Training course · AI Agents · Project Management

AI Agents for Project Managers

Agentic AI for business teams: understand AI agents, automate workflows safely and keep control with human-in-the-loop and governance.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“AI Agents for Project Managers” is a hands-on course for roles such as Project managers, PMO staff and portfolio managers and Scrum Masters and agile coaches. Rather than learning AI Agents in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Project Management.

AI agents go a step beyond conventional chat assistants: they plan sub-tasks, use tools such as search, files or business applications and complete multi-step work largely on their own. Over two days you will learn how agents are built, how they differ from chatbots and traditional automation, and which tasks genuinely justify their use. Widely used platforms serve as practical examples, including Microsoft Copilot Studio, custom GPTs and Claude with projects and tool connections.

In the hands-on sessions you design agent workflows for tasks from your own area of work, from triaging requests through research and drafting to handing results over to business systems. You decide where a person reviews and approves, which permissions an agent receives and how errors are detected. A dedicated block covers governance, data protection and accountability, so that your agents not only work but remain controllable, traceable and defensible within your organisation.

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.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your 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

What you will be able to do

  • You can explain how AI agents are structured and clearly distinguish them from chatbots and classic automation.
  • You can select a suitable agent platform for your requirements using transparent criteria.
  • You can design an agent workflow for a real process in your area and build a working prototype.
  • You can define human-in-the-loop checkpoints, test cases and escalation rules.
  • Produce project documents such as charters, plans, minutes and reports faster and more consistently with AI.
  • Use AI as a sparring partner for risk analysis, planning and stakeholder communication.
  • Design simple automations for follow-up and reporting in your project environment.

Course outline

Day 1

Module 1 What makes an AI agent
  • Agent building blocks: language model, instructions, knowledge, tools and memory
  • How agents differ from chatbots, macros and classic workflow automation
  • Levels of autonomy: from suggestion-making assistants to agents that act independently
  • Realistically judging which tasks suit agents and which do not
Module 2 Platform overview: Copilot Studio, GPTs and Claude
  • Microsoft Copilot Studio: agents grounded in company data and connected to Microsoft 365
  • Custom GPTs: configuring instructions, knowledge files and actions
  • Claude with projects, knowledge bases and tool access via the Model Context Protocol
  • Selection criteria: data access, integrations, administration and licensing
Module 3 Designing and building agent workflows
  • Breaking tasks into steps and defining hand-offs between agent and human
  • Writing system instructions, examples and knowledge sources for consistent output
  • Connecting tools: search, documents, email, spreadsheets and business applications
  • Building a prototype agent for a real process from your own area
Module 4 Human-in-the-loop, quality and error handling
  • Setting approval steps, escalation rules and thresholds for human review
  • Test cases, evaluation criteria and spot checks for quality assurance
  • Common failure modes: wrong tool choice, endless loops and fabricated facts
  • Using structured user feedback to improve the agent over time

Day 2

Module 5 Governance, security and roll-out
  • Roles and responsibilities across business units, IT, data protection and works council
  • Least-privilege permissions, logging and protection against prompt injection
  • Positioning under the EU AI Act and GDPR: transparency, documentation and data flows
  • From pilot agent to production: operation, maintenance and measuring success
Module 6 Practice lab: Project Management
  • Meeting minutes and actions
  • Project charter and WBS
  • Audience-specific status reports
  • Identifying risks
  • Agile artefacts
  • Automated follow-up
Module 7 Data protection, quality & transfer to daily work
  • 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.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

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.

Prerequisites

You should already use an AI assistant such as ChatGPT, Copilot or Claude on a regular basis. No programming skills are required. Experience leading or contributing to projects, whether traditional, agile or hybrid.

Technical requirements

You will need a laptop with an up-to-date browser. Ideally you have access to at least one agent platform such as Copilot Studio, ChatGPT with GPTs or Claude; practice accounts can be provided if needed.

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.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Salzburg Request
  • Mon, 14 December 2026 – Tue, 15 December 2026 Online Request
  • Mon, 11 January 2027 – Tue, 12 January 2027 Online Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Augsburg Request
  • Wed, 3 February 2027 – Thu, 4 February 2027 Online Request

Frequently asked questions

Do I need programming skills to build AI agents?

No. The platforms used on the course rely on visual interfaces, plain-language instructions and ready-made connectors. You learn to specify agents precisely from a business perspective, connect tools and test workflows. Where deeper technical integration would be needed, you will know which requirements to put to your IT team.

Which platform will we use during the course?

The course is vendor-neutral and uses Microsoft Copilot Studio, custom GPTs and Claude as examples. You build your prototype on the platform that is available or planned in your organisation. The principles of workflow design, control and governance you learn carry over to other agent solutions as well.

How do I stop an agent from acting without control?

Through deliberate design: agents receive only the minimum permissions they need, critical actions such as sending, booking or deleting require human approval, and every step is logged. In addition, you define test cases and escalation rules. These are exactly the control mechanisms you develop for your own use case during the course.

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.

How much does “AI Agents for Project Managers” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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