Pay Equity Analysis Agent

A pay equity analysis agent is an AI agent for compensation, benefits & payroll that runs aggregate pay-gap analysis by gender, ethnicity, and other protected characteristics you lawfully hold, controlling for level, job family, location, hours, and tenure; flags cohorts with unexplained gaps and drafts the statutory reporting inputs (UK gender pay gap, EU Pay Transparency Directive, US state filings).

How does the pay equity analysis agent work?

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

  1. Reads from

    Pay by element · Level, job family, location, tenure and hours · Protected characteristics held on a lawful basis · Legal-privilege arrangement · Statutory report templates

  2. AI agent · runs when the annual pay-equity review or a filing deadline

    Pay Equity Analysis Agent

  3. A person decides

    Total Rewards and legal decide remediation and what is filed

  4. Produces

    Adjusted and unadjusted gaps by cohort · Flagged cohorts with unexplained gaps · Draft statutory reporting tables

What does the pay equity analysis agent do?

Runs aggregate pay-gap analysis by gender, ethnicity, and other protected characteristics you lawfully hold, controlling for level, job family, location, hours, and tenure; flags cohorts with unexplained gaps and drafts the statutory reporting inputs (UK gender pay gap, EU Pay Transparency Directive, US state filings).

What does it produce?

An adjusted and unadjusted gap analysis by cohort, a list of flagged cohorts with the size of the unexplained gap, and draft reporting tables and narrative

Who decides?

The head of total rewards and legal counsel decide which gaps to remediate, how, and what to report; the agent analyzes at cohort level and does not propose individual adjustments.

What systems does the pay equity analysis 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.

  • HRIS

    pay, level, location and tenure

    WorkdaySAP SuccessFactorsHiBob
  • Analytics

    controlled analysis and reporting tables

    SnowflakePower BITableau
  • Pay equity tools

    comparison point where already licensed

    SyndioTrusaic
  • Document store

    privileged working papers with restricted access

    SharePointGoogle Drive

What data does it need?

  • employee pay by element
  • level, job family, location, tenure, hours
  • protected characteristics held lawfully with consent or statutory basis
  • statutory reporting templates per jurisdiction

How would you measure it?

adjusted gap by cohort, annually or per cycle; flagged cohorts opened and closed, per cycle; statutory filings on time, per jurisdiction; time to produce the analysis, per run

What does a first proof look like?

Run the analysis on last year's data set alongside the report the team or an external adviser produced. Compare adjusted gaps and flagged cohorts.

You'd call it working when

Results match within the method's tolerance, every cohort shown meets the minimum group size, and the draft statutory tables reconcile to the filed ones.

What usually goes wrong?

  • Small cohorts leak identities; enforce a minimum group size before anything is shown
  • Regression choices drive the answer; make the controls explicit and reviewable
  • Findings may be privileged; decide with counsel who sees what before running

What are the guardrails?

  • Aggregate only, minimum group size enforced; no individual pay adjustment is proposed
  • Protected characteristics used only under a lawful basis, minimized, and never joined to other agent outputs
  • Works council or employee representative consultation where required before analysis
  • Access limited to total rewards and counsel; working papers held under privilege where advised
  • GDPR and DSAR ready: an individual's data can be located, explained and removed

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

Strong case sensitivity high Order: once trust is earned

Clearly valuable with real deployments behind it. Needs care on data and adoption.

Parts of this may exist in your current tools. The case for building is usually the join across systems, or your rules and language, that a suite feature cannot carry.

protected characteristics and pay; often subject to works council consultation and legal privilege

Where it sits in the order

Protected characteristics and possible legal privilege; needs counsel, consultation and clean level data before it runs.

Is a Pay Equity Analysis 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.