MIC: 53% of laptops to run local AI inference by 2026
AI technology and applications continue to evolve rapidly, with recent developments shifting from generative AI to AI agents. The widespread adoption of generative AI over the past several years has laid the foundation for long -term AI growth. This has driven the technology's evolution from content generation to autonomous task execution, making it a new core driver of enterprise digital transformation.
Long-term AI capabilities are expected to deepen progressively, according to industry projections. OpenAI has divided AI development into five stages: conversational interaction, complex reasoning, autonomous action, innovative collaboration and organizational autonomous operation. The world is now entering a new phase of AI agents (Level 3) that autonomously execute tasks. In the coming years, AI will advance to the Innovations and Organizations stages, evolving toward assisting in invention, executing entire organizational workflows and deploying across various industrial applications.
The AI agent industrial ecosystem has now formed a four-layer architecture comprising infrastructure, model development, platforms and applications, attracting technology giants and startups to collaborate. As each layer of the ecosystem continues to mature, industry chain integration effects will gradually emerge. Conditions for AI agent commercial deployment have recently become increasingly mature, and AI applications across all industries will progressively materialize.
With the rapid advancement of AI technology and applications, varying degrees of computing power are required for model training, deployment, optimization and application inference. Countries have also begun constructing autonomous computing data centers based on sovereign AI policy considerations, significantly increasing global demand for AI computing power. With the rapid proliferation of AI agent applications, cloud service providers' computing capacity has become insufficient to meet demand. To address this new wave of computing requirements, the global server market has seen growth not only in AI servers but also in general-purpose servers.
Looking at the growth drivers for server market procurement demand in 2026, major cloud service providers continue to build large data centers. AI model developers, sovereign AI operators and computing power service providers known as NeoClouds are also investing in data center construction. These facilities are designed for model computation and application deployment, according to MIC analysis.
The computing power demand driven by AI applications has gradually extended from large cloud data centers to edge and terminal devices. In response to model inference requirements, the overall deployment architecture has shifted from centralized data centers to distributed, multi-tiered configurations. This trend has not only expanded deployment scenarios for AI computing but has also significantly elevated the role of AI terminal devices in local inference and user interaction.
Considering the differences in deployment scenarios, future market growth for AI computing power will come from domain-specific computing engines and open software ecosystems. Different application scenarios will drive different system configurations: cloud data center computing will prioritize high performance and high bandwidth, while edge computing devices such as industrial computers will emphasize real-time capability and reliability. Client terminal devices such as AI PCs will prioritize low power consumption, privacy and user-friendly interfaces.
The Market Intelligence and Consulting Institute, a government-backed think tank, estimates that AI PCs will see significant growth in their share of the overall PC market. By 2026, an estimated 53% of laptops will be capable of executing AI inference tasks locally, entering an accelerated adoption phase. The market for PCs equipped with neural processing units will also continue to expand, and new AI PCs jointly launched by Nvidia and Taiwan PC manufacturers will further stimulate growth. ◼