AI agents in practice: Strategic classification for decision makers

What are AI agents really?

• Definition without marketing hype: The three core skills (planning, tool use, memory).
• Clear distinction: RPA vs. chatbot vs. workflow vs. agent.
• Live demo: An agent in action – from input to independent result.
• Technological basis explained in an understandable way: What you need decision maker as decision maker .

Where agents are productive today!

Where agents don't (yet) work!

Use cases from various industries.

Identify processes for the use of agents

• Process evaluation framework: Where is it worth using?
• The four criteria: repeatability, data quality, risk acceptance, ROI.
• Quick assessment for your own company.

Challenges in practice

• Data protection and GDPR compliance: What needs to be considered.
• Hallucinations and sources of error: How to deal with them.
• Change management: Getting teams on board.
• Vendor selection: In-house development vs. platform solutions.

Technology landscape for decision makers

• Overview without technical deep dive: What do LLMs, RAG, and multi-agent systems mean?
• Integration into existing system landscapes (CRM, ERP, HR systems).
• Build vs. Buy: When which approach makes sense.

Trends for the next 12-18 months

• Multi-agent systems: Cooperation between specialized agents.
• Agent-to-agent communication: What does this mean for processes?
• Physical applications: When robotics and IoT become relevant.
• Self-learning systems: Opportunities and risks of autonomy.