In Depth
Enterprise buyers face a hard problem. Every AI vendor says its agent is safe, and none of them can prove it in a way a security team can actually compare. "Trust us" does not survive procurement. The Agent Trust Score exists to replace that assurance with evidence. It compresses many signals about how an agent behaves into one number on a fixed scale, so a buyer can read it the way they read any other trust signal, and a vendor can point to something concrete instead of adjectives.
The score runs from 0 to 100, and higher is safer. Ollive groups the range into three bands: Weak for 0 to 49, Moderate for 50 to 74, and Strong for 75 to 100. The band gives the number a plain-language reading. An agent that scores 76 is Strong. One that scores 40 has real work to do before an enterprise should rely on it.
Five inputs shape the score. Autonomy is how much the agent acts without a human in the loop. Domain is the stakes of where it operates, from low-risk content to clinical care. Data sensitivity is whether it touches PHI, financial records, or other regulated data. Failure modes capture how exposed it is to hallucination, bias, injection, and leakage. Governance maturity is how well the controls around it are defined, owned, and operated. The first four describe how much could go wrong. The last describes how well that is being managed, and because governance is something a vendor can change, it is one of the main levers for raising the score.
The score is built from evidence rather than a self-report. It reflects how the agent actually behaves under adversarial red-teaming, with measured failure rates behind the number. A strong score means the agent held up under testing.
What It Looks Like
A vendor takes an agent through assessment ahead of a big enterprise deal. The agent handles customer messages with a human approving anything sensitive, works in a low-stakes domain, and has documented controls, so it earns a Strong score. A second agent that autonomously books appointments and messages patients, touches PHI with no approval step, and has thin governance lands in the Weak band. The contrast shows the vendor exactly where to invest to earn trust: add a confirmation step, document the controls, and narrow what the riskier agent can do on its own. When the deal comes, the vendor can hand the buyer a Strong score backed by test results instead of asking them to take its word.
Why It Matters For AI Vendors
The score's job is to build trust with the enterprise customers who decide whether your agent ships. Their security and procurement teams are being asked to deploy agents into their own environments, and their own name is on the line if one misbehaves. A single, evidence-backed score they can read at a glance, and compare across vendors, is far more persuasive than a deck full of reassurances. It gives the buyer a reason to say yes, and it gives you a defensible answer when they ask how they can know the agent is safe.
It is also a roadmap you control. Because the score responds to real changes, a vendor can raise it on purpose: add human review on a high-stakes action, mature governance, tighten the agent's scope, and watch the number climb. That turns "make the agent more trustworthy" from a vague goal into a set of concrete moves with a visible result.