![\"cloud](\"https:\/\/www.newsbeep.com\/au\/wp-content\/uploads\/2025\/12\/gettyimages-1034035084.jpg\")
John Lund\/Photodisc\/Getty Images<\/p>\n John Lund\/Photodisc\/Getty Images<\/p>\n
Follow ZDNET: Add us as a preferred source<\/a> on Google.<\/p>\n ZDNET’s key takeaways Cloud-first approaches need to be rethought.AI contributes to escalating cloud costs.A hybrid model assures the best of both worlds.<\/p>\n A decade or so ago, the debate between cloud and on-premises computing<\/a> raged. The cloud handily won that battle, and it wasn’t even close. Now, however, people are rethinking whether the cloud is still their best choice for many situations.\u00a0<\/p>\n Also:\u00a0Cloud-native computing is poised to explode, thanks to AI inference work<\/a><\/p>\n Welcome to the age of AI, in which on-premises computing is starting to look good again.<\/p>\n There’s a movement afoot<\/p>\n Existing infrastructures now configured with cloud services simply may not be ready for emerging AI demands, a recent analysis<\/a> from Deloitte warned.\u00a0<\/p>\n “The infrastructure built for cloud-first strategies can’t handle AI economics,” the report, penned by a team of Deloitte analysts led by Nicholas Merizzi, said.\u00a0<\/p>\n Also:\u00a05 must-have cloud tools for small businesses in 2025 (and my top 10 money-saving secrets)<\/a><\/p>\n “Processes designed for human workers don’t work for agents. Security models built for perimeter defense don’t protect against threats operating at machine speed. IT operating models built for service delivery don’t drive business transformation.” <\/p>\n To meet the needs of AI, enterprises are contemplating a shift away from mainly cloud to a hybrid mix of cloud and on-premises, according to the Deloitte analysts. Technology decision-makers are taking a second and third look at on-premises options.\u00a0<\/p>\n Also:\u00a0Want real AI ROI for business? It might finally happen in 2026 – here’s why<\/a><\/p>\n As the Deloitte team described it, there’s a movement afoot “from cloud-first to strategic hybrid — cloud for elasticity, on-premises for consistency, and edge for immediacy.” <\/p>\n Four issues<\/p>\n The Deloitte analysts cited four burning issues that are arising with cloud-based AI: <\/p>\n Rising and unanticipated cloud costs: AI token costs have dropped 280-fold in two years, they observe — yet “some enterprises are seeing monthly bills in the tens of millions.” The overuse of cloud-based AI services “can lead to frequent API hits and escalating costs.” There’s even a tipping point in which on-premises deployments make more sense. “This may happen when cloud costs begin to exceed 60% to 70% of the total cost of acquiring equivalent on-premises systems, making capital investment more attractive than operational expenses for predictable AI workloads.”Latency issues with cloud: AI often demands near-zero latency to deliver actions. “Applications requiring response times of 10 milliseconds or below cannot tolerate the inherent delays of cloud-based processing,” the Deloitte authors point out.On-premises promises greater resiliency: Resilience is also part of the pressing requirements for fully functional AI processes. These include “mission-critical tasks that cannot be interrupted require on-premises infrastructure in case connection to the cloud is interrupted,” the analysts state.Data sovereignty: Some enterprises “are repatriating their computing services, not wanting to depend entirely on service providers outside their local jurisdiction.”<\/p>\n