Artificial Intelligence is changing project management by automating routine tasks, streamlining workflows, and helping us make better decisions. In this course, you’ll learn to use AI tools for scheduling, managing risks, communicating and allocating resources. You’ll find out how to bring AI into your daily work, think through ethical issues, and combine automated insights with your own judgment. By the end, you’ll know how to use AI to make your projects run more efficiently while staying in control.
Master Future-Ready PM Skills
AI competencies are now essential for project professionals. 93% of companies investing in AI for project management report increased project success and ROI.
Automate and Optimise
Learn how to use AI to automate repetitive tasks, enhance scheduling, and improve collaboration. Free up time for high-impact strategic activities rather than routine admin work. Gartner forecasts that by 2030, 80% of project management tasks will be managed by AI, making automation ubiquitous in portfolio and resource planning.
Make Data-Driven Decisions
Use predictive analytics to detect risks early and leverage real-time data to increase accuracy, minimise budget overruns, and improve resource allocation. 54% of project professionals say AI-driven analytics have enhanced project agility and real-time adaptability, increasing their ability to respond to changing priorities.
Adopt Leading Tools
Get hands-on with industry-leading AI PM software used by top organisations in 2025, including ClickUp, Asana, Notion, and Zapier.
Navigate AI Ethics and Human-AI Balance
Address biases, data privacy, and understand the limits of AI—keeping human expertise at the heart of leadership and project strategy.
Stay Ahead of Trends
The market for AI-driven project management is expected to reach $7.4 billion by 2029 (CAGR 19.9%) as organisations invest in digital fluency for their PM workforce.
Learning Objectives
- Explain how AI enhances planning, scheduling, risk management, and communication in projects.
- Demonstrate how AI-powered automation can improve project efficiency and reliability.
- Use AI-driven tools for risk assessment, predictive analytics, and resource allocation.
- Apply AI to streamline repetitive tasks and boost collaboration across teams.
- Discuss ethical issues, potential biases, and data security concerns in AI-driven project management.
- Balance automated insights with human judgment for optimal results.
Key Themes in AI and Project Management
- AI in project management
- Project management automation
- Predictive analytics for projects
- AI PM tools and skills
- Digital transformation for project managers
- AI scheduling and risk management
- Project management certification AI
- Human-AI collaboration in PM
- AI ethics in project management
- Next-gen project management course
FAQ
- Why is AI important for project management in 2025?
AI is now core to project management, enabling faster, smarter decisions and freeing professionals from routine admin. Most organisations report improved project outcomes and ROI after implementing AI-driven PM solutions.
- What practical skills will I learn in this course?
You’ll learn to automate tasks, use predictive analytics for risk management, optimise resource allocation, enhance team communication with AI, and confidently evaluate the ethical and strategic implications of using AI in projects.
- How does AI training benefit my project management career?
AI skills rank among the top credentials for PMs in 2025 with access to advanced roles, higher salaries, and the ability to lead digital transformation projects across industries.
- What AI tools will I gain proficiency in?
You’ll explore top platforms like ClickUp, Asana, Notion, Zapier, and Trello, as well as specialised AI plugins for workflow automation, chatbots, and data analytics.
- Is this course relevant for traditional project managers?
Even classic methodologies are now supported by AI for planning, reporting, collaboration, and risk assessment. The course bridges traditional PM best practices and next-gen technology.
- What are the biggest challenges of using AI in PM?
Potential problems are overreliance on algorithms, data privacy and bias issues, and underestimating the value of human insight. This course covers how to balance automation with ethical leadership and effective problem-solving.
- What are the future trends for AI in project management?
Advances in real-time predictive analytics, self-updating project dashboards, more competent virtual assistants, and fully integrated PM ecosystems. Digital fluency and AI awareness are emerging as must-have skills for every PM.
Course Outline
Session One: Course Overview
- Learning Objectives
- Pre-Assignment
- Pre-Course Assessment
Session Two: Understanding AI in Project Management
- The Role of AI
- Using AI to Solve Challenges
Session Three: AI for Planning and Scheduling
- How AI Can Help
- AI-Powered Scheduling
Session Four: AI and Risk Management
- Predictive Analysis and Early Warnings
- Risk Scenario Analysis
Session Five: Communications and Collaboration
- AI-Powered Chatbots and Virtual Assistants
- Enhancing Team Collaboration
- Using Chatbots and Virtual Assistants
Session Six: Data Analysis and Decision-Making
- Data Processing and Insights
- AI-Driven Decision Support Systems
- Real-Time Data Challenge
Session Seven: AI and Task Automation
- Automation and Workflow Optimisation
Session Eight: Understanding AI Limitations
- Lack of Human Intuition and Judgement
- Ethical Implications and Biases in AI Algorithms
- Human Decision-Making
Session Nine: Addressing Data Challenges
- AI Requires Large Volumes of Quality Data
- Challenges with Data Privacy and Security
- Limitations in Handling Unexpected Changes
- Integration Challenges in AI
- Impact of Data Quality on AI
Session Ten: Case Studies and Real-World Examples
- Successfully Implementing AI
Session Eleven: The Future of AI in Project Management
- Emerging AI Trends in Project Management
- Preparing for an AI-Driven Future
Session Twelve: Using AI Tools
- Introduction to AI in Project Management
- AI Tool Applications
Personal Action Plan
Course Summary
Recommended Reading List
Post-Course Assessment
Curriculum
- 1 Section
- 9 Lessons
- 10 Weeks
