where the hype says it should be. AI is a genuine enablement tool, making assessments faster and more efficient while removing a meaningful amount of manual work. But efficiency and judgment are not the same thing, and leaders who treat them as interchangeable are setting themselves up for a hard lesson.​

Accountability doesn’t transfer to a model​.

Regulated industries already have a clear answer for what happens when something goes wrong: Someone signs their name to it.​

Under frameworks like the Cybersecurity Maturity Model Certification (CMMC), the affirming official personally attests that an organization’s systems meet the required standard. That signature carries liability under the False Claims Act. No AI system can assume that liability. Only a person can.​

Leaders should treat that as the test for any process they’re automating. If something goes wrong, who is exposed? And can that exposure sit with a model? In almost every regulated context today, the answer is no.​