TLDR: A new IDC research paper, commissioned by Akamai Technologies, indicates that 91% of ASEAN enterprises expect significant disruption from Generative AI (GenAI) within the next 18 months. The study highlights a rapid adoption curve, with 16% already deploying GenAI in production and 84% in initial testing phases. This shift is driving a re-evaluation of infrastructure strategies, pushing businesses towards edge services to meet the demands of AI workloads, address cost concerns, and bridge skills gaps across the Asia-Pacific region.
A recent IDC research paper, commissioned by cybersecurity and cloud computing giant Akamai Technologies, has unveiled a compelling outlook for Generative Artificial Intelligence (GenAI) across Southeast Asia. The study, released on Tuesday, September 2, 2025, reveals that a staggering 91% of ASEAN enterprises anticipate disruption from GenAI within the next 18 months. This expectation is underpinned by a rapid progression in adoption, with 16% of these organizations having already integrated GenAI applications into their production environments, while a substantial 84% are actively engaged in initial testing phases.
The research, titled “The Edge Evolution: Powering Success from Core to Edge,” extends its findings to the broader Asia-Pacific (APAC) region, indicating a critical realization among enterprises: centralized cloud architecture alone is proving insufficient to meet the escalating demands for scale, speed, and compliance driven by AI. Consequently, there is a growing imperative for businesses to rethink and enhance their infrastructure strategies, with a particular emphasis on incorporating edge services to maintain competitiveness and compliance, and to prepare for real-world AI deployments.
Public cloud infrastructure as a service (IaaS) is a cornerstone of this transformation, with 96% of GenAI adopters relying on it for their AI workloads. However, the study also points to rising edge investment, crucial for supporting remote operations and ensuring robust data control. The IDC Worldwide Edge Spending Guide — Forecast, 2025, projects that public cloud services at the edge will experience a compound annual growth rate (CAGR) of 17% through 2028, with total spending expected to reach $29 billion by that year. Furthermore, IDC predicts that by 2027, 80% of Chief Investment Officers (CIOs) will increasingly turn to edge services provided by cloud vendors to satisfy the performance and compliance requirements of AI inferencing, marking what the paper terms “The Edge Evolution.”
As GenAI transitions from experimental stages to full-scale execution, APAC enterprises are confronting the limitations of their existing legacy infrastructure. Key challenges include managing costs and addressing skills gaps, which are collectively driving the demand for more affordable and AI-ready infrastructure solutions. To navigate this evolving landscape, the study underscores the necessity for enterprises to modernize their infrastructure across both cloud and edge environments, ensuring deployments are meticulously aligned with specific workload needs.
Securing data through Zero Trust frameworks and maintaining continuous compliance are highlighted as essential measures. Additionally, ensuring interoperability is crucial to avoid vendor lock-in, enabling businesses to leverage a diverse ecosystem of partners. By embracing these strategies, organizations can significantly accelerate their AI deployment initiatives, achieving faster, smarter, and more flexible scaling capabilities.
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Regional variations in AI adoption are also noted. In Japan, for instance, while only 38% of enterprises have GenAI in production, a significant 84% believe GenAI has already disrupted or will disrupt their businesses within the next 18 months. A remarkable 98% of Japanese enterprises plan to run AI workloads on public cloud IaaS for both training and inferencing. India is also expanding its edge infrastructure to meet GenAI demand and manage costs, with 82% of enterprises in initial testing and 16% in production, focusing on building edge capabilities in tier 2 and 3 cities.
