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AI has quickly transformed from an experimental tool into a part of the daily work of IT teams. But it’s interesting to see how much it really costs businesses and whether companies have started to calculate AI costs as systematically as cloud services or software. dev.ua asked Anatoly Yevpak, Associate Director at Railsware, about budgets, the most popular tools, and the token economy within the company.

I was recently collecting fresh data for my Coupler.io team on how people are using Claude for analytics. It would seem that it is difficult to surprise us: we build a data platform with AI analytics ourselves, monitor the market and have a good understanding of where it is going. And yet, a few numbers surprised me. Not the direction of change, but its speed. Two years ago, we were just starting to explain to our audience that conversational analytics requires both data and processes. Today, 70% of Claude users have it set up as their only data tool. That is, for seven out of ten, it is no longer an addition to their usual BI or a way to test a hypothesis from time to time. It is the main place where they ask questions of their data. If you work with data, are responsible for analytical processes in a team, or are simply watching how AI enters business, I suggest you analyze together what exactly is changing in people's behavior around data and what this means for business analytics in the next six months.