ManorHR

Framework

AI Hiring Governance Framework

A governance framework for using AI in recruitment while protecting fairness, privacy, accountability, and human decision quality.

HR

Resource brief

Enterprise workforce operations

6 sections

Executive use case

Structured guidance for practical decision-making and implementation.

1. Define permitted AI use cases

Structured guidance for practical decision-making and implementation.

2. Control the data foundation

Structured guidance for practical decision-making and implementation.

3. Monitor fairness and quality

Structured guidance for practical decision-making and implementation.

Executive use case

AI can improve hiring productivity, but only when it is governed by clear policies, clean workflow data, and accountable human review. This framework helps HR, legal, technology, and leadership teams define where AI is useful and where it should remain advisory.

1. Define permitted AI use cases

Start by separating low-risk productivity use cases from high-impact decision support. Drafting job descriptions, summarizing interview notes, improving candidate communication, and organizing recruiter tasks are different from automated ranking or rejection.

OK List every AI-supported hiring activity
OK Identify which activities affect candidate outcomes
OK Require human approval before rejection or offer decisions
OK Keep explainability expectations practical and documented

2. Control the data foundation

AI hiring tools need structured, relevant, and lawful data. Poor source tracking, inconsistent screening stages, and incomplete candidate records produce weak recommendations and increase governance risk.

OK Capture candidate consent where required
OK Do not use sensitive attributes for screening decisions
OK Keep role requirements explicit and job-related
OK Maintain audit history for important workflow actions

3. Monitor fairness and quality

Governance should include routine review of shortlist quality, source diversity, rejection patterns, candidate complaints, and hiring outcomes. AI should improve decision support without hiding bias inside automation.

OK Compare AI-assisted outcomes against human-reviewed samples
OK Review false positives and false negatives
OK Track adverse patterns by role, source, and selection stage
OK Give candidates and recruiters clear escalation paths

4. Assign accountability

AI governance fails when ownership is vague. HR should own the hiring process, technology should own system controls, legal should advise on risk, and leadership should approve policy boundaries.

OK Name a process owner for AI hiring governance
OK Document vendor responsibilities and data-processing terms
OK Train users before enabling AI-assisted workflows
OK Review policies at least twice per year

Decision summary

Use AI to strengthen hiring operations, not to remove accountability. The safest path is a human-led workflow where AI improves clarity, speed, and consistency while decisions remain explainable and reviewable.

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