Technology Innovation Institute: AI agents need proof, not promises

Dr. Najwa Aaraj, Chief Executive Officer (CEO) at the Technology Innovation Institute (TII), has a PhD with Highest Distinction in Applied Cryptography and Embedded Systems Security from Princeton University (USA), and has extensive expertise in applied cryptography, trusted platforms, security architecture for embedded systems, software exploit detection and prevention systems, and biometrics.

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 inside approved limits.

Agents collapse the distance between software output and business consequence. A model that recommends an action carries one kind of risk. An agent that takes the action carries another. As agents reach into email, databases, code repositories and financial workflows, they increasingly function like non-human insiders. They have no intent, yet they can accumulate privileges, spread errors and create exposure at machine speed.

Traditional oversight was not........

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