Who decides…
What should an AI agent be allowed to do on its own, and what needs a person's approval?
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The short answer
- Recommendation
- List every action the agent can take and give each the approval of the first rule that applies. The agent never releases a payment, changes supplier bank details or decides about a person; a person approves the exact action for anything risky; reversible changes and own-context reads are allowed and logged.
- Reasoning
- The model will sometimes be fooled by text it reads, so what the agent may do rests on the system around it, never on the prompt. The rules decide in order (GS-25): payments and bank details never (GS-27); decisions about a person never (AG-06); every action needs a person when the agent reads untrusted content, reaches sensitive data and can act outside (GS-24); then changes of access, code outside a sandbox, anything that leaves the organisation, deletes or cannot be undone, or changes Confidential or personal data each need a person.
- Considerations
- The person approving sees the exact action: the message and recipient, the command, the record before and after. A summary is not enough.
- Spending has no approval step of its own. The pack controls it through a tested cap on steps, tool calls, spend and time.
- A read outside the signed-in person's own context is not covered by the rules. Have a person approve it and the Head of Information Security settle the case.
- The approval levels are the pack's defaults, and your own policy may be stricter. An agent that acts is Tier 3 until it is assessed.
The decision, step by step
Select any step for the reasoning behind it and where the pack covers it.
- Start
- Step
- Decision
- Outcome
Keyboard: Tab to a step, arrow keys move along the flow, Enter pins its explanation, + and − zoom, 0 fits the diagram, Esc closes. The text version below has the same content.
Where a step quotes a number, it is the default in the CISO Times pack. Your own standard may set a different one.
Read as text
The same flow written out: each step, its reasoning and where the pack covers it. 20 steps.
Start
An AI feature can now act, not only answer
A feature acts when the model chooses which tools to call, or when its tools can change something. The model will sometimes be fooled by text it reads, so what the agent may do rests on the system around it and never on a sentence in the prompt. P24 treats an agent that acts as Tier 3 until it is assessed, and it runs under a named identity with the least access it needs.
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistDefinitions (rule Agent)
- P24-A02 AI Acceptable Use & Security PolicyUses that are never allowed, and uses that need a senior decision (rule AG-16)
- P25-A02 Generative AI Security StandardAgents and tools (rules GS-22, GS-23)
- P25-A02 Generative AI Security StandardDesign (rule GS-02)
Step
List every action it can take, one row each
For each action write the kind (read, write, send, delete, execute, change access, payment, change supplier bank details, decide about a person), whether one step undoes it, whether it leaves the organisation, the highest data level it touches, and whether personal data is involved. A read counts as undone unless you say it cannot be. For code or commands, say whether they run in a sandbox. An action that fits two kinds is listed twice.
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistAction Review
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistChecklist (rule AP-09)
Decision
Can any tool or path release a payment or change bank details?
This is the first rule and it decides before any other. It covers any tool, connector or path to a payment or to a change of supplier bank details. If you cannot say, answer yes and find out. The rule takes no exception.
- Yes, or not known: Never by the agent: remove the path
- No: Does the action decide a matter about a person?
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistApproval Rules (rule step 1)
- P25-A02 Generative AI Security StandardHuman approval (rule GS-27)
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistChecklist (rule AP-10)
Outcome
Never by the agent: remove the path
Take away the tool or the path. The agent may draft a payment request, and a named person then makes the payment through the normal approval. This is a P24 rule as well, and a feature that can release a payment takes no exception under either pack.
In the pack
- P25-A02 Generative AI Security StandardHuman approval (rules GS-27, GS-30)
- P24-A02 AI Acceptable Use & Security PolicyUses that are never allowed, and uses that need a senior decision (rule AG-16)
- P25-A03 LLM Application Security Review ProcedureWhat takes no exception
Decision
Does the action decide a matter about a person?
A matter about a person is one that affects their job, pay, discipline, credit, access to a service or legal position. No AI output decides such a matter alone. A named person decides after reading the evidence. A use that decides or shapes such a decision is Tier 3 in P24.
- Yes: Never by the agent: it drafts or informs, a named person decides
- No: Does it read untrusted content, reach sensitive data and act outside?
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistApproval Rules (rule step 2)
- P24-A02 AI Acceptable Use & Security PolicyUses that are never allowed, and uses that need a senior decision (rule AG-06)
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistChecklist (rule AP-11)
Outcome
Never by the agent: it drafts or informs, a named person decides
Let the agent prepare the evidence or a draft, and name the person who decides. For a use that only informs such a decision P24 sets Tier 2. For one that decides or shapes it, P24 sets Tier 3 and the use does not start before that decision. Whether the matter also falls under the EU AI Act is for counsel.
