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The Importance of Prioritizing Data Science and AI Use Cases
We see a lot of additional investment in AI right now because of the JatchPIT hype. But do you think that could take away maybe attention from executives and leaders on low-hanging fruit, simple use cases? Have you seen that there is a trade-off here when thinking about prioritization of data science and AI use cases? I think it's important to balanceIt. Actually, we do not struggle with that, but I can see that because there is so much hype for some of the executives who might actually concentrate on low-H hanging fruits.