Apple used its fiscal third quarter earnings call, held on July 30, to argue that some enterprise AI workloads are better suited to run on endpoint devices like Macs, while continuing to rely on the cloud for others, citing reduced costs and enhanced privacy. The company highlighted concerns over high recurring inference costs associated with cloud-based AI deployments, noting that cloud GPUs are expensive to rent and every AI query consumes compute, with costs growing as deployments move from pilot projects into production. Apple positions its approach as an alternative for certain workloads: a Mac, local inference, lower cloud spend, and better privacy. If adopted more broadly, the approach could influence how enterprises decide where different AI workloads should run. The discussion came during a quarter in which Apple reported revenue of $109.4 billion, up 16% year over year, with Mac revenue rising 29%. Tim Cook emphasized Apple's commitment to AI through hardware advancements since the introduction of the Neural Engine in 2017. Industry observers note that as organizations expand AI deployments, recurring inference costs have become a growing concern alongside data governance and security.