In the pack
- P24-A02 AI Acceptable Use & Security PolicyUses that are never allowed, and uses that need a senior decision (rule AG-06)
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistApproval Rules
Decision
Does it read untrusted content, reach sensitive data and act outside?
This is the rule of two, counted over the whole agent, and step 3 of the pack's order: it decides before the checks on single actions. A: it reads content from outside or from anyone who can submit text. B: it reaches data above Public or any personal data. C: it can change state, sends output outside, or acts without a person reading the output first. With all three, a person approves every action. With two, the review records the residual risk in plain words and the approvers read it. If you cannot say whether a property is true, treat it as true until the data flow shows otherwise.
- All three, or not known: A person approves each time and sees the exact action
- Two or fewer: Does it change access, or run code outside a sandbox?
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistApproval Rules (rule step 3)
- P25-A03 LLM Application Security Review ProcedureThe rule of two (rule GS-24)
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistChecklist (rule AP-08)
Decision
Does it change access, or run code outside a sandbox?
Adding a person to a group, granting a role or issuing a key changes access. A command on a server, or code that can reach internal systems or secrets, runs outside a sandbox. Code counts as sandboxed only when it has no network access to internal systems and no secrets. Both kinds need a person who sees the exact change or command.
- Yes: A person approves each time and sees the exact action
- No: Does it send anything outside the organisation?
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistApproval Rules (rule steps 4 and 5)
- P25-A02 Generative AI Security StandardAgents and tools (rules GS-22, GS-23)
Decision
Does it send anything outside the organisation?
An email to a supplier, a message to a customer, a file shared outside, or a web request that carries data out all count. The person approves the exact content and the exact recipient. Judgement: an agent that follows an instruction hidden in a document it read is one way data leaves, so this check does not depend on the model's judgement.
- Yes: A person approves each time and sees the exact action
- No: Does it delete something, or can it not be undone?
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistApproval Rules (rule step 6)
- P25-A02 Generative AI Security StandardOutput handling (rule GS-07)
Decision
Does it delete something, or can it not be undone?
A change is undoable only if one step puts things back as they were. A plain read changes nothing, so answer no for a read. For a write, delete or other change, answer yes when it cannot be undone or when you do not know, because the rules treat an unknown as not undoable.
- Yes, or not known: A person approves each time and sees the exact action
- No: Does it change Confidential or personal data?
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistApproval Rules (rule step 7)
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistAction Review
Decision
Does it change Confidential or personal data?
A reversible change that touches Confidential data or any personal data still needs a person. Special category data is never reachable by an agent, so it does not appear here. The data level column takes the classification levels only.
- Yes: A person approves each time and sees the exact action
- No: Does it change something, or only read?
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistApproval Rules (rule step 8)
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistChecklist (rule AP-07)
Decision
Does it change something, or only read?
A reversible change inside the organisation is allowed, logged and sampled by a person. A read in the signed-in person's own context is allowed and logged, and the data level must still be one the tool is approved for. Judgement: the rules say nothing about a read outside the signed-in person's context, so this flow asks for a person to approve it and for the Head of Information Security to settle the case, because retrieval must return only what the person may already read.
- Changes something, reversibly: Cap steps and spend, log every call, name who can switch it off
- Only reads, in the person's own context: Cap steps and spend, log every call, name who can switch it off
- Reads outside their context (judgement): A person approves each time and sees the exact action
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistApproval Rules (rule steps 9 and 10)
- P25-A02 Generative AI Security StandardData exposure (rule GS-09)
Step
A person approves each time and sees the exact action
The person sees the action itself: the message with its recipient, the command, the record before and after. A summary of the action is not enough. Log each approval with the tool call. Where all three rule of two properties hold, the review runs at Depth 3 with an independent test.
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistChecklist (rules AP-12, AP-16)
- P25-A02 Generative AI Security StandardHuman approval (rule GS-25)
- P25-A03 LLM Application Security Review ProcedureWhat sets the depth
Step
Cap steps and spend, log every call, name who can switch it off
Set a cap on steps, tool calls, spend and time per task, and test it. Judgement: the pack's list of actions that need a person includes spending money, but its approval method has no step for spend except payment, so this flow covers spend through the cap. Log every tool call with its arguments, result, identity and any approval. Name the one person who can switch the agent off in one step.
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistChecklist (rules AP-13, AP-16, AP-17)
- P25-A02 Generative AI Security StandardResource limits (rule GS-21)
- P25-A02 Generative AI Security StandardHuman approval (rule GS-26)
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistApproval Rules
Decision
Is today's approval as strong as the one the rules give?
Compare what happens now with the approval needed for each action. A weaker approval than needed is a gap: for example an email to a supplier that the agent sends without a person looking. If you cannot tell what happens today, answer no.
- Yes: Can one named person switch it off in one step, and was that tested?
