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Enterprise AI Adoption Stalls As Inferencing Costs Confound Cloud Customers
According to market analyst firm Canalys, enterprise adoption of AI is slowing due to unpredictable and often high costs associated with model inferencing in the cloud. Despite strong growth in cloud infrastructure spending, businesses are increasingly scrutinizing cost-efficiency, with some opting ...
The Register reports:[Canalys] published stats that show businesses spent $90.9 billion globally on infrastructure and platform-as-a-service with the likes of Microsoft, AWS and Google in calendar Q1, up 21 percent year-on-year, as the march of cloud adoption continues. "Unlike training, which is a one-time investment, inference represents a recurring operational cost, making it a critical constraint on the path to AI commercialization," said Canalys senior director Rachel Brindley. "As AI transitions from research to large-scale deployment, enterprises are increasingly focused on the cost-efficiency of inference, comparing models, cloud platforms, and hardware architectures such as GPUs versus custom accelerators," she added.
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