Cambridge
Academy
In London

Introduction

Employee Relations teams handle highly sensitive information and decisions that directly affect people’s lives and workplace trust. As AI is increasingly used to summarize cases, detect patterns, support investigations, and automate reporting, it must be applied responsibly—with strong privacy protection, fairness safeguards, and clear human accountability. This practical program equips ER specialists with simple, actionable practices for ethical, safe, and compliant AI use in ER work.

Course Objectives

By the end of this course, participants will be able to:

·        Understand responsible AI principles for Employee Relations work

·        Protect privacy and confidentiality when using AI tools

·        Identify and reduce bias risks in AI-assisted ER processes

·        Set clear human-in-the-loop controls and documentation practices

·        Apply safe AI workflows for common ER tasks

Target Audience

This course is designed for:

·        Senior Employee Relations specialists and case managers

·        HR professionals supporting investigations and ER casework

·        People analytics and HR reporting partners supporting ER insights

·        Compliance, privacy, and legal partners supporting HR governance

·        Managers who handle sensitive ER information 

Course Outlines

Day 1: Responsible AI Basics in ER

·        Where AI is used in ER

·        Benefits vs. risks in ER work

·        Human accountability and oversight

·        Common AI errors and limits

·        Activity: ER AI use-case checklist

Day 2: Privacy and Confidentiality

·        Sensitive ER data types

·        What not to share with AI

·        Consent and transparency basics

·        Data minimization and access controls

·        Workshop: Safe-use rules for ER 

Day 3: Bias and Fairness Risks

·        Where bias can enter

·        Disparate impact basics

·        Reviewing AI outputs safely

·        Fair decision documentation

·        Activity: Bias risk scenario exercise

Day 4: Governance and Controls

·        Roles and approvals

·        Human-in-the-loop checkpoints

·        Record keeping and audit trails

·        Third-party tool considerations

·        Case study: Handling an AI incident 

Day 5: Practical ER Workflows and Roadmap

·        Safe prompts for ER tasks

·        Summarizing cases with checks

·        Pattern insights without profiling

·        Monitoring and continuous improvement

·        Final project: Responsible AI ER playbook