- No, or not known: Raise the approval or remove the action, then check again
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistAction Review (rules Approval needed here, Approval in place)
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistInstructions
Outcome
Raise the approval or remove the action, then check again
Mark the checklist item Not met and enter the finding in the findings register, which rates it and sets the due date. A departure from the standard needs an exception approved by the approver its band sets, and a Critical one goes to the board or its equivalent. A path to a payment takes no exception. Judgement: fix it before release where you can.
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistInstructions
- P25-A03 LLM Application Security Review ProcedureExceptions
- P25-A02 Generative AI Security StandardFindings (rule GS-30)
Decision
Can one named person switch it off in one step, and was that tested?
The switch-off stops the feature and revokes its keys and tool access. It is tested before release and again after any change to the feature, and the date of the last test is kept. A switch-off nobody has tried is not yet a control.
- Yes: Get the release signed by the right approvers
- No, or not known: Hold the release until the switch-off is named and tested
In the pack
- P25-A02 Generative AI Security StandardHuman approval (rule GS-26)
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistChecklist (rule AP-17)
Outcome
Hold the release until the switch-off is named and tested
Name the person, write the one-step procedure and test it. Then return to the release decision. Until then the agent does not go live. If it already runs, the AI governance lead may suspend it pending review, and the approvers of its tier decide whether it resumes.
In the pack
- P25-A02 Generative AI Security StandardHuman approval (rule GS-26)
- P24-A02 AI Acceptable Use & Security PolicyThe inventory and suppliers (rule AG-10)
Step
Get the release signed by the right approvers
The approvers of the higher of the use's P24 tier and the review depth sign, and the Head of Information Security signs as well from Depth 2. At Tier 3 or Depth 3 that is the executive decision-maker. Where an approver owns the agent, P24 names who takes their place, and where the top approver owns it, the board or its equivalent decides.
In the pack
- P25-A03 LLM Application Security Review ProcedureWho signs (rule RG-6)
- P24-A02 AI Acceptable Use & Security PolicyUses that are never allowed, and uses that need a senior decision (rule AG-16)
Outcome
Release, and keep the checklist and the next review date
Keep the checklist, the action list and the rule of two result with the feature's other review evidence. Repeat the review at the interval of the feature's depth and after any change of tool, permission or model. A new tool or a wider permission is a change, so the action list is redone then.
In the pack
- P25-A09 AI Agent Permission & Tool-Access Review ChecklistChecklist (rule AP-18)
- P25-A03 LLM Application Security Review ProcedureWhat forces a new review
Practical checklist
- List every action with its kind, whether one step undoes it, whether it leaves the organisation, the data level and any personal data.
- Remove any tool or path to a payment or a change of supplier bank details.
- Keep decisions about a person with a named person; let the agent draft or inform.
- Count the three risky properties over the whole agent; with all three, a person approves every action.
- Give each remaining action the approval its first matching rule sets.
- Set and test caps on steps, tool calls, spend and time, and log every tool call with its approval.
- Raise any approval in place that is weaker than the rules give, or remove the action.
- Name the person who can switch the agent off in one step, and test it before release.
Evidence to have ready
- The action list, with the approval each action needs and the approval in place.
- The checklist and the three-property count for the agent.
- The log of tool calls with arguments, results, identity and each approval.
- The named switch-off owner and the date the switch-off was last tested.
- The release approval signed by the approvers of the higher of the tier and the depth.
Assumptions
- The agent is already an approved use on the AI inventory. An AI system that can act on its own is Tier 3 until assessed, and this flow sets what it may do once it is approved.
- You can list every tool and connector the agent can call and the permission each one holds. If you cannot, that gap comes before any approval question.
- The approval levels shown are the pack's defaults. Your own policy may be stricter, and may add actions the rules do not name. Spending is covered as a judgement, through the cap on spend.
- Nobody approves a use they own. Who signs follows how the organisation is governed, and where the top approver owns the use, the board or its equivalent decides.
Not covered here
- Whether the AI use may go ahead at all, and at which tier. That is “How do we decide whether a proposed AI use case can go ahead?”.
- Who answers for an AI decision and who can stop a use. That is “Who is accountable for an AI decision, and who can stop an AI use?”.
- The full security review of an agent before it goes live. That is “How do we review an LLM feature or an AI agent for security before it goes live?”.
- How to defend the agent against instructions hidden in what it reads. That is “How do we defend an LLM application against prompt injection?”.
Related questions
- How do we decide whether a proposed AI use case can go ahead?
- Who is accountable for an AI decision, and who can stop an AI use?
- How do we review an LLM feature or an AI agent for security before it goes live?
- How do we defend an LLM application against prompt injection?
- How do we test an LLM application the way an attacker would?