AI-Driven Talent Management

AI-Driven Talent Management

Use AI to attract, develop and retain talent: effectively, fairly and lawfully

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Platform:
Online
In-class
Revised and Updated: 08 October 2026
Date Venue Duration
02 - 06 November 2026 Sandton, Gauteng 5 Days

Course Introduction

Artificial intelligence is changing how Human Resources attracts, develops, and retains people. Used well, it supports data-driven decisions, predictive workforce planning, personalised development, and smarter recruitment. Used badly, it can screen out good candidates, entrench bias, and expose the organisation to legal and reputational harm.

 

HR is one of the most sensitive areas for AI. Decisions about hiring, pay, promotion, and dismissal affect people’s livelihoods, and they are regulated: in South Africa by the Employment Equity Act, the Labour Relations Act, and POPIA, and abroad by rules such as the EU AI Act, which treats AI used for recruitment and employment decisions as high-risk. This course therefore teaches participants to design AI-enabled talent management solutions that deliver measurable business value and stand up to scrutiny.

 

This practical five-day course gives HR professionals the tools, frameworks, and hands-on exposure to modern AI applications, including generative AI assistants, to improve recruitment, learning and development, workforce planning, and retention.

Course Objectives

By the end of this AI-Driven Talent Management course, participants will be able to:

  • Develop and implement AI strategies for talent management transformation
  • Apply AI-powered recruitment and candidate assessment tools, with human oversight
  • Use predictive analytics for workforce planning, retention, and succession
  • Design personalised learning and development pathways
  • Establish ethical and compliant AI governance frameworks, including under South African employment and data protection law
  • Evaluate and manage AI solution providers
  • Lead organisational AI adoption and change initiatives
  • Measure and optimise the return on AI investments in human capital

Who should attend?

  • Chief Human Resources Officers
  • HR Directors and Senior HR Managers
  • Talent Acquisition Leaders, and Recruitment Managers and Specialists
  • Learning and Development Managers
  • Organisational Development Practitioners
  • Workforce Planning Managers
  • HR Business Partners
  • HR Technology and HRIS Managers
  • People Analytics Specialists
  • Business Unit Leaders with HR Oversight
  • Transformation and Change Managers
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Training Methodology

Our diverse instructional approaches ensure effective learning:

– Lectures & Presentations: Engage with expert-driven, stimulating content.
– Course Material: Access well-crafted supporting resources.
– Group Work: Collaborate on discussions and case studies for practical insights.
– Workshops & Role-Play: Participate in immersive, scenario-based activities.
– Practical Application: Focus on applying theoretical knowledge in real situations.
– Post-Training Support: Receive extensive support after training for skill implementation.

Training Outline

Day 1 — AI Fundamentals and Strategic Foundation
Module 1: AI Fundamentals and Strategic Foundation
  • AI technologies in HR: machine learning, natural language processing, predictive analytics, generative AI, and AI agents
  • Organisational AI readiness and data maturity
  • Aligning AI initiatives with business strategy
  • Building stakeholder buy-in and governance structures
  • Developing an AI talent management roadmap
  • Practical Exercise: assess your HR function's AI readiness and identify two priority use cases
Module 2: The Legal and Ethical Guardrails for AI in HR
  • Why HR AI is high-risk: decisions that affect jobs, pay, and careers
  • South African requirements: the Employment Equity Act (including limits on unfair discrimination and on assessment tools), the Labour Relations Act, and POPIA, including its limits on solely automated decisions
  • The EU AI Act: employment AI as a high-risk category (obligations postponed to December 2027), and its ban on inferring emotions in the workplace
  • Principles to apply from day one: lawful basis, transparency, human oversight, and a right to challenge
  • Practical Exercise: classify a list of HR AI use cases as low, medium, or high risk, and set minimum controls for each

