Learning Objectives:
- Understand the basics of generative AI and its relevance to Agile.
- Identify practical applications and benefits of AI in Agile environments.
Gen AI Enterprise for Agilists
Gen AI Enterprise for Agilists is an advanced, hands-on training program designed for Agile leaders and transformation professionals who want to leverage Generative AI to improve enterprise agility, portfolio planning, program execution, product ownership, and Agile transformatio...
- 16-Hour Live Instructor-Led Training
- 30+ Hands-On Activities based on Transformation Use Cases
- 4 Enterprise-Scale AI Projects
- 200+ AI Prompts for Agile Teams, Programs, and Portfolios
Overview
Gen AI Enterprise for Agilists is an advanced, hands-on training program designed for Agile leaders and transformation professionals who want to leverage Generative AI to improve enterprise agility, portfolio planning, program execution, product ownership, and Agile transformation initiatives. The course focuses on integrating AI into Agile workflows, backlog management, sprint planning, team coordination, metrics, reporting, workflow automation, and enterprise-scale Agile transformations. Through practical activities, real-world simulations, and enterprise projects, learners gain the skills required to drive AI-powered Agile delivery and organizational transformation
Prerequisites
- Familiarity with Agile frameworks (Scrum, Kanban, SAFe)
- Experience working across multiple Agile teams or programs
- Exposure to program/portfolio-level Agile planning
- Experience in stakeholder communication and alignment
- Basic understanding of Gen AI tools such as ChatGPT
- Familiarity with JIRA, Confluence, Trello, Mural, etc.
- Involvement in Agile transformation or process improvement initiatives
Key Features
30+ Hands-On Activities based on Transformation Use Cases
4 Enterprise-Scale AI Projects
200+ AI Prompts for Agile Teams, Programs, and Portfolios
AI-Integrated Agile Workflows
Real-World Simulations for Distributed Agile Environments
Curriculum
1. Introduction to Generative AI in Agile Leadership
Learning Objectives:
Topics:
Explore the fundamentals of generative AI and its transformative impact on Agile leadership, collaboration, and delivery. Get hands-on with leading AI tools and real-world Agile use cases.
2. AI in Lean Portfolio Management
Learning Objectives:
Learning Objectives:
- Apply AI to define strategic themes, prioritize initiatives, and create business cases.
- Utilize AI tools to enhance portfolio-level planning and alignment.
Topics:
Learn how AI streamlines strategic planning, value stream mapping, and business case development in Lean portfolio management. Experience AI-driven prioritization and decision-making.
3. AI-Driven Program Backlog Management and PI Planning
Learning Objectives:
Learning Objectives:
- Use AI to automate and optimize backlog management and PI planning.
- Generate features, estimate values, and identify risks with AI-powered tools.
Topics:
Master the use of AI to automate backlog grooming, feature creation, estimation, and risk identification for more effective PI planning. Experience hands-on automation of Agile program workflows.
4. AI for Agile Coordination and Syncs
Learning Objectives:
Learning Objectives:
- Employ AI to monitor progress and manage dependencies in Agile teams.
- Use AI-driven insights to quickly resolve blockers and improve coordination.
Topics:
Discover how AI can streamline Agile coordination by tracking progress, identifying dependencies, and resolving impediments. Leverage AI insights to enhance team synchronization.
5. AI-Powered Sprint Planning
Learning Objectives:
Learning Objectives:
- Break down tasks and plan sprints efficiently using AI.
- Utilize AI integrations for capacity-aware and goal-driven sprint planning.
Topics:
Harness AI to optimize sprint planning through automated task breakdown, capacity planning, and goal setting. Integrate AI with popular tools for smarter, faster planning.
6. AI in Daily Stand-ups and Team Syncs
Learning Objectives:
Learning Objectives:
- Automating Daily Updates with AI
- Identifying Blockers via AI
- Summarizing Team Health with AI Tools
7. AI in Inspect and Adapt Workshops
Learning Objectives:
Learning Objectives:
- Facilitate AI-enhanced retrospectives and root cause analyses.
- Use AI to identify improvement opportunities and predict performance trends.
Topics:
Enhance retrospectives and continuous improvement workshops with AI-driven analysis, root cause identification, and performance forecasting. Drive actionable improvements with data-backed insights.
8. AI for Agile Product Ownership
Learning Objectives:
Learning Objectives:
- Generate and refine user stories and requirements with AI.
- Apply AI to split stories and define acceptance criteria efficiently.
Topics:
Empower product owners to write user stories, acceptance criteria, and non-functional requirements more effectively using AI. Streamline backlog management and story splitting with AI prompts.
9. Metrics and Dashboards with AI
Learning Objectives:
Learning Objectives:
- Create and visualize Agile metrics and dashboards using AI.
