Subscribe to enjoy similar stories. Business technology leaders are winding down two years of fast-paced artificial intelligence experiments inside their companies, and putting their AI dollars toward proven projects focused on return on investment. “When generative AI came along, there was a certain amount of discretionary funding that we could look at to go experiment and test out some of the technology," said Jonny LeRoy, chief technology officer of industrial supplier W.W.
Grainger. “But really to scale beyond some of those experiments, we’re seeing the need to actually make a better business case." While technology leaders previously had the blessing of corporate leadership to freely experiment with AI, “the window for experimenting is mostly behind us now," Erik Brynjolfsson, co-founder of research and software company Workhelix, said Monday at The Wall Street Journal’s CIO Network Summit in New York. “This is a year where you have to be expecting business results," Brynjolfsson said, adding that the technology is mature enough to deliver them.
“This is a time when you should be getting benefits, and hope that your competitors are just playing around and experimenting." The problem is, roughly 70% of business customers’ generative AI projects are still stuck in pilot or testing phase, Philip Rathle, CTO of graph database software company Neo4j, said at the event. Generative AI models are good at summarizing text, for instance, but less capable of more sophisticated tasks, he added. Naveen Rao, vice president of generative AI at cloud data firm Databricks, said that some 90% of generative AI experiments aren’t making it beyond the lab.
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