Policy Exception Request Preparation Agent

A policy exception request preparation agent is an AI agent for hr operations & shared services that when someone asks for something outside policy (extra leave carry-over, a remote-work arrangement the policy does not cover, an unusual working-hours change), it gathers the relevant policy text, past exceptions of the same type at aggregate level, and the options open to HR, so the human has the full picture in one place.

How does the policy exception request preparation agent work?

What flows in, what the agent does with it, where a person decides, and what comes out.

  1. Reads from

    Exception request · Relevant policy text and version · Aggregate log of past exceptions · Requester's location, entity and role type

  2. AI agent · runs when someone asks for something the policy does not cover

    Policy Exception Request Preparation Agent

  3. A person decides

    HRBP or Head of People decides with the manager

  4. Produces

    Decision brief with the options open to HR · Anonymised precedent counts · Draft reply only after the decision is logged · Exception log entry

What does the policy exception request preparation agent do?

When someone asks for something outside policy (extra leave carry-over, a remote-work arrangement the policy does not cover, an unusual working-hours change), it gathers the relevant policy text, past exceptions of the same type at aggregate level, and the options open to HR, so the human has the full picture in one place.

What does it produce?

A decision brief with the request, the policy, comparable precedent (anonymized counts, not names), options and consistency notes, plus a draft reply once the human decision is recorded.

Who decides?

The HRBP or Head of People, with the manager, decides on the exception. The AI never recommends granting or refusing it and only drafts the reply after the decision is logged.

What systems does the policy exception request preparation agent connect to?

Examples of the kind of systems this agent would read from or write to, so you can picture it in your own stack. The actual set is whatever you run.

  • Case management

    request and exception log

    ServiceNow HR Service DeliveryZendesk
  • Policy library

    policy text

    ConfluenceSharePointGoogle Workspace
  • HRIS

    location, entity, role type

    WorkdaySAP SuccessFactors

What data does it need?

  • policy library
  • exception log with categories and outcomes
  • employee context needed for the request (location, entity, role type)

How would you measure it?

time from request to decision, monthly, by exception type; briefs rated complete by the decider; same-type exceptions decided consistently, reviewed quarterly

What does a first proof look like?

Choose one exception type with a decent history, such as leave carry-over. For a month of new requests, the HRBP gets the brief before deciding, then rates whether it was complete and neutral.

You'd call it working when

It saved research time, precedents were counted not named, and no brief nudged toward an answer.

What usually goes wrong?

  • Exception log too thin or untagged to give real precedent.
  • Requesters include health or family reasons; the brief must not carry them beyond who needs to know.
  • Options phrased so one obviously 'wins'; that is a recommendation in disguise.

What are the guardrails?

  • Never recommends granting or refusing.
  • Precedent shown as anonymized counts, never names.
  • Health or family reasons are seen only by the decider, not stored in the brief.
  • Reply drafted only after the decision is logged.
  • Works council or representatives consulted where exception categories touch collective terms.

What leaves your boundary is set per build; the inputs above are the ceiling, and where the model runs, what it retains, and the DPA are agreed with your security team before anything is connected.

Our read

Human decides sensitivity high Order: once trust is earned

The job itself is a decision about a named person. This agent exists as decision support only; the decision stays with the person named above.

Some suites offer this as an automated decision. We do not build it that way: the agent prepares, a named person decides, and the record shows who.

Exceptions are individual employment-terms decisions and often involve health or family circumstances

Where it sits in the order

Individual employment-terms decisions with sensitive reasons; needs a tagged exception log and an established habit of human review.

Is a Policy Exception Request Preparation Agent worth building for your function?

That depends on your numbers, your data, and what else is on the map for you. The strategy month works that out.

How the strategy month works

Book a call

Thirty minutes. Bring the number this would move.