Business fields · Project Management
AI training for Project Managers
Project management is largely information work: clarifying requirements, building plans, assessing risks, reporting status and keeping a wide range of stakeholders aligned. Generative AI speeds up exactly these activities. It turns meeting notes into minutes and action lists, structures project charters and work breakdown structures, writes status reports for different audiences and supports risk workshops with well-grounded suggestions. AI agents connect project management tools, inbox and calendar and send automatic reminders about overdue tasks. Whether you work waterfall, agile with Scrum or hybrid, project leads gain time for what AI cannot do: making decisions, resolving conflicts and leading the team.
Who is this course for?
- Project managers
- PMO staff and portfolio managers
- Scrum Masters and agile coaches
- Workstream and work package leads
- Business teams with occasional project responsibility
Typical challenges we address
- Heavy documentation workload for minutes, reports and plans
- Many stakeholders with different information needs
- Risks and dependencies spotted too late
- Information scattered across tools, emails and chats
Practical scenarios from your field
Meeting minutes and actions
Notes or transcripts become structured minutes with decisions, open points and actions including owners and due dates, ready to be transferred into the project tool.
Project charter and WBS
AI helps turn a project idea into a charter with objectives, scope boundaries and success criteria, plus an initial work breakdown structure with work packages and milestones.
Audience-specific status reports
From raw data such as task progress, budget and risks, AI drafts status reports at different levels of detail – concise for the steering committee, detailed for the core team.
Identifying risks
In risk workshops AI suggests typical risks for the project type and industry, helps assess likelihood and impact and drafts mitigation actions. Owners and review dates are assigned straight away.
Agile artefacts
User stories with acceptance criteria, backlog refinement, sprint goals and retrospective formats are prepared with AI and then sharpened together by the team. Definitions of done can be drafted too.
Automated follow-up
AI agents check task progress regularly, remind owners about overdue items, summarise the week's changes and prepare a short project newsletter from them. The team stays informed without extra effort.
Possible hands-on projects
RAID log app
A small web app for maintaining risks, assumptions, issues and dependencies with ratings, owners and a colour-coded overview for the steering committee.
Status report generator
An internal tool that captures RAG status, milestones and key messages via a form and produces a consistently formatted report.
Capacity planner
A simple app that visualises team members, availability and project assignments and highlights overload week by week. Holidays are taken into account automatically.
All 15 courses for Project Managers
AI for business (12)
- ChatGPT for Project Managers
- Claude for Project Managers
- Microsoft 365 Copilot for Project Managers
- Google Gemini for Project Managers
- AI Agents for Project Managers
- Prompt Engineering for Project Managers
- Generative AI for Project Managers
- n8n for Project Managers
- Make for Project Managers
- Perplexity for Project Managers
- Mistral Le Chat for Project Managers
- EU AI Act & AI Compliance for Project Managers
Vibe & agentic coding (3)
Data protection & compliance
Project documents often contain confidential client data, contract details and personal data about team members, which may only be processed in approved AI environments. Analysing employee performance or workload data requires compliance with the GDPR and, where applicable, works council co-determination rights.
Prerequisites
Experience leading or contributing to projects, whether traditional, agile or hybrid.
Frequently asked questions
Can AI create a project plan?
AI provides a solid first draft of the work breakdown structure, milestones and dependencies if you describe objectives and constraints clearly. Effort estimates, resources and priorities still need to be agreed with the team. The course shows how to review AI drafts systematically and transfer them into your project tool.
Does this work in agile projects too?
Yes. In Scrum or Kanban, AI helps write user stories and acceptance criteria, prepare refinements and retrospectives and summarise sprint results for stakeholders. Decisions about the backlog and delivery naturally remain with the team and the Product Owner. AI supports, the team decides.
Request without obligation
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