AI for HR: Applied AI Design, Governance Awareness & Workforce Insights for HR Practitioners

• Why HR cannot remain only an AI user

• HR as decision supporter, not system owner

• Risks of unstructured AI usage

Output: HR AI application scope map

• AI vs human judgment: practical boundaries

• When AI supports, informs, or is excluded

• “Human-in-the-loop” explained practically

Exercise:

• Classify HR decisions by AI support level

• AI-assisted JD structuring and role clarity

• Candidate screening logic and bias awareness

• Scenario thinking for manpower demand

Lab:

• Design an AI-assisted recruitment decision workflow

• Risks identified

• Controls required

• AI-assisted KPI alignment and clarity

• Evidence-based performance narratives

• Supporting PIP preparation responsibly

Lab:

• Build an AI-assisted appraisal & PIP draft (with controls)

• What managers should and should not use AI for

• Coaching scripts and difficult conversations

• HR’s role in standardising manager AI usage

Design Task:

• Line Manager AI Support Toolkit

• Data privacy and confidentiality rules

• Bias, hallucination, and misuse risks

• HR accountability vs IT accountability

Output:

• HR AI Usage & Control Checklist

• Using AI to analyse engagement data (limits)

• Avoiding surveillance and trust erosion

• Turning insights into HR actions

Lab:

• Build an AI-assisted engagement insight workflow

• Risks, value, and controls alignment

• AI-supported capability gap analysis

• Simple workforce scenario planning

• Linking people insights to business needs

Lab:

• Workforce scenario analysis using AI

• From task automation to decision support

• Integrating recruitment, performance, L&D

• Measuring time saved and quality improved

Group Work:

• AI-assisted HR workflow design

• 90-day HR AI implementation roadmap

• Manager engagement plan

• Final commitments