For most of the generative AI era, enterprises judged AI by what it could do. Could the model summarize a contract, answer a customer, support an analyst or a clinician? That test still holds. It is no longer enough.
A harder phase is underway. Organizations are deploying agents that retrieve sensitive data, call tools and APIs, update records and act inside live business systems. The job has changed from producing content to performing tasks. That changes the evidence enterprises need before they can trust these systems.
When a chatbot returns a wrong answer, someone usually catches it and fixes it. When an agent moves money inside a payments platform, alters a record in a hospital network or pushes code into production, the damage is harder to contain. Accuracy remains essential but accountability is now the harder problem. The enterprise must be able to show what an agent did, which model and code it executed, where it ran, what data it accessed and whether it stayed in
We współpracy z: https://fortune.com/2026/06/23/ai-agents-verifiable-execution-enterprise-trust-najwa-aaraj-tii/