- Employ AI for predictive analytics and quality enhancement.
Topics:
Leverage AI to generate actionable OKRs, KPIs, and visual dashboards that drive Agile team performance. Use predictive analytics to enhance quality assurance and forecast trends.
10. Workflow Automation
Learning Objectives:
Learning Objectives:
- Integrate AI into workflow tools to automate Agile processes.
- Use automation to reduce manual effort and increase team efficiency.
Topics:
Automate Agile workflows by integrating AI with tools like Jira, Asana, and Zapier for seamless operations. Streamline repetitive tasks and boost productivity with AI-powered automation.
11. AI for Agile Transformation Roadmap
Learning Objectives:
Learning Objectives:
- Assess Agile readiness and design transformation strategies with AI.
- Define governance, guardrails, and communication plans using AI tools.
Topics:
Apply AI to assess Agile maturity, design transformation roadmaps, and establish governance for successful Agile adoption. Use AI insights to craft effective communication and team structures.
Module 12: Ethical AI Use & Future Trends in Agile
Examine the ethical implications, governance, and future trends of AI in Agile environments. Learn to identify and mitigate bias
while preparing for next-gen Agile+ AI integration.
Who Can Do
Ideal for
FAQ
1. What is the Gen AI Enterprise for Agilists course?
Gen AI Enterprise for Agilists is an advanced training program that teaches Agile professionals how to leverage Generative AI to improve portfolio management, program execution, sprint planning, backlog management, Agile transformation, workflow automation, and enterprise-scale delivery.
2. Who should enroll in this course?
This course is ideal for Agile Coaches, Scrum Masters, Product Owners, Product Managers, Program Managers, Portfolio Managers, Release Train Engineers, Agile Delivery Leads, Transformation Leaders, and stakeholders involved in Agile initiatives.
3. Are there any prerequisites for this course?
Yes. Participants should have a basic understanding of Agile frameworks such as Scrum, Kanban, or SAFe, along with familiarity with Agile tools like JIRA, Confluence, Trello, or Mural. Basic knowledge of Generative AI tools such as ChatGPT is also recommended.
4. What skills will I gain after completing this course?
You will learn how to apply Generative AI to Agile planning, backlog refinement, sprint execution, stakeholder communication, workflow automation, risk identification, dependency management, Agile metrics, and enterprise transformation initiatives.
5. Will this course include hands-on practice?
Yes. The course includes 30+ hands-on activities, 4 enterprise-scale projects, real-world simulations, and practical exercises based on Agile transformation use cases.
6. Which AI tools will be covered in the course?
Participants will work with Generative AI tools and learn how to integrate AI with platforms such as ChatGPT, JIRA, Confluence, Trello, Mural, Zapier, and other Agile productivity tools.
7. How can AI improve Agile delivery?
AI can automate backlog refinement, sprint planning, user story generation, risk analysis, dependency tracking, reporting, dashboard creation, and workflow automation, helping teams improve efficiency and decision-making.
8. Is this course suitable for enterprise-scale Agile environments?
Yes. The course focuses on portfolio, program, and team-level Agile practices and demonstrates how AI can support enterprise-scale Agile transformations and distributed Agile teams.
9. Will I learn how to create AI-powered Agile dashboards and reports?
Yes. The course covers AI-driven metrics, dashboards, predictive analytics, quality insights, KPIs, OKRs, and performance reporting for Agile teams and programs.
10. Does the course cover ethical AI usage?
Yes. The course includes a dedicated module on Ethical AI Use and Future Trends, covering responsible AI adoption, governance, bias mitigation, and best practices for AI implementation in Agile environments.
11. How long is the course?
The course consists of 16 hours of live instructor-led training.
12. What makes this course unique?
Unlike traditional Agile courses, this program focuses on the practical application of Generative AI across the Agile lifecycle, including planning, execution, coordination, automation, metrics, transformation roadmaps, and enterprise-level decision-making.
13. Will I receive a certificate after completing the course?
Yes, participants will receive a course completion certificate upon successfully completing the training requirements.
14. How can this course benefit my career?
The course helps professionals stay ahead in the rapidly evolving Agile and AI landscape by developing skills in AI-driven Agile leadership, transformation, automation, and enterprise delivery, making them valuable assets for modern organizations.
15. What practical outcomes can I expect after completing the course?
After completing the course, you will be able to:
- Use AI for portfolio and program planning.
- Automate Agile workflows and reporting.
- Improve backlog refinement and sprint planning.
- Create AI-powered dashboards and metrics.
- Identify risks and dependencies using AI.
- Lead AI-driven Agile transformation initiatives.
- Enhance collaboration across distributed Agile teams.