Day 2 — Intelligent Recruitment and Talent Acquisition
Module 3: Intelligent Recruitment and Talent Acquisition
  • AI-powered candidate sourcing and talent mapping
  • Automated CV screening and assessment systems, and how bias enters them
  • Chatbots and virtual recruitment assistants
  • Using generative AI for job adverts, interview guides, and candidate communication, and checking the output
  • Skills matching and competency-based selection
  • Designing seamless, fair AI-enabled hiring workflows with human decision points
  • Practical Exercise: redesign a hiring workflow with AI support, marking where a person must decide and where candidates are told that AI is used

Day 3 — AI-Driven Learning and Employee Development
Module 4: AI-Driven Learning and Employee Development
  • Personalised learning pathways and adaptive systems
  • Intelligent content recommendations and AI-supported coaching and mentoring
  • Skills gap prediction and capability planning, and linking it to skills development planning in South Africa
  • Employee engagement analytics and listening tools, and the line between useful insight and intrusive monitoring
  • AI-enabled career and succession development
  • Practical Exercise: design a personalised learning pathway for a critical role, using a skills-gap analysis

Day 4 — Predictive Talent Analytics and Workforce Intelligence
Module 5: Predictive Talent Analytics and Workforce Intelligence
  • Employee turnover and flight-risk prediction, and the ethics of acting on a prediction about a named person
  • Data-driven retention strategies
  • AI-supported compensation and rewards analysis, including pay equity
  • High-potential identification and succession analytics
  • Executive workforce dashboards and reporting
  • Practical Exercise: build a retention-risk view from a sample workforce dataset, and agree what actions the organisation will and will not take on the results

Day 5 — Governance, Providers, Adoption and ROI
Module 6: Ethical AI and Governance in HR
  • Bias detection and fair algorithm design, including testing outcomes by group
  • Data governance and privacy frameworks for employee and candidate data
  • Evaluating and managing AI solution providers: due diligence questions, contract clauses, and audit rights
  • Monitoring, incident handling, and documentation
  • Practical Exercise: review a vendor's AI recruitment tool against a due-diligence checklist
Module 7: Adoption, Change and Return on Investment
  • Leading organisational AI adoption and change: HR team skills, employee trust, and communication
  • Measuring and optimising return on AI investments in human capital: time to hire, quality of hire, retention, and cost per hire
  • AI implementation roadmaps and performance metrics
  • Practical Exercise: finalise your AI talent management roadmap with governance controls and success metrics, and present it for feedback

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FAQs – AI-Driven Talent Management

Build AI-driven talent management skills covering AI in HR, talent acquisition, workforce analytics, employee development, performance management, and strategic workforce planning.

What is covered in the AI-Driven Talent Management course?
The course covers AI strategy for talent management, intelligent recruitment, learning and development, predictive workforce analytics, employee retention, AI governance, organisational adoption and measuring AI return on investment.
Who should attend the AI-Driven Talent Management training?
The training is designed for HR directors and managers, talent acquisition and recruitment professionals, learning and development managers, HR business partners, workforce planning managers, HR technology specialists, people analytics professionals and business leaders with HR responsibilities.
How can AI be used in recruitment and talent acquisition?
Participants learn how AI can support candidate sourcing, talent mapping, CV screening, skills matching, job advertisements, interview guides and candidate communication, while maintaining human oversight and fair decision-making.
Does the course cover AI for employee learning and development?
Yes. The course covers personalised learning pathways, intelligent content recommendations, AI-supported coaching and mentoring, skills-gap prediction, capability planning, career development and succession planning.
Does the training cover AI ethics, governance and POPIA?
Yes. Participants explore ethical AI governance, bias detection, employee and candidate data privacy, human oversight, transparency and South African requirements including the Employment Equity Act, Labour Relations Act and POPIA.
Are practical exercises included in the AI-Driven Talent Management course?
Yes. The five-day training includes practical exercises such as assessing AI readiness, redesigning AI-supported recruitment workflows, creating personalised learning pathways, analysing workforce retention risks and developing an AI talent management roadmap.

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