How experimentation turns ordinary users into AI experts

Experimentation defines advanced users

A Microsoft study found that people who master artificial intelligence behave differently: they test different applications of the technology more frequently. Advanced users are 68% more likely to experiment with new ways of using AI than beginners.

In addition to testing more, these users also spend more time reflecting before starting a task, persisting after an unsatisfactory result, and searching for new commands.

Learning happens during use

The practice of experimenting changes the relationship with the tool. By applying AI to real problems, professionals discover where it adds value and how it can be adjusted.

According to Microsoft, experienced users are 49% more likely to pause before a task to assess whether AI can help, 30% more likely to keep trying when the first answer doesn’t work, and 56% more likely to research and test new prompts.

A bad answer stops being just frustrating and becomes a clue to what needs to be changed in the next attempt.

Error is part of the process

Working with AI involves dealing with incomplete answers, incorrect interpretations, and commands that don’t produce the expected result. That’s why persisting after a first bad attempt is a common trait among advanced users.

These professionals treat AI responses as a starting point and focus more on review and quality control rather than accepting any output without criticism.

Start with simple, recurring tasks

You don’t need to overhaul your entire routine to get familiar with AI. An effective strategy is to choose recurring activities and test different ways of applying them.

For example, comparing a response generated from a generic request with another that includes context, purpose, and desired format can reveal significant improvements.

When experimenting with a new task, you can observe where the technology truly saves time or improves the quality of the result. This practical experience turns curiosity into skill.