Key Features of AI Applications in Project Management

1. Introduction to AI and Generative AI (GenAI) in Project Management

• What is AI? Overview of Machine Learning (ML) & Natural Language Processing (NLP)
• Understanding Generative AI & how it’s transforming project management
• AI-driven automation, analytics, and workflow optimization
• The role of Large Language Models (LLMs) in project management

2. Introduction to AI-Powered Project Management Tools

• AI-based platforms: Notion AI, ClickUp AI, Trello AI, Microsoft Copilot, Asana AI
• Exploring task automation, document summarization, and intelligent insights
• AI-powered email automation, scheduling assistants, and predictive forecasting
• Ethical considerations & challenges of AI in project management

3. Introduction to Prompt Engineering for Project Managers

• What is Prompt Engineering and why does it matter?
• Types of prompts: Instruction-based, Chain-of-Thought, Role-based prompts
• Crafting effective prompts for task management, risk assessment, and reporting
• Advanced techniques: Few-shot prompting, context-setting, and AI persona creation

4. AI-Driven Risk Management and Decision Support

• Using AI for risk assessment, issue tracking, and mitigation planning
• AI-driven predictive analytics for project success probability
• Automating decision-making using AI-driven insights

5. AI-Powered Project Collaboration and Stakeholder Engagement

• AI in real-time collaboration: Chatbots, AI-driven meeting notes, automated follow-ups
• AI-enhanced stakeholder management: Sentiment analysis & real-time feedback
• Using AI for automated email responses, chat summarization, and knowledge management

6. AI for Agile and Traditional Project Planning

• AI-driven Gantt charts, roadmaps, and backlog prioritization
• Using AI for automated sprint planning and retrospective analysis
• AI-powered Kanban board optimizations and workload distribution Workshop: Conducting a release planning session in Jira

7. AI for Reporting, Forecasting, and Data Visualization

• AI-powered project dashboards: Customizing real-time reports
• Generating predictive analytics for resource allocation & project health
• AI-driven data visualization for better decision-making

8. AI for Automation and Workflow Optimization

• AI-driven workflow automation & task dependencies
• Using Jira AI, Notion AI, and Zapier AI for automating routine project tasks
• AI in change management, compliance tracking, and knowledge retention

9. Final Hands-On Exercise and Question and Answer

• Applying AI knowledge in real-world project management
• Group activity: Building an AI-driven project workflow
• Final Q&A, troubleshooting, and next steps