Keep AI-driven results within the authority the organization has established.
AI agents can work across tools, services, and organizations. Whether deployed by you, used by a supplier, or operating through a compromised account, the payments, disclosures, production changes, and obligations they produce remain subject to your organization's authority. Authority Control applies that authority to those results before they take effect.
More agents do not create more authority.
An agent can use new tools, delegate work and try another route. The organization still defines which disclosures, payments and production changes it authorizes. One task may create several consequences, each with its own authority question.
The Scale, Scope and Pace thesis →Different paths can lead to the same result.
Illustrative scenario: an agent assigned to analyze customer data proposes releasing protected data to an external recipient. An export API, collaboration workspace, or another agent could offer different routes to that result. Each route needs its own coverage assessment.
The teal line marks the authority determination before the proposed result takes effect.
Authority Control applies the organization’s authority to that result and returns Permit, Defer, or Block before it takes effect. Each determination leaves a durable record.
An authorized objective does not make every consequential result authorized.
OpenAI’s September 2026 model-misalignment reporting framework includes individual training and evaluation cases in which models used exposed credentials, uploaded files to public services, or created unsanctioned communication paths while pursuing assigned objectives.
While pursuing an authorized task, a system may still propose a consequential result that falls outside organizational authority. Technical capability and task assignment do not by themselves establish authority for that result.
More capable AI. Authority that remains organization-defined.
New AI capability does not itself expand what the organization has authorized. Authority Control applies the organization’s current authority before consequential results take effect.
Where may this model and version be deployed and used?
What consequential results may this agent create on the organization’s behalf?
Which consequential results require additional authority or review as AI use expands?
Model Authority →Frontier Agentic Systems →
Five Eyes cyber leaders warned that AI is increasing the speed, scale, and sophistication of cyber threats and shortening the interval between vulnerability discovery and exploitation. Read the joint statement →
AI security and Authority Control work at different parts of the problem.
helps the organization understand model capability and behavior.
govern who or what can reach systems and tools.
manage operating conditions, manipulation, and technical risk, including prompt injection and unsafe tool use.
evaluates whether the result is within organizational authority before it takes effect.
Together, these controls address technical risk and organizational authority as AI capability grows.
Start with one AI workflow that can create a material result.
Choose an AI workflow that can move money, release data, change production, or create an external obligation. Map the result and its applicable authority, then observe proposed results before choosing enforcement.
New technology changes how work gets done. The organization still decides what it may commit to.
Six applications.
One organizational question.
Connects with other solutions. Identity applies to the account used; Connected Vendors applies if the agent acts for a supplier; Data applies when a proposed result would disclose protected information.