HR policy

AI policy for HR should separate draft work from people decisions

A good HR AI policy does not ban every useful tool or allow every experiment. It tells the team which tasks are allowed, which data is restricted, which tools are approved, and where human review is mandatory.

Template Data rules Human review

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Export the HR AI policy builder

Copy this into your approved AI tool to create a first-draft HR AI policy with allowed uses, restricted uses, data rules, review duties, and open questions for legal or compliance review.

Use this as a starting policy, not final legal language

HR teams need an AI policy before AI use becomes invisible. The policy should be plain enough for recruiters, HR generalists, managers, and people analysts to use during normal work.

This template is designed for HR operations, recruiting support, employee communication, learning and development, and people analytics. It is not a substitute for legal review. Employment, privacy, and AI rules differ by jurisdiction, and the final policy should be reviewed by the right internal stakeholders.

Policy principle: AI may assist with drafting, summarizing, organizing, and checking HR work. AI must not be the final decision-maker for hiring, pay, promotion, performance ratings, discipline, termination, or other employment-impacting outcomes.

Template language

HR AI Use Policy

Purpose:
This policy explains how HR team members may use approved AI tools to support HR work while protecting employee and candidate data, reducing bias risk, and preserving human accountability.

Allowed uses:
- Drafting job descriptions, employee communications, FAQs, training outlines, and policy summaries.
- Summarizing anonymized or aggregated comments, notes, or survey themes.
- Creating interview-question drafts and scorecard drafts for human review.
- Rewriting HR content for clarity, accessibility, and consistency.
- Generating checklists, meeting agendas, and first-draft templates.

Prohibited uses:
- Making final hiring, promotion, compensation, performance, discipline, termination, or layoff decisions.
- Ranking, rejecting, or selecting candidates without documented human review.
- Uploading confidential employee or candidate data to unapproved AI tools.
- Inferring protected characteristics, health status, family status, disability, age, religion, union activity, or other sensitive traits.
- Using AI-generated content without checking facts, fairness, and policy alignment.

Data handling:
HR team members may use public or non-sensitive internal information in approved AI tools. Confidential, employee-sensitive, candidate-sensitive, payroll, medical, immigration, investigation, grievance, or performance data may only be used in approved systems with appropriate access controls and business justification.

Human review:
Every AI-assisted HR output must be reviewed by a qualified human before it is used. The reviewer must check factual accuracy, source support, bias risk, privacy risk, and alignment with company policy.

Logging:
For sensitive HR workflows, the team must keep a record of the tool used, purpose, reviewer, approval date, final version, and any source materials required for audit.

Tool approval:
HR may use only company-approved AI tools for HR work. New AI vendors or features must be reviewed for data use, retention, access controls, audit features, and employment-decision risk before adoption.

The policy needs operating rules, not slogans

A policy that says "use AI responsibly" is not enough. HR needs task rules. A recruiter drafting outreach needs different guardrails than a people analytics lead summarizing survey comments. The policy should classify tasks by risk level and define what review is required.

Risk level Examples Policy rule
Low Drafting an internal announcement, creating a training outline, rewriting a policy FAQ. Allowed with review for accuracy and tone.
Medium Summarizing employee survey comments, creating interview questions, drafting performance feedback language. Allowed only with data minimization, bias check, and documented human review.
High Resume screening, candidate ranking, performance ratings, compensation decisions, attrition prediction. Do not automate without formal governance, legal review, validation, auditability, and human decision ownership.

Data categories

HR data is different from ordinary business text. A policy should define data categories in plain language. Public job information and general policy text may be appropriate for approved tools. Candidate resumes, employee relations records, medical information, payroll details, immigration documents, investigation notes, and performance records require stricter controls.

If an HR user cannot tell whether data is sensitive, the policy should default to "do not paste it into an external AI tool." The team can then provide approved alternatives, such as enterprise tools with contract protections, internal systems, or anonymized summaries.

HR AI policy checklist

Allowed use listDoes the policy name specific safe starting tasks?
Prohibited use listDoes it block final employment decisions and unreviewed screening?
Data rulesDoes it separate public, internal, confidential, candidate-sensitive, and employee-sensitive data?
Tool approvalDoes HR know which AI tools are approved and which are not?
Human reviewDoes every output have a named human owner?
Audit trailDoes sensitive work keep enough records for later review?

FAQ

Can HR use ChatGPT to draft employee communications?

Usually yes, if the message does not include confidential employee data, legal conclusions, or sensitive facts. The final message still needs human review for accuracy, tone, policy alignment, and audience impact.

Can HR paste resumes into public AI tools?

That should be treated as restricted. Resumes contain candidate personal data, and unapproved tools may create privacy, retention, bias, and audit problems. Use approved systems and clear review rules.

Should the policy cover managers too?

Yes. Managers often use AI for feedback, coaching notes, and employee messages. HR should define what managers may do, what data they may use, and when HR review is required.

Sources and further reading