AI+ Agile Project Management Fundamentals™

Smart Sprint Planning: Discover how AI-powered insights improve backlog prioritization, sprint forecasting, and resource allocation for predictable delivery.
Adaptive Workflow Optimization: Learn to use AI tools to track progress, identify bottlenecks, and automate routine tasks to keep projects moving smoothly.
Data-Driven Decision Making: Gain the ability to analyze real-time project metrics, risks, and team performance with AI support for faster, smarter decisions.
Enhanced Team Collaboration: Master intelligent communication and reporting tools that improve stakeholder alignment, transparency, and cross-functional teamwork.
Predictive Risk Management: Use AI to anticipate delays, budget overruns, and scope creep, enabling proactive planning and effective mitigation strategies.

At a Glance: Course + Exam Overview

Category	AI Business AI Professional All Courses Business Analyst Business Intelligence Analyst English Language Product Manager Program Director Project Management Practitioner Scrum Master
Program Name	AI+ Agile Project Management Fundamentals™
Prerequisites	Basic Understanding of Project Management: Familiarity with project lifecycle and management principles. Introductory Knowledge of Agile: Awareness of agile methodologies like Scrum and Kanban. Familiarity with AI Concepts: Basic knowledge of artificial intelligence and its applications. Problem-Solving Skills: Ability to address challenges in dynamic environments. Team Collaboration Experience: Comfort working in cross-functional, collaborative teams.
Exam Format	50 questions, 70% passing, 90 minutes

What You'll Learn

AI Integration in Agile Planning
Learn how to incorporate AI tools into sprint planning, backlog grooming, and resource allocation to improve forecasting accuracy and team productivity.
Smart Workflow Automation with AI
Gain expertise in automating repetitive project tasks such as status tracking, reporting, and documentation, enabling teams to focus on high-value work.
Data-Driven Decision Making
Understand how AI-powered analytics can help interpret project metrics, predict risks, and support faster, evidence-based decisions throughout the project lifecycle.
AI-Enhanced Risk and Issue Management
Discover how intelligent tools can identify potential bottlenecks, delays, and dependencies early, allowing proactive mitigation and smoother delivery.
Natural Language Processing for Collaboration
Learn to use NLP-based assistants to summarise meeting notes, extract action items, and improve communication across distributed Agile teams.
Predictive Sprint Performance Tracking
Master AI techniques to forecast sprint outcomes, measure velocity trends, and continuously optimise team performance.

Certification Modules

Module 1: Fundamentals of AI in Agile Project Management

1.1 Introduction to AI Concepts for Project Managers
1.2 Synergy Between AI and Agile Methodologies
1.3 Case Study: AI-Enhanced Sprint Planning
1.4 Hands-On Session: AI Tools Walkthrough for Sprint Planning and Backlog Grooming

Module 2: Data Literacy for Agile Project Managers

2.1 Understanding Project Data Types and Sources
2.2 Data-Driven Decision Making in Agile
2.3 Case Study: Data-Led Sprint Retrospectives
2.4 Hands-On Simulation Exercise: AI-Driven Sprint Prediction and Metrics Analysis

Module 3: AI for Resource and Team Management

3.1 Predictive Resource Allocation
3.2 AI-Driven Agile Metrics and Performance Tracking
3.3 Use Cases: Smart Scheduling and Workload Balancing
3.4 Hands-On Session: Managing Team Capacity and Task Distribution Using AI Dashboards

Module 4: Predictive Analytics in Agile Project Management

4.1 Foundations of Predictive Modelling
4.2 Forecasting Delays and Resource Shortages
4.3 Case Studies: Early Risk Detection in Agile Projects
4.4 Hands-On Simulation Exercise: Resource Shortage and Timeline Forecasting

Module 5: AI in Project Monitoring and Reporting

5.1 Real-Time Monitoring with AI
5.2 Intelligent Reporting and Stakeholder Communication
5.3 Use Cases: Automated Status Updates and Performance Reviews
5.4 Hands-On Session: Creating AI-Powered Reports and Visual Dashboards

