Turn company policy into agent-enforced rules: a practical framework

Q: What is the condition + action form for a policy rule?

It is a machine-checkable pair like 'if refund > $50 then require manager_approval' — a condition the agent can test and an action it must take (approve, block, or escalate) before acting.

Step 1 — inventory the policy

Start by listing the policies your agent must honor: refund limits, approval thresholds, data-residency boundaries, allowed actions per role. Don't try to code them yet — just make the inventory explicit. Most teams discover rules they assumed were "understood" but were never written down as enforceable statements.

Step 2 — extract condition + action

Rewrite each policy sentence as a condition + action pair:

if refund > $50 then require manager_approval
if data_subject in EU then block transfer outside EU region
if tool == delete_record then require human approval

This is the form an agent can evaluate before it acts. AgentPolicy automates this extraction from pasted policy text, but the discipline matters more than the tool.

Step 3 — map to EU AI Act obligations

For each high-risk rule, note the obligation it supports. A refund-approval gate maps to Art. 14 (human oversight). A data-residency block maps to Art. 9 / Chapter IV (data governance). A logged decision maps to Art. 12. The mapping is a decision-support view of your exposure — it is not a conformity certificate, and it should be validated with qualified counsel.

Step 4 — export and wire

Export the rules file and wire it into the agent's runtime so every run evaluates the conditions. Wire the high-risk rules to human approval or a block, and log every decision. Re-run the extraction after any prompt or tool change, because drift is the rule, not the exception.

What this framework does not do

It reduces obvious failure modes and makes obligations visible. It is not a guarantee that the agent is compliant, and it is not a legal opinion. Conformity stays the deployer's responsibility across the full system.

Authoritative references

EU AI Act (Reg. 2024/1689), Art. 9 / 12 / 14: https://eur-lex.europa.eu/eli/reg/2024/1689/oj
AI Act explorer: https://artificialintelligenceact.eu/
European Commission AI policy: https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai

FAQ

What is the condition + action form for a policy rule?

It is a machine-checkable pair like `if refund > $50 then require manager_approval` — a condition the agent can test and an action it must take (approve, block, or escalate) before acting.

How do I know which rules are "high-risk"?

A rule is high-risk when its failure causes an irreversible or regulated harm — a refund above threshold, a cross-border data transfer, a destructive tool call. Map those to EU AI Act obligations (Art. 9/12/14) and wire them to human approval.

Does mapping a rule to an article make me compliant?

No. The mapping is decision-support that helps you evidence a control. Conformity is the deployer's responsibility and depends on the full system, not on one rules file. Validate the mapping with qualified counsel.

How often should I re-extract rules?

After any prompt or tool change, because the agent's behavior can drift away from the written policy. Treat re-extraction as part of every release, not a one-time setup.

Is AgentPolicy a legal opinion?

No. AgentPolicy helps you extract enforceable rules and see where they map to EU AI Act obligations. It is not a legal opinion, a certification, or a guarantee of conformity.

## Disclaimer

Disclaimer (decision-support, not legal advice): AgentPolicy is a tool that helps teams turn policy text into agent-callable checks and a compliance checklist. It is not a legal opinion, a compliance certificate, or a guarantee that an agent is safe or compliant. EU AI Act conformity depends on the full deployed system and is the responsibility of the deploying organization. Verify current obligations and effective dates with qualified counsel before relying on any timeline.

Try AgentPolicy to convert your policy text into exportable, agent-enforced rules mapped to EU AI Act obligations — try AgentPolicy.