AI In Talent Management

AI in Talent Management: 2-Day Intensive Course

Course Overview

Duration: 12 hours (2 days × 6 hours each)
Format: Interactive workshop with lectures, hands-on activities, and group discussions
Target Audience: HR professionals, People Operations teams, HR leaders
Prerequisites: Basic understanding of HR processes; no technical background required

Course Objectives

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

• Understand AI fundamentals and identify key applications in HR
• Evaluate AI tools for recruitment, performance management, and employee experience
• Navigate ethical considerations and bias mitigation in AI-powered HR decisions
• Develop a practical implementation roadmap for their organization
• Measure ROI and effectiveness of AI initiatives in HR

Day 1: AI Foundations and Core Applications (6 hours)

9:00 AM – 10:30 AM: AI Fundamentals for HR (1.5 hours)

Learning Objectives:

• Define AI, machine learning, and automation in HR context
• Understand the business case for AI in human resources
• Identify current market trends and adoption patterns

Topics Covered:

• AI Basics for HR Professionals (30 minutes)
  • What is AI vs. traditional automation?
  • Types of AI: predictive analytics, natural language processing, computer vision
  • Common AI applications already in use (recommendation engines, chatbots, analytics)
• The Business Case for AI in HR (30 minutes)
  • Market trends: 67% of organizations planning AI adoption in HR by 2025
  • ROI examples: 50% reduction in time-to-hire, 25% improvement in employee retention
  • Competitive advantages and cost savings
• Current State of AI in HR (30 minutes)
  • Technology landscape overview
  • Success stories: Unilever, IBM, McDonald’s
  • Common implementation challenges and lessons learned

Activities:

• Group discussion: Current pain points in your HR processes
• Quick poll: AI readiness assessment
• Case study review: AI transformation success story

10:45 AM – 12:15 PM: AI in Talent Acquisition (1.5 hours)

Learning Objectives:

• Implement AI-powered recruitment strategies
• Understand automated screening and candidate matching
• Navigate bias considerations in recruitment AI

Topics Covered:

• Intelligent Recruitment (45 minutes)
  • AI-powered job posting optimization and candidate sourcing
  • Resume screening and ranking algorithms
  • Chatbots for candidate engagement and initial screening
  • Video interview analysis and assessment tools
• Bias Mitigation and Fair Hiring (30 minutes)
  • Understanding algorithmic bias in recruitment
  • Legal compliance considerations (EEOC guidelines)
  • Strategies for creating inclusive AI systems
  • Audit processes for AI recruitment tools
• Tool Evaluation Framework (15 minutes)
  • Key criteria for selecting AI recruitment platforms
  • Vendor evaluation checklist
  • Implementation timeline considerations

Hands-on Activity:

• Live demonstration of 3 AI recruitment tools
• Group exercise: Design bias-free job descriptions using AI
• Workshop: Create evaluation criteria for AI recruitment vendors

1:15 PM – 2:45 PM: AI in Performance Management and Employee Development (1.5 hours)

Learning Objectives:

• Design AI-enhanced performance evaluation systems
• Create personalized learning and development programs
• Implement continuous feedback mechanisms

Topics Covered:

• Intelligent Performance Analytics (45 minutes)
  • Real-time performance tracking vs. annual reviews
  • Predictive performance modeling and goal tracking
  • 360-degree feedback analysis using sentiment analysis
  • Early warning systems for performance issues
• Personalized Learning and Development (30 minutes)
  • AI-powered skill gap analysis
  • Customized learning path recommendations
  • Career progression predictions
  • Microlearning and adaptive platforms
• Employee Engagement Analytics (15 minutes)
  • Continuous pulse surveys with AI analysis
  • Social network analysis for team dynamics
  • Personalized retention strategies

Practical Exercises:

• Design a competency framework for AI analysis
• Create personalized development plans using AI insights
• Workshop: Build a continuous feedback system blueprint

3:00 PM – 4:30 PM: Employee Experience and Workplace Analytics (1.5 hours)

Learning Objectives:

• Optimize employee experience through AI insights
• Implement workplace analytics for better decision-making
• Create predictive models for employee behavior

Topics Covered:

• AI-Powered Employee Support (45 minutes)
  • HR chatbots and virtual assistants
  • Automated policy interpretation and guidance
  • Intelligent case routing and self-service optimization
  • Employee journey mapping with AI insights
• Workplace Analytics (30 minutes)
  • Space utilization and meeting room optimization
  • Collaboration pattern analysis
  • Hybrid work model optimization
  • Productivity and wellness tracking
• Predictive Employee Analytics (15 minutes)
  • Turnover prediction models
  • Absenteeism pattern analysis
  • High-performer identification
  • Succession planning analytics

