Session 1 · AI-HRM Opportunity Map
Generative AI Trends in Digital HRM
From casual AI use to structured, accountable HR augmentation.
Local hook
Sri Lanka scenario
LankaLearn University wants to help final-year HRM students prepare CVs, interview practice plans, and career pathways without creating generic or misleading advice.
Student deliverable
AI-HRM Opportunity Map
Teams choose one Sri Lankan sector and create a six-row opportunity map: HR area, pain point, AI idea, benefit, risk, and human review point.
Learning outcomes
- ✓Explain core GenAI trends in HRM
- ✓Map AI opportunities across the HR lifecycle
- ✓Separate useful augmentation from risky automation
- ✓Identify where human review is required
Trend briefing
- ↗AI copilots for daily HR work
- ↗AI agents for workflow execution
- ↗People analytics moving from reporting to recommendations
- ↗Synthetic media for HR communication
- ↗Human-in-the-loop governance becoming core HR literacy
Regional inspiration
- ★Sri Lanka–Singapore AI collaboration and capacity building
- ★Singapore agentic AI governance
- ★IndiaAI skilling ecosystem
- ★WEF future-of-work reskilling agenda
Session 1 demo prompt
Act as an HR digital transformation advisor. Create an AI opportunity map for a Sri Lankan hotel chain with 500 employees across Colombo, Galle, Ella, and Kandy. Map AI opportunities across recruitment, onboarding, learning and development, employee engagement, performance support, and HR operations. For each opportunity include: HR pain point, AI use case, benefit, risk, and human oversight needed.
Survey-informed extra prompts
Broaden beyond recruitment
Act as a Digital HRM lecturer in Sri Lanka. Students already understand AI in recruitment, but they need to see wider HRM use cases. Create 12 practical generative AI use cases across onboarding, learning and development, employee engagement, HR operations, performance support, and people analytics. For each use case, state: - HRM purpose - Example AI output - Why it helps - What a human HR professional must review - One ethical or privacy risk
Human-in-the-loop decision wall
Create a classroom activity called "AI drafts, humans decide" for HRM students. Give 15 HR tasks and classify each as: 1. Safe to use AI for drafting 2. AI may assist, but human approval is required 3. Do not delegate to AI Include Sri Lankan examples from recruitment, onboarding, training, performance, employee relations, and HR communication. Explain each classification in one sentence.
Misconception clinic
Act as a responsible AI facilitator. Create a 10-minute misconception clinic for HRM students around these risky ideas: - Secretly monitoring employee conversations - Letting AI make final dismissal decisions - Uploading real medical or disciplinary data to public AI tools - Treating AI ranking as objective truth For each misconception, provide a short correction, a Sri Lankan classroom example, and one question to ask students.
Minute-by-minute flow
- •0–5 Survey pulse check
- •5–12 Trend briefing beyond recruitment
- •12–22 HR lifecycle demo
- •22–35 Team opportunity map
- •35–45 Misconception clinic
- •45–55 Human-in-the-loop challenge
- •55–60 Exit ticket
Ethics checkpoint
- !Do not rank real students or employees
- !Avoid uploading real CVs or personal records
- !Treat AI recommendations as draft analysis, not final HR decisions
- !Require human review for hiring, promotion, discipline, and termination
Knowledge check
Which HR activity is most suitable for AI augmentation rather than full automation?
Team canvas