Authority is growing faster than governance.
Most organizations do not know how much AI they run. Shadow AI connects to company data under employee access, and approved AI gains reach with every new integration. Leaders then govern tools and policies, while the real question stays open: how much authority does each AI hold?
Six gaps keep showing up:
Nobody sizes authority.
Teams approve use cases, and authority expands by default.
Nobody traces its source.
An agent acts on someone’s rights, and few records show whose.
Nobody measures use.
A system may hold L4 and use L2, so oversized access stays hidden.
Authority moves slowly.
Reviews take months, so teams create shadow authority to keep pace.
Promotions rest on technical tests.
A model passes accuracy checks and gains authority without business proof.
Governance sits in a document.
Policies age on a shelf while AI changes weekly.
Five ideas that make authority governable.
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Inherited Authority
Every AI acts under someone’s rights. You need to trace those rights back to a named owner.
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Authority Sizing
You need to set how much authority each AI should hold, based on the risk of what it can do.
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Authority Utilization
You need to compare the authority an AI holds with the authority it uses, and act on the gap.
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Time-to-Authority
You need to track how long it takes to move an AI between levels, because slow approval pushes teams toward shadow AI.
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Business-level Evidence Gates
An AI must earn more authority by proving business results, and it must lose authority when that evidence weakens.
One scale for every AI, from assistant to agent.
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L1
Inform
The AI shares information.
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L2
Recommend
The AI suggests actions to a person.
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L3
Human in the loop
Act on approval
The AI acts after a person approves each step.
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L4
Human on the loop
Act within limits
The AI acts inside set boundaries while a person supervises.
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L5
Human out of the loop
Act and report
The AI acts on its own and reports afterward.
An assistant and an agent sit on the same scale, so one governance system covers both.
A working system your leaders keep after the engagement.
The AI Governance Decision System is a web application built with your team in an advisory engagement or workshop. You can integrate it with your existing systems, data, and identity tools, or run it standalone. It records every authority decision, shows who made it, and tracks utilization and evidence over time. You can import and export your data as CSV.
Start by finding the authority you already have.
Book a workshop to map your known and shadow AI to the five levels and see where authority sits today.