Definition
Actor intelligence is evidence about who or what is driving an interaction with an application, combined with the context needed to act on it. The "actor" is whatever is in control of the interaction at that moment: a person, a person working with an AI assistant, an autonomous agent, or something the available evidence cannot determine.
Actor intelligence differs from identity. Identity answers "which account is this?" Actor intelligence answers "what kind of participant is operating that account, or this request, right now, and how do we know?"
Why the category exists
For most of the web's history, applications could treat an authenticated session as a person. Automated traffic was something to detect and usually stop. That model breaks down once legitimate software agents start browsing, calling APIs and invoking tools for the people and companies that run them. An application now needs to tell apart:
- People who should get the normal experience.
- People using AI assistance, which may be welcome, restricted or simply disclosed depending on the workflow.
- Agents that deserve structured access, such as an API or a machine-readable response.
- Interactions where the evidence is too thin to say.
Our post Human, AI-assisted or agent: a practical taxonomy for application traffic explains these four groups in detail.
Without that distinction, teams fall back on blunt tools: block everything that looks automated, or allow everything that authenticates. Both create problems. The first breaks legitimate integrations. The second lets high-impact actions run with less context than anyone intended.
Components of actor intelligence
Signals
The raw inputs: request signatures, protocol details, declarations from clients, and interaction signals from browser sessions. Which signals exist depends on where the integration runs.
Classification with a basis
A conclusion such as Agent or Human is only useful if it states what it rests on. Good actor intelligence always reports the evidence basis: verified, declared, inferred or unknown.
Analytics
Patterns over time and by route: which parts of the application see agent traffic, how much is unknown, and how those numbers change after a release.
Decisions
The application's own policy for each route and risk level. Actor intelligence informs these decisions; it does not make them on its own.
How it relates to bot detection
Bot detection is mainly adversarial: it aims to find and stop abusive automation. Actor intelligence is broader. It treats automation as a normal participant that may be legitimate, and it treats AI-assisted humans as their own category. It also gives Unknown a first-class place instead of forcing every interaction into "bot" or "not bot".
Common misconceptions
More signals always mean more certainty. Signals of different strength should not be averaged into one score. A verified signature and an inferred behavior pattern are different kinds of evidence.
Actor intelligence should decide automatically. The value is in giving the application owner reliable context. The owner decides enforcement.
Actor intelligence in Proof of Actor
Proof of Actor packages actor intelligence as three capabilities: Detect, Understand and Route. Results are always one of four classes with an explicit basis, teams start in observation mode, and policies run in the application's own code. Learn more on the product page or apply for early access.