Akamai Surpasses $1 Billion in APAC Revenue, Entering Next Growth Phase Focused on Edge AI

Akamai Technologies announced that its annual revenue for 2025 in the Asia Pacific (APAC) region has surpassed $1 billion. This marks a turning point for the company's business in the region as it focuses on deploying next-generation AI closer to end users.

With over 20 years of experience in APAC, Akamai sees clear opportunities for growth in the region. This milestone serves as a stepping stone to its next phase of growth. The core of this phase is supporting the operationalization of AI for enterprises, with a particular focus on inference at the edge, where speed and proximity determine competitive advantage.

Leading this strategy is Sean Li, who took office as the new leader for APAC in April of this year as Senior Vice President of Sales and Managing Director. Under Li's leadership, the APAC business is evolving to meet the needs of companies looking to operationalize AI.

Sean Li stated, "APAC is currently transitioning from the experimental phase of AI to the execution phase. The real challenge today is making AI work in a production environment. There, latency, scalability, and reliability are directly tied to revenue and customer experience. By executing inference at the edge, Akamai provides enterprises with a platform to instantly and securely deploy intelligence at a scale that centralized clouds simply cannot achieve."

From AI Conception to AI Execution

Across APAC, companies are accelerating the adoption of AI, but many face common constraints. These constraints arise because traditional cloud architectures are not built with large-scale, real-time inference in mind.

Akamai aims to close this gap by running AI workloads on one of the most distributed cloud platforms in the world. By running GPU-powered computing closer to users and data, it delivers real-time AI experiences such as recommendation engines, live video intelligence, autonomous vehicles, assistive agents, and high-resolution video workflows.

This change reflects an industry-wide shift from centralized model training to distributed inference. A difference of just a few milliseconds can determine the outcome of customer engagement, operational efficiency, and risk management.

Sean Li noted, "Akamai's advantage lies not just in running applications, but in where we run them. By bringing cloud and inference closer to the point of contact with the user, we help our customers act faster, respond in real time, and deliver superior experiences at scale."

APAC Driving the Next Wave of Infrastructure Demand

APAC's diversity is becoming a catalyst for innovation rather than a barrier. In mature markets like Japan and Australia, the adoption of managed infrastructure models is increasing to improve performance and resilience. Meanwhile, in rapidly growing economies such as India, China, and across Southeast Asia, a new generation of AI-native companies built for speed and scalability is emerging. South Korea, in particular, reflects both trends, with established companies modernizing legacy systems while digital-first companies expand the possibilities of AI-driven services.

These dynamics are redefining infrastructure requirements across the region, boosting the demand for distributed platforms that can consistently address fragmented regulatory environments, diverse network conditions, and rapidly rising user expectations.

Accelerating Inference

In Akamai's next phase in APAC, the focus will be on placing GPU-accelerated inference closer to users and data across its global network, freeing AI from centralized data centers. In addition, by building security directly into the infrastructure—including the protection of AI applications and workloads—it eliminates the typical tradeoff between performance and security.

Sean Li commented, "This milestone is a testament to the trust our customers have placed in Akamai over the past 20 years. But the bigger opportunity lies ahead. As AI redefines how business is done, Akamai is building the intelligent infrastructure needed for the agent-based web. Through this, we will support enterprises in building systems that function reliably not just in theory, but in real-world operational environments."