91 percent of ASEAN enterprises expect generative artificial intelligence (GenAI) disruption within 18 months, with 16 percent having introduced GenAI applications into the production environment and 84 percent in the initial testing phase, a study showed Tuesday.

According a new IDC research paper commissioned by Akamai Technologies, the cybersecurity and cloud computing company that powers and protects business online, 96 percent are adopting public cloud infrastructure as a service (IaaS) for artificial intelligence (AI) workloads, while edge investment is rising to support remote operations and data control.

Overall, the research showed Asia-Pacific (APAC) enterprises are realizing that centralized cloud architecture alone is unable to meet the increased demands of scale, speed, and compliance.

It is crucial that businesses rethink and enhance infrastructure strategies to include edge services to stay competitive and compliant, and be ready for real-world AI deployment, it added.

According to the IDC Worldwide Edge Spending Guide — Forecast, 2025, public cloud services at the edge will grow at a compound annual growth rate (CAGR) of 17 percent through 2028, with the total spending projected to reach $29 billion by 2028.

In addition, in the latest research paper, IDC predicts that by 2027, 80 percent of Chief Investment Officers (CIOs) will turn to edge services from cloud providers to meet the performance and compliance demands of AI inferencing.

This shift marks what is emerging in the paper as “The Edge Evolution.”

The research paper further outlines how public cloud–connected systems combine the agility and scale of public cloud with the proximity and performance of edge computing, delivering the flexibility businesses need to thrive in an AI-powered future.

As generative AI moves from experimentation to execution, enterprises across APAC are confronting the limits of legacy infrastructure.

Today, 31 percent of organizations surveyed in the region have already deployed GenAI applications into production.

Meanwhile, 64 percent of organizations are in the testing or pilot phase, trialing GenAI across both customer-facing and internal use cases.

However, this rapid momentum is exposing serious gaps in existing cloud architectures:

According to the study, 49 percent of enterprises struggle to manage multicloud environments due to inconsistent tools, fragmented data management, and challenges in maintaining up-to-date systems across platforms.

50 percent of the top 1,000 organizations in APAC will struggle with divergent regulatory changes and rapidly evolving compliance standards, and this will challenge their ability to adapt to market conditions and drive AI innovation.

Meanwhile, 24 percent of organizations identify unpredictable rising cloud costs as a key challenge in their GenAI strategies.

Traditional hub-and-spoke cloud models introduce latency that undercuts the performance of real-time AI applications, making them unsuitable for production-scale GenAI workloads, said the research.

“AI is only as powerful as the infrastructure it runs on,

“This IDC research paper reveals how APAC businesses are adopting more distributed, edge-first infrastructure to meet the performance, security, and cost needs of modern AI workloads,” said Parimal Pandya, Senior Vice President, Sales, and Managing Director, Asia-Pacific at Akamai Technologies.

Daphne Chung, Research Director at IDC APAC, added that GenAI is shifting from experimentation to enterprise-wide deployment.

“As a result, organizations are rethinking how and where their infrastructure operates,

“Edge strategies are no longer theoretical — they’re being actively implemented to meet real-world demands for intelligence, compliance, and scale,” she added.

According to the study, China scales GenAI with edge and public cloud dominance.

37 percent of enterprises have GenAI in production and 61 percent are testing, while 96 percent rely on public cloud IaaS.

Edge IT investment is accelerating to support remote operations, disconnected environments, and industry-specific use cases.

The study also showed Japan is accelerating AI infrastructure despite digital maturity gap.

While only 38 percent of Japanese enterprises have GenAI in production, 84 percent believe GenAI has already disrupted or will disrupt their businesses in the next 18 months, and 98 percent plan to run AI workloads on public cloud IaaS for training and inferencing workloads.

Edge use cases like AI, internet of things (IoT), and operational support for cloud disconnection are driving infrastructure upgrades.

The research also highlighted that India expands edge infrastructure to meet GenAI demand and manage costs.

With 82 percent of enterprises conducting initial testing of GenAI and 16 percent leveraging GenAI in production, India is building out edge capabilities in tier 2 and 3 cities.

91 percent of GenAI adopters rely on public cloud IaaS, but cost concerns and skills gaps are pushing demand for affordable, AI-ready infrastructure.

To stay ahead, the study highlighted that enterprises must modernize infrastructure across cloud and edge, aligning deployments with specific workload needs.

It noted securing data through Zero Trust frameworks and continuous compliance is essential, as is ensuring interoperability to avoid vendor lock-in.

By tapping into ecosystem partners, businesses can accelerate AI deployment and scale faster, smarter, and with greater flexibility, it added. 

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