AI in project management training – plan projects faster, manage them smarter and implement them more efficiently
On request
Individual duration
Online, Munich or in-house
On request
German or English
Digital participant certificate
Artificial intelligence (AI) as a project assistant, decision-making aid and efficiency driver – modern project work rethought: project management is becoming more complex: more dependencies, shorter cycles, higher expectations. At the same time, project managers are faced with the challenge of evaluating information faster, making more informed decisions and leading teams efficiently through each project phase. Modern AI tools such as ChatGPT, Copilot and AI agents are revolutionizing precisely these tasks. Our AI in project management training shows you in a practical way how artificial intelligence relieves project management, increases planning quality and improves communication. You will learn how to use AI to initialize projects, analyze risks, automate documentation and accelerate coordination. With the right prompt engineering, AI becomes your daily sparring partner – reliable, precise and ready for immediate use.
Contents and procedure of AI in project management training
The training is practice-oriented – with immediately applicable methods, tools and AI-supported exercises for your everyday work.
- Goals, expectations and benefits of further training
- Basics of AI & language models (LLMs) explained in an understandable way
- Market trends, developments & significance for project roles
- Overview of AI tools: ChatGPT, Copilot, Gemini, Bing Chat and others.
- Setting up and configuring the tools
- Basic principles of Prompt Engineering
- Structured prompts for planning, risk analysis, communication & reports
- Advanced techniques: roles, perspectives, constraints, iterations
- Reusable prompt templates for project managers
- Best practices for consistent, reliable results
- Sparring for scope, goals, concepts and project descriptions
- Creation of business cases, fact sheets, presentations
- Deep research (for non-critical data)
- Cost estimation & resource planning
- Creation of project plans, communication plans, RACI matrices
- Automatic documentation: protocols, decisions, to-dos
- Knowledge management & team communication
- Creation of multilingual target group-oriented text, image & audio content for projects
- Method sparring for lessons learned, retrospectives, conflict resolution and moderation
- Process support in all phases: Initiation, planning, control, completion
- Reporting, status updates and documentation
- Analysis of risks, bottlenecks, dependencies
- Support with problem and change management
- Quality control for deliverables
- Use of AI agents for project monitoring
- Integration options for AI in existing systems
- API-based automations & workflows
- Evaluation of modern tool landscapes
- Use of AI functions in Jira, Confluence, Planner, Teams etc.
- Visualizations, icons & charts with DALL-E or similar tools
- Creating visual communication materials
- Design of kick-offs, workshops & stakeholder presentations
- Data protection & IT security
- Dealing with sensitive data & regulatory requirements
- Copyrights for AI content
- Risk analysis: hallucinations, bias, responsibility
- Overview EU AI Act & practical implications
- Organizational requirements for the sustainable use of AI
- AI-supported planning, coordination & risk analyses
- Support through all project phases via AI
- Creation of own prompts & workflows
- Automated project updates, risk logs & status reports
- Work on project examples from the participants
What you can apply directly after the AI in project management course
- Create AI-supported project plans, reports and analyses
- Automate documentation & communication
- Identify risks & bottlenecks more quickly
- Create AI-supported project documents (business case, presentation, RACI, etc.)
- Making stakeholder communication more efficient
- Sensibly integrate AI agents & AI tools into PM workflows
- efficiently solve your own project challenges with AI
Who is AI suitable for in project management training?
- Project managers & PMO employees
- Program and portfolio manager
- Managers & decision-makers
- Agile Leads, Scrum Master, Product Owner
- Teams in project management, change & transformation
- Companies that want to professionalize digital project work
Participation requirements for AI in project management training
No specific prior knowledge required.
About us as a training provider
We are a management consultancy with over 20 years of experience in project management, digital transformation and AI-based process optimization. Our training courses combine modern AI tools, tried-and-tested PM methods and realistic application examples – with direct added value for companies and teams. We empower project managers to use AI safely, efficiently and responsibly.
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Your speaker - expertise from leadership & complex projects
Principal Consultant for Project Management, Organization & Transformation. She stands for clarity in challenging situations and combines many years of experience in managing complex programs with a deep understanding of methods and AI. She shows how AI can be used effectively in projects – in a practical, structured and directly applicable way.
Request a non-binding appointment now
- Practical workflows: directly applicable AI solutions
- Individual customization: Content suitable for industry & project environment
- Experienced trainer: expertise from complex projects & AI applications
- Ready to use: prompts, templates & tools for your everyday project work
TISAX and ISO certification for the Munich site only
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TISAX and ISO certification for the Munich site only
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FAQ - AI in project management training
No. The training is structured in such a way that you can start directly without any prior technical training. Basics such as how AI models work, limits, prompting principles and safe use are explained in a practical way. All you need is experience in project management – you will learn the rest in the course.
Very practice-oriented. You will work with realistic project tasks, create prompts for planning, risk analysis and communication, automate documentation, develop reports and test AI-supported PM workflows. Each method is immediately applied in exercises so that you can use it directly in everyday project work.
We work with common tools such as ChatGPT, Copilot, Gemini and AI-supported PM automation solutions. On request, we can integrate your own systems such as Jira, Confluence, Planner, Teams or project management software. In in-house training courses, we can fully address your tool landscape.
AI supports scope definition, effort estimation, risk and dependency analyses, creation of RACI models, stakeholder analyses, communication plans, status reports and project documentation. This significantly reduces manual effort while increasing the quality, speed and structure of project work.
Yes – if governance, transparency and oversight are taken into account. In the seminar, you will learn secure prompting techniques, data protection-friendly usage methods and mechanisms such as model cards, transparent decision-making logic and approval processes. This ensures that AI remains legally compliant and can be used responsibly.
We show you how to use AI securely on the user side – including through anonymized input, local tools, secure company accounts and privacy settings. In in-house training courses, we work exclusively with synthetic or generic data. Data protection, security and compliance are always at the forefront.
No – AI takes over routine activities and provides sound analyses, but project management remains a human core competence. Leadership, stakeholder management, prioritization and conflict navigation are still tasks that require human judgment. AI will become a co-pilot and quality turbo, not a replacement.
Typical risks include the uncritical adoption of AI suggestions, hallucinations, incomplete data sets, misinterpreted analyses or inaccurate forecasts. In the seminar, you will learn how to reliably control these risks – through quality processes, human oversight, structuring techniques, explainability and clear release rules.