Modernizing infrastructure with cloud and edge integration, along with Zero Trust security frameworks, is essential for accelerating AI deployment and ensuring data security and compliance.

APAC enterprises face infrastructure challenges such as managing multicloud complexity, regulatory compliance, rising cloud costs, and latency issues, which hinder AI deployment.

India is expanding edge infrastructure in tier 2 and 3 cities to address AI demand, driven by cost concerns and skills gaps, with 82% testing AI and 16% deploying it in production.

China leads in Generative AI deployment, with 37% in production and 61% testing, primarily relying on public cloud infrastructure.

ASEAN countries are adopting an edge-first strategy, with 91% expecting AI disruption within 18 months and 84% actively testing or deploying AI applications, supported by high public cloud IaaS adoption (96%).

The shift toward distributed, edge-first infrastructure is crucial for addressing performance, security, and cost challenges associated with AI deployment.

Traditional centralized cloud models are increasingly insufficient for AI demands, prompting organizations to adopt edge-first architectures to enhance performance, security, and compliance.

Edge spending in public cloud services is projected to grow at a CAGR of 17% through 2028, reaching US$29 billion, driven by the need for scalable, high-performance infrastructure.

The IDC report provides strategic insights into building AI-ready, cloud-connected infrastructure tailored for the APAC region.

By 2027, 80% of CIOs in Asia-Pacific are expected to rely on edge services from cloud providers to meet AI performance and compliance demands, marking a significant shift called 'The Edge Evolution'.

Japan is upgrading its AI infrastructure, with 98% of organizations planning to run AI workloads on public cloud IaaS, despite only 38% currently deploying AI in production.