Topic 04 / 063 articles
When automation is enough and when AI is needed, whether output is accurate enough, and how to prepare a team to work with AI.
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In most companies somebody already uses AI — each in their own way, with nothing agreed. What a team genuinely needs to learn, what is worth standardising, what must be checked, and when training is the wrong answer.
A demonstration always looks good, because the examples were chosen. Accuracy is your number, measured on your own cases — and you can measure it before you buy. How to do that without technical knowledge.
Both promise the same thing: the work happens without a person. The difference is not the subject but how certain the answer is. Automation gives the same answer every time; AI gives a likely one. How to choose, and why the cheaper option usually fits.
The services this topic is relevant to.
Workflow automation: whether a process is ready, what to automate and what not, the exception path, the audit trail and who owns the rules afterwards.
AI solutions: what kind of error is possible, how output is checked before use, where a human checkpoint belongs and when a plain rule is better.
AI training for teams by role and real tasks: practice on your own material, checking output, and safe handling of company information.
