Generative AI for Human Resources Professionals Training Course

Course overview

Human resources teams are being asked to improve service speed, workforce insight and employee communications while protecting sensitive personal data and maintaining fair, defensible decisions. Generative AI can assist with drafting job descriptions, preparing interview materials, summarising policy feedback, analysing themes in employee comments and creating manager guidance. Used without controls, however, it can expose candidate or employee data, reproduce bias, invent policy details or create records that cannot be justified in an audit. HR professionals need practical judgement about where AI can support work and where human review must remain decisive.

This course teaches participants to use generative AI responsibly across recruitment, learning and development, employee relations, HR operations and workforce planning. Participants learn prompt patterns for HR tasks, source-grounded drafting, document summarisation, structured output creation and quality-checking techniques. They assess use cases by value, risk and data sensitivity; apply privacy, fairness and transparency controls; and develop review criteria for AI-generated content. The course also addresses vendor questions, governance roles, acceptable-use rules and metrics for evaluating whether an AI-enabled HR process is producing useful, equitable results.

Delivery combines instructor-led demonstrations, realistic HR case studies and guided work in ChatGPT and Microsoft Copilot. Participants test prompts against fictionalised recruitment, policy and employee-feedback scenarios, identify failure modes and practise documenting human oversight. They leave with an HR Generative AI Use Case and Control Plan: a practical pack containing a prioritised use-case backlog, prompt templates, risk assessment, review checklist, data-handling rules and a 90-day pilot plan suitable for discussion with HR leadership, legal, IT and information security.

The course is suited to HR practitioners and leaders who need enough technical fluency to use and govern generative AI confidently, without becoming data scientists or software developers.

Course objectives

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

• Identify HR generative AI use cases using a value, feasibility and people-risk prioritisation matrix
• Write reusable prompt templates for job descriptions, manager communications, policy FAQs and learning materials
• Classify employee and candidate information by sensitivity before entering content into an AI tool
• Apply human-in-the-loop review criteria to detect hallucinations, bias, unsupported claims and policy inaccuracies
• Produce structured AI-assisted outputs using role, context, constraints, source and format prompt components
• Assess AI-enabled recruitment and employee-relations workflows for fairness, explainability and adverse-impact risks
• Draft an HR generative AI acceptable-use guide with escalation routes and approval responsibilities
• Build a 90-day HR AI pilot plan with success measures, control checks and stakeholder actions

Benefits of attending

Target competencies

Who should attend

• HR Business Partners — who advise leaders and need practical, controlled ways to improve HR service delivery
• HR Managers and Heads of HR — who must select, govern and defend AI use across people processes
• Talent Acquisition Managers and Recruiters — who want to accelerate recruitment content while protecting candidate fairness and privacy
• Learning and Development Professionals — who create learning assets and need reliable AI-assisted design workflows
• People Analytics and HR Operations Specialists — who manage HR data, reporting and process improvement
• Employee Relations and Policy Professionals — who draft guidance and must maintain accurate, consistent and defensible communications

Requirements and prerequisites

This is a foundation-to-intermediate course. Participants should understand their organisation's core HR processes, such as recruitment, employee relations, learning, HR operations or workforce planning, and be comfortable working with documents, spreadsheets and web-based business applications. Familiarity with Microsoft 365, including Word and Teams, is helpful but not essential. Participants should bring examples of non-confidential HR tasks they would like to improve. No coding, statistics, machine learning, Python, data-science background or prior experience with ChatGPT, Microsoft Copilot or automation tools is required. Complete beginners will start with AI terminology, safe prompting and practical HR scenarios.

Training methodology

The instructor uses short demonstrations to show how prompts, source material and output constraints affect HR results, followed by individual and small-group practice. Case work covers a recruitment campaign, an employee-policy query, manager guidance and employee-feedback themes using fictionalised records. Participants compare weak and controlled outputs, apply privacy and fairness checks, and discuss escalation decisions with peers. Each day adds components to an HR Generative AI Use Case and Control Plan. The final workshop turns that material into a pilot proposal with owners, measures, review gates and implementation actions.

Course outline

Day 1: Generative AI foundations for HR work

• Generative AI, large language models and retrieval-augmented generation explained for HR
• HR task mapping across recruitment, onboarding, learning, employee relations and HR operations
• Capabilities and limitations of text-generation and summarisation models
• Prompt anatomy: role, task, context, constraints, examples and output format
• Zero-shot, few-shot and iterative prompting for HR documents
• Hallucinations, stale knowledge and unsupported policy claims
• Human accountability boundaries in people decisions

Workshop: Participants convert three routine HR tasks into controlled prompts and produce a first prompt library with stated review requirements.

Day 2: Safe data and responsible HR AI

• Candidate, employee, health, performance and grievance data sensitivity classification
• Personal data minimisation, anonymisation and redaction before AI use
• Confidentiality risks in public, enterprise and integrated AI environments
• Bias sources in training data, prompts and HR decision workflows
• Fairness, transparency and explainability in recruitment and employee management
• NIST AI Risk Management Framework concepts applied to HR use cases
• Human-in-the-loop approval, audit trails and escalation triggers

Workshop: Using a fictional recruitment and grievance scenario, participants complete a data-and-risk assessment and define prohibited, permitted and escalated uses.

Day 3: AI-assisted recruitment and talent development

• Competency-based job description and job-advert prompting
• Inclusive language review and bias-sensitive recruitment content checks
• Interview question banks linked to role criteria and scoring rubrics
• Candidate communication drafting with approved tone and process boundaries
• Learning needs analysis and curriculum-outline generation
• Scenario-based learning content and manager coaching guide creation
• Quality assurance for AI-generated talent content

Workshop: Participants build a recruitment and learning-content toolkit comprising a job-advert prompt, interview guide, learning outline and review checklist.

Day 4: HR operations, employee experience and workflow design

• Policy FAQ generation from approved source documents
• Source-grounded summarisation and citation checking for HR guidance
• Employee feedback theme analysis with privacy safeguards
• Manager communication drafting for organisational change scenarios
• Knowledge-base design for self-service HR queries
• Microsoft Copilot and Power Automate opportunities in HR administration
• Workflow mapping for AI hand-offs, exceptions and approval points

Workshop: Participants redesign a fictional HR service request process and produce a source-grounded FAQ workflow with human escalation rules.

Day 5: Governance, measurement and pilot implementation

• HR AI use-case portfolio prioritisation by benefit, effort, data sensitivity and risk
• Acceptable-use policy clauses for HR generative AI
• Roles and responsibilities for HR, IT, legal, privacy and information security
• Vendor due-diligence questions for AI-enabled HR technology
• Quality, fairness, adoption and time-saving measures for pilots
• Testing protocols, sample reviews and incident response procedures
• 90-day implementation roadmap and stakeholder communication plan

Workshop: Participants present an HR Generative AI Use Case and Control Plan containing a prioritised pilot, control set, success measures and 90-day roadmap.

Tools & standards covered

ChatGPT, Microsoft Copilot, Microsoft Power Automate, NIST AI Risk Management Framework

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions