General Objective:

To enable participants to effectively integrate AI tools and AI agents into project management processes to improve efficiency, decision-making, and overall project performance.

Key Learning Objectives:

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

• Understand the role of AI in modern project management environments
• Identify project processes suitable for AI automation
• Apply AI tools for project planning, tracking, and reporting
• Design and implement AI-driven workflows using AI agents
• Improve project visibility and performance using AI-generated insights
• Recognize ethical, governance, and risk considerations in AI adoption
• Enhance collaboration and productivity through intelligent automation.

• Day 1: Introduction to AI in Project Management

• Module 1: AI Fundamentals for Professionals

• What is AI, Machine Learning, and Generative AI
• Types of AI applications in business
• AI capabilities and limitations.

• Module 2: AI in Modern Project Environments

• Evolution of project management
• AI use cases in project lifecycle
• AI vs traditional project tools
• Role of AI in PMO transformation

• Module 3: Opportunities and Challenges

• Benefits of AI adoption in projects
• Common implementation challenges
• Organizational readiness for AI

  Day 2: AI Tools for Project Planning and Execution

• Module 4: AI for Project Planning

• AI-assisted scope definition
• Work Breakdown Structure (WBS) generation
• Scheduling with AI
• Resource allocation optimization

• Module 5: AI for Monitoring and Control

• Predictive analytics in projects
• Risk identification using AI
• Performance tracking with AI dashboards
• AI-driven reporting and insights

Workshop

• Hands-on use of AI tools for planning and reporting

• Day 3: AI-Driven Workflows and Automation

• Module 6: Process Automation in Projects

• Identifying automation opportunities
• Mapping workflows for automation
• AI vs RPA (Robotic Process Automation)

• Module 7: Designing AI-Driven Workflows

• Workflow design principles
• Integrating AI into project processes
• End-to-end automation strategies

• Workshop

• Designing an AI-driven workflow for a project scenario

• Day 4: AI Agents and Intelligent Systems

• Module 8: Introduction to AI Agents

• What are AI agents?
• Types of AI agents (task agents, decision agents)
• Use cases in project management

• Module 9: Building AI Agent-Based Workflows

• Agent-based task management
• Automating communication and reporting
• Integrating agents with project tools

• Workshop

• Designing AI agents for project tasks
• Creating simple agent-based workflows

• Day 5: Governance, Ethics, and Implementation

• Module 10: AI Governance and Risk Management

• Data privacy and security
• AI risks in project environments
• Governance frameworks for AI adoption

• Module 11: Ethical Considerations

• Bias in AI systems
• Transparency and accountability
• Responsible AI practices

• Module 12: Implementation Strategy

• Building an AI adoption roadmap
• Change management for AI
• Measuring ROI of AI in projects

• Final Workshop

• Developing an AI-enabled project plan
• Group presentations and feedback.