Using and applying AI in process management

Fundamentals of AI tools and prompt engineering

• Introduction to AI tools and prompt engineering (targeted formulation of inputs for AI tools).
• Definition of artificial intelligence and key concepts of generative AI tools.
• Typical use cases for generative AI along your own processes and tasks in process management.

Intelligent prompts and dialogues with AI tools

• Roles of user prompts, system prompts, history (chat history), and memories in AI tools.
• Development, adaptation, and design of effective dialogue structures and prompts.
• Dealing with context control and critically questioning AI results.

Ensuring quality: checking and improving results

• Critical review and iterative improvement of AI interaction.
• Avoiding typical pitfalls and types of errors (e.g., hallucinations, loss of context).
• Best practices, dos and don'ts, own use cases.

AI use cases and workflows in your process management

• Systematic analysis of AI use cases from real challenges in your process management.
• Assessment and evaluation of use cases based on effort, benefits, and risk factors.
• Handy-on Development and testing of at least three ready-to-use AI workflows based on the most relevant AI use cases, e.g.
  • Process history assistant
  • Feedback Analyzer
  • Automation Potential Scout
  • SOP Generator (Standard Operating Procedure)
  • Lessons Learned AI
• Practical application and simulation on your own processes and areas of responsibility.

Action plan for AI integration in your process management

• Development of concrete measures for the steps from the first prototype to stable rollout in your department/company.
• Customized stakeholder analysis and consideration of typical barriers to implementation in AI-based process innovations.
• Designing effective change management and communication strategies.