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How to optimise enterprise AI costs: Control compute structure first

Companies looking to reduce AI costs should do more than pick cheaper models, an argument says. They need to cut unnecessary tokens and computation themselves. Ben Canning (벤 캐닝), chief product officer at Alteryx, wrote that model costs are becoming a new burden as corporate AI use moves from experiments to large-scale operations. He said firms should first decide whether a large language model is needed and build business-logic workflows to avoid repeated processing.