Module 6: Ethics, Bias, and Regulation in AI for Project Management

6.1 Ethical AI in Decision-Making
6.2 Bias and Risk in Predictive Models
6.3 Regulatory and Compliance Considerations
6.4 Hands-On Exercise: Evaluating AI Outputs for Fairness and Responsible Use

Module 7: Evaluating and Implementing AI Tools in Agile Projects

7.1 Selecting the Right AI Solutions
7.2 Change Management and Stakeholder Adoption
7.3 Case Study: AI-Automated Reporting and Risk Forecasting in Consulting Projects
7.4 Hands-On Simulation Exercise: Tool Evaluation and Vendor Comparison
7.5 Hands-On Exercise: Measuring AI Effectiveness with Project Analytics Platforms

Module 8: Future Trends and AI in Agile Project Management

8.1 Autonomous and Self-Optimising Projects
8.2 AI for Remote and Distributed Agile Teams
8.3 Case Studies Inspired by Industry Trends
8.4 Hands-On Simulation Exercise: Designing an AI-Augmented Agile Workflow

Industry Opportunities

AI+ Agile Project Manager
Lead cross-functional teams using Agile and AI-driven insights to deliver projects faster, improve predictability, and maximise stakeholder value.
Agile Delivery Specialist
Implement Scrum, Kanban, and AI-powered planning tools to streamline workflows, remove bottlenecks, and ensure timely releases.
Project Data Analyst (AI-Enabled)
Use AI analytics to forecast risks, track sprint performance, optimise resource allocation, and support data-driven decision-making.
Agile Transformation Consultant
Guide organisations in adopting Agile frameworks enhanced with AI automation to improve collaboration, adaptability, and business outcomes.
Product Owner with AI Insights
Leverage AI tools to prioritise backlogs, analyse customer behaviour, and align product development with market needs.
Scrum Master (AI-Assisted)
Facilitate ceremonies, monitor team velocity with intelligent dashboards, and proactively address impediments using predictive insights.

Frequently Asked Questions

Yes, you’ll gain hands-on experience with AI-powered project management tools, sprint planning techniques, and Agile workflows, enabling you to apply these skills immediately to real projects and team environments.

This course uniquely blends Agile principles with AI capabilities, teaching you how to automate planning, improve forecasting, optimize resources, and make data-driven decisions for smarter and faster project delivery.

You’ll work on practical projects such as AI-assisted sprint planning, backlog prioritization, risk prediction, workflow automation, and a capstone project simulating an end-to-end Agile project lifecycle.

The course combines core Agile theory with interactive exercises, real-world case studies, hands-on tool usage, and guided simulations, ensuring you actively practice and apply concepts rather than just learning them passively.

You’ll develop in-demand skills in Agile frameworks and AI-driven project management, preparing you for roles such as Scrum Master, Agile Project Manager, Product Owner, or digital transformation lead across industries.

Prerequisites

Basic Understanding of Project Management: Familiarity with project lifecycle and management principles.
Introductory Knowledge of Agile: Awareness of agile methodologies like Scrum and Kanban.
Familiarity with AI Concepts: Basic knowledge of artificial intelligence and its applications.
Problem-Solving Skills: Ability to address challenges in dynamic environments.
Team Collaboration Experience: Comfort working in cross-functional, collaborative teams.

Exam Details

Duration

90 minutes

Passing Score

70%

Format

50 multiple-choice/multiple-response questions

Exam Blueprint

Fundamentals of AI in Agile Project Management	7%
Data Literacy for Agile Project Managers	15%
AI for Resource and Team Management	15%
Predictive Analytics in Agile Project Management	15%
AI in Project Monitoring and Reporting	12%
Ethics, Bias, and Regulation in AI for Project Management	12%
Evaluating and Implementing AI Tools in Agile Projects	12%
Future Trends and AI in Agile Project Management	12%