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Data & AI

Artificial intelligence for a small business: where to start without overspending

· 1 min read

Reasonable first use cases for AI in a small company, its limits, and the questions worth answering before you invest.

Artificial intelligence can save work, but it is not a solution for everything. The costliest mistake is starting from the technology and looking for a problem afterwards. It works better the other way round.

Cases where it usually makes sense to start

  • Answering frequent questions with an assistant that consults your own information.
  • Classifying and summarizing emails, forms or documents before a person reviews them.
  • Extracting data from invoices, orders or other documents and passing it to your system.
  • Preparing draft reports from data you already have.

Limits worth keeping in mind

  • It can be wrong. For important tasks, a person should review the result.
  • Not all data should leave your company. Before using an external service, decide what information cannot be shared.
  • It works only as well as the information you give it.
  • Results should be compared with how things are done today, not just with what seems possible.

Questions before investing

  1. Which specific task do I want to improve, and how do I measure it today?
  2. What would a person do with the result, and who reviews it?
  3. What information would it use, and is it safe to share?
  4. What happens when it is wrong, and how do we notice?
  5. How will I know, with real examples, that it works well enough?

Test before integrating

A good path is to try the case with a small sample and real examples from your operation, measure how well it works, and only then connect it to the rest of your tools. If it does not work, you will have learned cheaply.

At D4 we evaluate each case with a goal and limits defined before choosing the technology. If you have a task in mind, tell us about it and we will see whether it makes sense.

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