People and Python in AI

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People and Python in AI

In yet another installment of “everyone is doing it, but no one knows how,” a recent NewVantage Partners survey found that while 93.9% of executives surveyed expect to increase their data investments in 2023, just 23.9% of organizations characterize themselves as data-driven. Where is all that investment going, if not to change the way their companies operate? What’s stopping these executives from imposing this vision of a glorious data future on their companies?

People. The problem is always people. Of these same executives, 79% cite cultural issues as the biggest impediment to embracing a data-driven future. It turns out to be easy to say “data-driven” but much harder to implement because people ultimately animate a business, not data. The key, then, is to ensure that data enables and augments people rather than replaces them.

To read this article in full, please click here

In yet another installment of “everyone is doing it, but no one knows how,” a recent NewVantage Partners survey found that while 93.9% of executives surveyed expect to increase their data investments in 2023, just 23.9% of organizations characterize themselves as data-driven. Where is all that investment going, if not to change the way their companies operate? What’s stopping these executives from imposing this vision of a glorious data future on their companies?

People. The problem is always people. Of these same executives, 79% cite cultural issues as the biggest impediment to embracing a data-driven future. It turns out to be easy to say “data-driven” but much harder to implement because people ultimately animate a business, not data. The key, then, is to ensure that data enables and augments people rather than replaces them.

To read this article in full, please click here

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