By the end of this program, participants will be able to: 1. Explain the fundamentals of generative artificial intelligence and large language models. 2. Describe how generative AI technologies are influencing workplace productivity, decision-making, and HR practices. 3. Identify common AI tools and platforms used for business and HR applications. 4. Apply structured prompt engineering frameworks to generate more accurate and effective AI outputs. 5. Demonstrate practical ways generative AI can support HR tasks such as communication drafting, policy explanation, research, and problem analysis. 6. Evaluate the limitations and ethical considerations associated with AI use, including bias, misinformation, and the importance of human oversight. 7. Integrate AI tools into everyday professional workflows to improve efficiency, creativity, and decision support.

By the end of this program, participants will be able to: 1. Explain the legal, regulatory, and organizational foundations of employee performance and behavior documentation. 2. Apply objective documentation principles using the Situation-Behavior-Impact (SBI) model. 3. Differentiate between coachable performance issues and matters requiring immediate HR escalation. 4. Evaluate documentation for bias, speculative language, and potential EEOC or legal risk. 5. Develop clear and measurable corrective action and performance improvement plans. 6. Integrate generative AI tools into documentation workflows while maintaining governance and confidentiality safeguards. 7. Assess the legal discoverability and compliance implications of AI-assisted documentation.

By the end of this program, participants will be able to: 1. Explain how generative AI tools can support leadership coaching and organizational development while maintaining ethical and professional standards. 2. Analyze the role of emotional intelligence, self-reflection, and cognitive awareness in effective coaching conversations. 3. Apply structured coaching frameworks to improve employee engagement, performance development, and accountability. 4. Demonstrate active listening and coaching dialogue techniques that strengthen trust and psychological safety in workplace conversations. 5. Integrate generative AI tools into leadership coaching preparation, conversation design, and follow-up reflection activities. 6. Evaluate ethical considerations, including bias detection, confidentiality, and responsible AI use in leadership coaching and HR practice. 7. Develop an action plan for applying AI-supported coaching techniques within their leadership or HR role.