The hype cycle is over, the reality remains: language models are a powerful tool — but a tool, not an end in themselves. The question isn’t “where can we use AI?” but “where is there real, measurable value?”.
Three patterns that pay off
- Unstructured to structured. Turn emails, PDFs and tickets into clean fields. High hit rate, clear ROI, easy to verify.
- Assistance, not autonomy. The AI suggests, the human decides — in support, case work, sales. Speed plus control.
- Search over your own knowledge. Make internal documents searchable, with citations. Saves time without inventing facts.
What these share: the human keeps the decision, and every output is checkable.
Three patterns where AI (still) disappoints
- Hard correctness without review. Where a wrong number is expensive and no one proofreads, an LLM is the wrong tool.
- Fully autonomous chains. Multi-step agents without a human checkpoint sound tempting but break at the edges in practice.
- “AI for AI’s sake.” A feature with no problem behind it only costs trust.
What a sensible start looks like
Start small, close to the real process, with a clear metric:
Handling time per case: -38%
"Suggestion accepted" rate: 71%
Escalation to a human: always availableA well-chosen first use case funds the next. We start where the value-to-risk ratio is best — EU-compliant and with data that never leaves the building.