Interactive Workshop:

• Design an AI-powered employee journey map
• Create workplace optimization scenarios
• Develop basic predictive models for employee outcomes

Day 2: Implementation and Strategic Applications (6 hours)

9:00 AM – 10:30 AM: Ethics, Compliance, and Risk Management (1.5 hours)

Learning Objectives:

• Navigate ethical considerations in AI-powered HR decisions
• Ensure compliance with employment law and regulations
• Develop governance frameworks for AI in HR

Topics Covered:

• Ethics Framework for AI in HR (45 minutes)
  • Fairness, accountability, and transparency principles
  • Privacy and data protection considerations
  • Employee consent and rights
  • Ethical decision-making frameworks
• Legal and Regulatory Compliance (30 minutes)
  • GDPR and data privacy regulations
  • Employment law implications of AI decisions
  • EEOC guidelines on AI in hiring
  • Documentation and audit requirements
• Governance and Risk Management (15 minutes)
  • AI governance committees and oversight structures
  • Risk assessment frameworks
  • Vendor management and due diligence
  • Crisis management for AI failures

Case Study Analysis:

• Legal challenges: HireVue lawsuit analysis
• GDPR compliance examples
• Bias detection and remediation case studies

10:45 AM – 12:15 PM: People Analytics and Data-Driven Decision Making (1.5 hours)

Learning Objectives:

• Implement comprehensive people analytics programs
• Create meaningful dashboards and reporting
• Use data insights for strategic HR decisions

Topics Covered:

• Advanced People Analytics (45 minutes)
  • Workforce planning and demand forecasting
  • Diversity and inclusion metrics and analysis
  • Compensation analytics and pay equity analysis
  • ROI measurement for HR initiatives
• Dashboard Design and Visualization (30 minutes)
  • Key HR metrics and KPIs for executives
  • Data visualization best practices
  • Storytelling with HR data
  • Real-time vs. historical reporting
• Data Quality and Management (15 minutes)
  • Data collection and cleaning processes
  • Integration with existing HRIS systems
  • Data governance for people analytics
  • Privacy and security considerations

Data Analysis Workshop:

• Hands-on experience with HR analytics tools
• Creating basic predictive models in Excel
• Dashboard design exercise
• Interpreting statistical results for business decisions

1:15 PM – 2:45 PM: Implementation Strategy and Change Management (1.5 hours)

Learning Objectives:

• Develop comprehensive AI implementation strategies
• Manage organizational change and user adoption
• Create realistic project timelines and budgets

Topics Covered:

• Strategic Planning for AI Implementation (45 minutes)
  • AI maturity assessment and readiness evaluation
  • Phased implementation approach and pilot programs
  • Stakeholder mapping and buy-in strategies
  • Budget planning and ROI projections
• Change Management and User Adoption (30 minutes)
  • Communication strategies for AI initiatives
  • Training programs for HR staff and managers
  • Overcoming resistance to AI adoption
  • Success metrics and milestone tracking
• Project Management Best Practices (15 minutes)
  • Implementation timeline development
  • Resource allocation and team structure
  • Risk mitigation and contingency planning
  • Vendor selection and contract negotiation

Strategic Planning Workshop:

• Create AI implementation roadmap for your organization
• Develop business case presentation
• Design change management strategy
• Build project timeline and budget estimate

3:00 PM – 4:30 PM: Future of AI in HR and Action Planning (1.5 hours)

Learning Objectives:

• Understand emerging trends in AI and HR technology
• Develop personal and organizational action plans
• Create ongoing learning and development strategies

Topics Covered:

• Emerging Trends and Future Applications (30 minutes)
  • Generative AI for HR content creation
  • Augmented reality for training and onboarding
  • Blockchain for credential verification
  • IoT and wearables for employee wellness
  • Future of work and human-AI collaboration
• Building AI Capabilities (30 minutes)
  • Developing internal AI expertise
  • Partnerships with technology vendors
  • Continuous learning and staying current
  • Building data literacy across HR teams
• Action Planning and Next Steps (30 minutes)
  • Individual action plan development
  • Organizational readiness assessment
  • 30-60-90 day implementation plan
  • Resource recommendations and continued learning