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AI for the People Function

Designing a Responsible AI Policy for the People Function

MARIA NOLAZCO MASSON

• 3 min read

Clear principles to guide ethical, effective use of AI in HR.

Introduction: The Need for Guardrails

AI is rapidly becoming part of how HR teams operate—from sourcing candidates to analyzing attrition risk. The opportunities are real, but so are the risks. Without clear internal policies, teams may adopt AI tools that unintentionally create bias, violate privacy, or erode employee trust.

A responsible AI policy for the People function is no longer optional. It’s how you set expectations, establish boundaries, and signal that the use of AI in HR is thoughtful—not reactive.

This isn’t about slowing innovation. It’s about ensuring innovation is aligned with your values, your people, and your business.

Why HR Needs Its Own AI Policy

Most organizations have general AI or data governance policies. But HR operates in a unique space—handling sensitive, personal, and often high-stakes information.

AI in HR touches areas like:

  • Hiring and promotions
  • Performance reviews
  • Employee communications
  • Compensation
  • Learning and development
  • Terminations

These are decisions that directly impact people's lives. The margin for error—or opacity—is small.

A People-specific AI policy ensures that ethical use, legal compliance, and cultural alignment are at the center of how AI is applied to human data and decisions.

Core Components of a Responsible AI Policy for HR

Here’s a framework to help you build or refine your internal guidelines.

1. Purpose Statement

Start by clarifying why the policy exists. This should reflect your values as a company and the importance of responsible AI use in all People-related decisions.

Example:
“Our goal is to use AI in a way that enhances fairness, transparency, and trust in all people processes. We will ensure AI is applied responsibly and never as a substitute for thoughtful human judgment.”

2. Scope of Application

Define where this policy applies. Be explicit that it covers:

  • Internally built tools
  • Third-party HR vendors using AI/ML
  • Any automated decision-support tools tied to employee data

Also include all stages of the employee lifecycle, not just talent acquisition.

3. Principles of Responsible Use

These are the non-negotiables—your ethical foundation. Typical principles include:

  • Transparency: We disclose when and how AI is used in people processes.
  • Human Oversight: All AI-informed decisions will be reviewed by a qualified person.
  • Fairness and Inclusion: All AI models must be tested for bias and adjusted if needed.
  • Accountability: There is always a clearly named owner for each AI tool in HR.
  • Privacy and Consent: Employees are informed about what data is used and why.

These principles should guide all decision-making—not just vendor selection.

4. Vendor and Tool Evaluation Standards

Before adopting any AI-enabled HR tool, teams should review:

  • What data the model uses
  • How the model was trained (and on what population)
  • Whether outputs can be explained in plain terms
  • The vendor’s own testing and audit protocols
  • Whether bias testing has been conducted by gender, race, age, etc.
  • Whether users can override, dispute, or escalate AI-generated outputs

This section can include a simple checklist or rubric that must be completed before implementation.

5. Bias Auditing and Monitoring Protocols

AI models are not “set and forget.” Your policy should define:

  • How often each tool will be audited (e.g. quarterly, annually)
  • What dimensions of bias will be reviewed (e.g. demographic impact)
  • Who is responsible for auditing (People Analytics, DEI, Legal?)
  • What thresholds trigger escalation or tool deactivation
  • How employees will be notified if a tool is updated or changed

Bias monitoring isn’t just a compliance task—it’s central to responsible use.

Employees should always know:

  • When AI is being used in a process (e.g. performance, promotion)
  • What data is being used
  • Who to contact with questions or concerns
  • What their rights are (e.g. request review, opt out where applicable)

Clear, honest communication is critical for maintaining trust.

7. Escalation and Redress

Things will go wrong. Your policy should include:

  • How concerns or errors can be raised
  • How AI-generated outputs can be reviewed or reversed
  • What happens when misuse or malfunction is identified
  • The People team’s responsibility to investigate and respond

This ensures the policy isn’t just theoretical—it has teeth.

8. Policy Governance and Maintenance

Define:

  • Who owns the policy (e.g. Head of People Analytics, HR Operations)
  • How often it will be reviewed
  • How updates are communicated
  • How new tools are evaluated against the policy before launch

This keeps the policy relevant as your tools and team evolve.

Implementation Tips

  • Start with one use case (e.g. recruiting AI) and expand.
  • Run tabletop exercises: simulate an AI decision gone wrong and test your response.
  • Involve Legal, IT, DEI, and Comms early.
  • Publish the policy internally, even if it’s in draft form. Invite feedback.
  • Add the policy to your onboarding for People team members and relevant vendors.

Final Thought

AI in HR is here—and growing fast. The question isn’t if it’s used, but how.

A responsible AI policy is how you lead with intention. It protects your people. It aligns your tools with your values. And it ensures that innovation doesn’t outpace ethics.

This is your opportunity to set the standard—not just for HR, but for the entire organization.