Key Takeaways
- AI agents complete multi-step tasks independently – from research assignments to process chains.
- The difference from a chatbot: agents plan, use tools and work while you do other things.
- For SMEs what counts is not the hype but the question: which process is worth starting with?
- Rule of thumb for the start: frequent, rule-based, time-consuming – and a human checks the result.
After the chatbot year comes the agent era – or so it sounds from every direction. In my keynotes I usually hear two reactions: fascination and the quiet question “What does that mean for us, concretely?”. Exactly this question deserves an honest answer.
What Distinguishes an AI Agent from a Chatbot?
A chatbot answers, an agent works: it breaks an assignment into steps, uses programs and data sources, checks interim results and reports back with the finished outcome. “Write me a summary” becomes “Monitor these five sources and file a briefing for me every morning”. This is no longer future music – but it needs smart guardrails.
Which Use Cases Pay Off First in SMEs?
- Recurring research: market, competitor or supplier monitoring.
- Document pipelines: turning inquiries, minutes or receipts into structured data and follow-up actions.
- Internal assistance: meeting preparation, summaries, follow-ups.
- Quality assurance: having texts, quotes and data checked against defined rules.
Where Is Caution Required?
Wherever mistakes are expensive or data is sensitive. Agents need defined boundaries: what may they do alone, where is a human sign-off mandatory? My recommendation from practice: start small, check results, build trust step by step – like a new employee in probation. And: understand processes first, then automate. A chaotic process only gets faster chaos through an agent.
Planning an event? As a keynote speaker for artificial intelligence, digitalization and Microsoft 365, I bring technology topics to the stage in a way that sticks – hands-on, entertaining and immediately actionable. Here you will find an overview of my keynotes.
Frequently Asked Questions (FAQ)
Do AI agents need their own IT infrastructure?
Not to start with – many tools run in existing environments such as Microsoft 365 or as cloud services. More important than infrastructure are clear processes and responsibilities.
How much time does an agent realistically save?
With well-chosen use cases, several hours per week and employee are realistic – the key is that the process occurs often enough to justify the setup effort.
Is the topic ready for an annual convention?
Yes – especially now: the technology is ready, orientation is missing. A keynote that separates hype from substance and shows concrete starting points hits the nerve of decision-makers.
