Frankfurt am Main, GermanyWhat is AI automation?
AI automation combines language and document processing with defined work steps. Unlike a standalone chat window, a workflow puts information into a process, uses approved systems, and passes results to the people responsible.
1. Start with recurring tasks, not spectacular ideas
A good first process occurs frequently, has a known input, and produces a verifiable result. Examples include transferring quote data from PDFs into a draft comparison, routing tenant requests to the responsible team, or organising group enquiries at a hotel.
Rare exceptions, critical decisions, and incomplete data need clear rules first. Not every problem calls for AI: sometimes a better template or simple rule-based automation is enough.
2. Check data and integrations early
Where is the information stored? Who is allowed to see it? Which document version applies? Can systems be connected through existing interfaces? Without these answers, a technically impressive demo can fail in everyday use.
3. Assess time savings and business value separately
Time saved through technology first creates additional capacity. Business value only emerges when that capacity is put to good use. Rework, approvals, operating costs, and error rates must all be considered.
Test your assumptions in the ROI calculator4. Every pilot needs clear acceptance criteria
Define in advance which information must be correct, which errors are tolerable, and when people should take over. Test representative cases and difficult exceptions, not just a few ideal examples.
5. Ultimately, people make the difference
A team needs to understand when it can trust a result and where review is necessary. Training, feedback, and clear responsibilities determine whether a workflow is truly adopted.
Ask the right next question for your business
Which recurring process is keeping your team busy—and what would a verifiably better result look like? That question is the foundation for a solid start.