AI for HR: Practical Applications, Ethics, and Implementation Training Course

Fundamentals of AI in Human Resources

• Overview of AI capabilities applicable to HR, including LLMs, automation, and data analytics
• Identification of common HR use cases and their strategic impact
• Assessing organizational readiness and defining the scope for AI pilot projects

Ethical AI, Privacy, and Regulatory Compliance in HR

• Core principles of data privacy and the proper handling of personal data in HR contexts
• Addressing bias, ensuring fairness, and navigating legal considerations in recruitment and performance evaluation
• Establishing governance frameworks, approval processes, and documentation standards for HR AI projects

Advanced Prompt Engineering and Generative Workflows for HR

• Creating precise prompts for job descriptions, candidate screening summaries, and offer letters
• Utilizing templates and prompt patterns for HR communications and policy drafting
• Iterating on prompts, validating outputs, and implementing human-in-the-loop verification

Process Automation and Workflow Design

• Developing end-to-end workflows that integrate LLMs, spreadsheets, and HRIS systems
• Automating repetitive tasks such as interview scheduling, FAQ handling, and onboarding checklists
• An overview of integration patterns using APIs and low-code tools

People Analytics and AI-Enhanced Decision Making

• Applying AI to workforce analytics, including attrition prediction, skills gap analysis, and personalized learning recommendations
• Interpreting model outputs and effectively communicating insights to key stakeholders
• Defining KPIs and calculating ROI for AI-driven HR initiatives

Change Management and Implementation Strategy

• Forming cross-functional teams and developing stakeholder engagement strategies
• Planning pilot phases, rollout timelines, and training programs for HR teams
• Managing operational aspects such as monitoring, maintenance, and continuous improvement

Practical Workshop: Developing an AI-Enabled HR Solution

• Group exercise: identifying a specific problem, designing a solution, and creating associated prompts and workflows
• Presenting solutions and receiving peer feedback focused on ethical and operational viability
• Outlining next steps and providing templates for pilot implementation

Conclusion and Future Directions