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| Module 01 | AI Foundations for HR Leaders |
| This foundational module demystifies Artificial Intelligence for HR professionals. Participants gain a clear, jargon-free understanding of how AI technologies work, where they are being applied across the HR value chain, and what distinguishes transformative adoption from superficial automation. The module establishes a shared vocabulary and mental model that will underpin all subsequent learning. |
| Key Topics Covered |
| > Defining AI, Machine Learning, Deep Learning, and Generative AI – a practical HR primer |
| > The AI-HR value chain: mapping AI applications across recruit, develop, engage, and retain |
| > Current state of AI in HR: global trends, adoption rates, and leading organizational practices |
| > Understanding AI capabilities and limitations: what AI can and cannot do in people management |
| > Introduction to Large Language Models (LLMs) and their implications for HR workflows |
| > Case Study: How leading organizations are deploying AI across the employee lifecycle |
| > Reflection exercise: AI maturity self-assessment for your HR function |
| Module 02 | AI-Powered Talent Acquisition and Workforce Planning |
| Recruitment and workforce planning are among the most rapidly AI-transformed HR domains. This module examines how AI is reshaping candidate sourcing, screening, assessment, selection and how HR leaders can deploy these tools strategically while safeguarding fairness, candidate experience, and legal compliance. |
| Key Topics Covered |
| > AI in talent sourcing: semantic search, talent intelligence platforms, and passive candidate identification |
| > Automated screening and ranking: how AI assesses CVs, cover letters, and application data |
| > AI-assisted interviewing: video interview analytics, voice intelligence, and sentiment analysis |
| > Psychometric and skills-based assessments powered by machine learning |
| > Workforce planning and demand forecasting: predictive labour analytics and scenario modelling |
| > Bias in AI hiring tools: causes, consequences, and mitigation strategies |
| > Vendor evaluation framework: questions every HR leader should ask AI hiring tool providers |
| > Practical workshop: Auditing an AI-powered recruitment workflow for equity and effectiveness |
| Module 03 | AI in Learning, Development & Performance Management |
| Continuous learning and performance management are being fundamentally reimagined through AI. This module explores how intelligent learning platforms, AI-generated content, skills inference engines, and continuous performance tools are redefining how organizations develop and evaluate their people and how HR can lead this evolution with intention. |
| Key Topics Covered |
| > Intelligent learning experience platforms (LXPs): personalization, recommendation engines, and skills mapping |
| > Generative AI in content creation: designing learning at speed and scale |
| > Skills ontologies and AI-driven skills gap analysis: building dynamic capability frameworks |
| > Continuous performance management: AI tools for feedback, goal tracking, and coaching support |
| > Succession planning and career pathing enabled by AI-powered talent analytics |
| > The human-AI coaching model: augmenting manager capability with AI-driven insights |
| > Risks of AI in performance management: surveillance, over-reliance, and the feedback quality challenge |
| > Practical exercise: Designing an AI-augmented L&D strategy for a workforce transformation scenario |
| Module 04 | Employee Experience, Engagement & Wellbeing in the Age of AI |
| AI is increasingly embedded in how organizations listen to, engage, and support their workforce. This module examines the use of AI in employee listening programmes, sentiment analysis, wellbeing platforms, and the evolving employee experience while probing the tensions between personalization, privacy, and psychological safety. |
| Key Topics Covered |
| > AI-powered employee listening: pulse surveys, NLP sentiment analysis, and real-time engagement signals |
| > Predictive attrition modelling: using AI to identify at-risk talent and trigger retention interventions |
| > AI in employee wellbeing: mental health platforms, wellness apps, and the boundaries of employer care |
| > Personalizing the employee experience at scale: AI-driven onboarding, benefits navigation, and HR self-service |
| > Conversational AI and HR chatbots: capabilities, limitations, and employee trust considerations |
| > The surveillance paradox: balancing data-driven insight with employee privacy and dignity |
| > Designing AI-informed yet human-centred employee experience programmes |
| > Case Study Discussion: When AI listening goes wrong – lessons from organizational missteps |
| Module 05 | Ethics, Governance & the Legal Landscape of AI in HR |
| Responsible AI deployment is not optional. it is a strategic and legal imperative. This module equips HR leaders with the frameworks, governance structures, and regulatory knowledge needed to champion ethical AI in the workplace, protect employee rights, and position HR as the conscience of the organization in AI transformation. |
| Key Topics Covered |
| > Principles of responsible AI: fairness, transparency, explainability, accountability, and privacy by design |
| > The regulatory horizon: GDPR implications, and emerging global standards |
| > Establishing an HR AI Governance Framework: oversight committees, use-case registers, and audit processes |
| > Algorithmic accountability: conducting AI impact assessments for HR applications |
| > Employee rights in the age of AI: rights to explanation, recourse, and human review of automated decisions |
| > Communicating AI use to employees: transparency obligations and trust-building strategies |
| > Building the HR AI Policy Toolkit: acceptable use policies, data ethics guidelines, and vendor contracts |
| Module 06 | Building the AI-Ready HR Function: Strategy, Change & the Future |
| The final module synthesizes the course learning into an integrated strategic framework for building and leading a future-ready HR function. Participants will develop a personal action plan for AI adoption, explore the evolving role of HR in an AI-first enterprise, and prepare for the next wave of technological disruption on the horizon. |
| Key Topics Covered |
| > The AI-ready HR operating model: rethinking roles, processes, and organizational design |
| > HR team capability building: data literacy, AI fluency, and the future HR competency framework |
| > Designing and leading AI change management: overcoming resistance, building confidence, and embedding adoption |
| > Communicating AI strategy to the C-Suite and Board: building the business case and executive narrative |
| > Measuring AI impact in HR: KPIs, ROI frameworks, and value realization roadmaps |
| > The future of work: generative AI, human-machine collaboration, and the evolving employment relationship |
| > Emerging frontiers: agentic AI, autonomous HR processes, and what lies beyond current AI capabilities |
| > Capstone exercise: Developing a 90-day AI Strategic Action Plan for your HR function |
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