by Rafi Kurlansik, Chris Klaczynski, Elliott Herz, Mikaila Garfinkel, Sam Shah, Francois Callewaert and Feng Pan
Archived. This article has not been updated since the publish date above. The dynamic nature of information means that previously accurate content can become outdated or even obsolete over time. Readers are advised to exercise due diligence and cross-check any information found in this blog post before making decisions or adopting any practices based on said information.
The historic surge of interest in large language models (LLMs) since ChatGPT launched to the public late last year has made the topic inescapable. Not only is the technology improving at an unparalleled cadence, but companies are also building their own models like never before. Now, predictive models are underpinning mission-critical tasks, giving organizations a window into the future instead of just a review of the past, and helping them operate quicker and leaner.
On the cusp of this new computing revolution, we were eager to learn exactly where enterprises are at in this transformation, as well as the platforms and tools they’re using to take advantage of it. By analyzing anonymized usage data from more than 9,000 global Databricks customers, we’ve compiled the 2023 State of Data + AI, a comprehensive look at organizations’ data and AI initiatives.
Here’s a glimpse at what we discovered:



While it’s still early days, these emerging trends are bound to define the future of AI. And business leaders need to pay attention. It's never been more clear: the companies that harness the power of DS/ML will lead the next generation of data.
Download the full report here to learn more!
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