A new IDC report has spotlighted AI-native cloud providers as the critical force propelling enterprises from proof of concept (PoC) to large-scale production in the generative AI (GenAI) era. The study identifies GMI Cloud and CoreWeave as the leading players redefining AI infrastructure, citing their strengths in technology innovation, ecosystem integration, product depth, and strategic foresight.
IDC’s findings suggest that while traditional cloud giants still dominate compute markets, a new generation of AI-native players—those built from the ground up around GPU acceleration, inference optimization, and compliance management—are becoming indispensable for enterprises scaling GenAI deployments.
The report forecasts explosive growth in GenAI adoption across the Asia-Pacific (APAC) region. By 2025, 65% of enterprises are expected to have more than 50 GenAI use cases in production, with over a quarter planning to exceed 100 active deployments. However, this acceleration also brings challenges: a shortage of high-performance inference infrastructure, growing data sovereignty pressures, and inefficient resource scheduling in multi-cloud environments.
IDC predicts that as large model pre-training matures, the market’s center of gravity will shift toward AI inference—the phase where real-world applications generate user-facing results. By 2025, 84% of organizations in APAC are expected to use AI inference infrastructure, yet nearly one-quarter report cost concerns as a key barrier. Balancing performance and affordability, the report concludes, is now the defining challenge for AI infrastructure providers.
IDC’s proposed solution: enterprises should prioritize dedicated AI infrastructure partners offering stable supply chains, local data centers, hybrid cloud flexibility, and regulatory compliance. These criteria, the report says, “perfectly align with GMI Cloud’s core strategy.”
In response to the shift toward inference, GMI Cloud has built a dual-engine architecture that mirrors IDC’s guidance for “high throughput, low latency, and cost-optimized” AI infrastructure.
Cluster Engine (IaaS layer):
Delivers modular and scalable resource scheduling combining reserved and on-demand capacity. It also supports Kubernetes cluster management, InfiniBand virtual networking, and customized private cloud deployments, ensuring both flexibility and data security.Inference Engine (MaaS layer):
Integrates nearly 100 large language and generative models worldwide, deeply optimizing open-source models to cut API latency and boost token throughput efficiency. It enables on-demand model hosting and dynamic scaling, directly addressing the industry’s cost-performance dilemma. IDC describes this as key to optimizing total cost of ownership (TCO) in AI deployment.
By October 2025, GMI Cloud will complete a foundational upgrade to create a globally integrated hybrid GPU cloud system. The upgrade will unify GPU scheduling across AWS, GCP, Alibaba Cloud, and private enterprise clusters via a single management plane, helping clients overcome “multi-cloud silos.” With localized data centers across North America, Europe, and APAC, the platform ensures both low latency and regional data compliance—a dual advantage for multinational enterprises.
IDC’s report underscores that supply chain stability is now the deciding factor in AI infrastructure success. According to survey data, 31.1% of APAC enterprises cite limited access to GPUs and high-performance infrastructure as their biggest roadblock in scaling GenAI.
Amid global GPU shortages—exacerbated by the rollout of NVIDIA’s H200 and B200 chips—IDC argues that only providers with strong supply chain ties can maintain reliable computing access. “A stable supply chain is the key prerequisite for AI-native cloud providers to gain a foothold in the market,” the report states.
Here, GMI Cloud’s partnership with NVIDIA sets it apart. As an NVIDIA Certified Partner (NCP) and one of only six global Reference Platform NCPs, GMI Cloud has established a seamless pipeline for next-generation GPUs. The company was among the first to support the H200 in 2024, launch the GB200 in sync in 2025, and secure early access to B300 resources.
This deep collaboration, IDC notes, enables GMI Cloud to deliver “zero-lag integration of next-generation GPU resources,” providing clients with uninterrupted, high-performance computing power and maximum GPU utilization through tight software-hardware integration. “Only AI-native cloud providers with stable supply chains,” IDC writes, “can truly alleviate enterprises’ computing power anxiety and move GenAI from pilot to production.”
In its “Advice for Technology Buyers” section, IDC explicitly recommends GMI Cloud and CoreWeave as the top AI-native providers for enterprise consideration. It advises organizations to prioritize partners “with stable supply chains, abundant resources, and strong technical consulting capabilities.”
GMI Cloud’s differentiator, according to IDC, lies in its expert-driven advisory services. Unlike hyperscale cloud providers, GMI Cloud offers end-to-end guidance—from GPU allocation and AI model selection to performance optimization and multi-agent deployment—helping businesses close the “GenAI operational gap.”
IDC China Research Director Lu Yanxia emphasized in the report that “to prepare for a future of multi-agent collaboration, enterprises must rebuild high-performance, reliable, and efficient AI infrastructure.” IDC positions GMI Cloud, with its model of “technological innovation + ecosystem integration + regional focus,” as a key enabler of this transition.
