(IHRP) AI for Recruitment Workforce Planning & HR Analytics

Course Objectives

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

• Utilise AI to review and refine hiring-related workforce execution plans by aligning recruitment stages, role requirements, volumes and timelines with business objectives.
• Analyse workforce trend signals affecting manpower demand, including market conditions, business direction, attrition risks, automation impact and ethical AI considerations.
• Develop manpower forecasts using performance evidence such as KPIs, competencies and potential to assess role readiness and succession coverage.
• Apply AI-supported analytical methods to evaluate workforce engagement, capacity and capability indicators to identify patterns, outliers and trends.
• Identify skills gaps and recommend targeted upskilling or hiring strategies based on capability gaps and business priority areas.
• Evaluate workforce-mix options, such as automation, redeployment and outsourcing, using elasticity principles to improve workforce flexibility and resilience.

Learning Units & Topics

LU1 – Foundations of Smarter Hiring and Candidate Experience with AI

• Smarter Hiring with AI Tools: Winning the Talent War with Zero-Ghosting & Rapid-Fire Recruitment
• Enhancing the Job Seeker Experience with AI: Delivering Premium, High-Touch Candidate Journeys at Scale

LU2 – Understanding Workforce Trends and Ethical AI Practices

• Prompt Engineering for HR Professionals: Mastering Meta-Prompting for Efficiency, WFA Readiness and AI Governance

LU3 – Data-Driven Performance Reviews and Forecasting

• Identifying Skills Gaps and Planning Training with AI: Precision Upskilling & Green Skills Mapping for the 2030 Plan
• Making Performance Reviews Fairer and Smarter with AI: Executive Storytelling & Data-Driven Performance Forecasts
• Brainstorming HR Improvements with AI: The Innovation Lab – Architecting Future-Ready HR Blueprints

LU4 – Strategic HR Planning through Elasticity and Workforce Flexibility

• Using AI to Improve Employee Engagement & Well-being: Decoding Sentiment and Implementing the ‘Right to Disconnect’
• Understanding Your Team Better with AI Insights: Leveraging Silver Talent and Age-Inclusive Job Redesign
• Automating Everyday HR Tasks with AI: Managing Agile Expansion & SPL Continuity Planning

Instructional Methods

Lectures & Case-Study Analysis: The course uses interactive lectures and guided demonstrations to introduce participants to the strategic application of Generative AI across core HR functions. Key concepts such as AI-powered recruitment, workforce analytics, sentiment analysis, governance, workplace fairness, data privacy and sustainable workplace design are explained through structured facilitation and trainer-led demonstrations, enabling participants to connect emerging concepts with practical HR workflows and decision-making.

Hands-On Lab Sessions: Practical labs require participants to use approved AI tools such as ChatGPT, Microsoft Copilot, Claude, Gemini and DeepSeek to improve recruitment content, analyse workforce data, compare transformation options, develop governance artefacts, define human-in-the-loop checkpoints and build implementation plans. Tool selection may be adjusted according to organisational policy and availability.

Scenario-Based Learning: Scenario-based learning is used to help participants apply AI solutions to authentic HR challenges. These scenarios include reducing recruitment delays, improving candidate experience, closing skills gaps, responding to attrition risks, planning for regional workforce expansion and managing workplace transitions in compliance-sensitive environments. This strengthens participants’ ability to evaluate issues and select appropriate AI-enabled interventions.

Case Study Discussions: Case study discussions are used to deepen understanding of how AI can support talent acquisition, employee experience, workforce planning, governance and organisational transformation. Through guided analysis of practical cases, participants examine business needs, legal and ethical considerations and the effectiveness of different HR strategies in achieving productivity, retention and compliance outcomes.

Group Discussions & Collaborative Learning: Collaborative learning activities and group discussions provide opportunities for participants to exchange perspectives, compare HR use cases and reflect on the organisational implications of AI adoption. This supports peer learning, broadens strategic thinking and encourages participants to evaluate HR challenges from multiple operational and leadership perspectives.

Practical Application and Skills Mastery: Participants translate learning into workplace-relevant artefacts, including process maps, journey maps, AI output review checklists, system requirements, configuration rules, UAT checklists, governance and monitoring checklists, communication plans, manager enablement guides, 90-day roadmaps and project plans. Guided practice and reflective review reinforce responsible, evidence-based and human-centred AI use.