AI Terminal Boom Triggers Edge Computing Power Restructuring: Why the Next Super Cycle for Chip Investment Lies in 'AI of Things'

Entering Q3 2026, the global semiconductor industry is undergoing a profound structural transformation. If the main thread of semiconductor investment over the past three years was a "cloud computing power arms race," then entering the second half of 2026, the industry's balance is quietly tilting—the scaled explosion of terminal AI devices is pulling the narrative logic of chip investment back from "centralized data centers" to "edge nodes of the AI of Things." From the comprehensive popularization of AI phones equipped with high-computing-power NPUs (Neural Processing Units), to the AI PC replacement wave sweeping the global consumer market, to the thirsty demand for low-latency edge computing power from smart manufacturing and autonomous driving, the shipment volume and value of edge AI chips are climbing at a speed exceeding market expectations. For investors, understanding the underlying logic of this shift means grasping the core anchor of semiconductor investment for the next decade. Why invest in chips? The answer is evolving from "centralized computing power" to "ubiquitous computing power."

1. Market Turning Point Emerges: From Cloud Solo Dance to Edge Explosion, Computing Power Restructuring Opens a New Era

For a long time, the growth driver of the semiconductor market relied heavily on the capital expenditure of cloud data centers. However, the 2026 market data shows a completely different picture. As large model technology gradually matures, the demand for computing power in the model inference phase is shifting massively to terminals. The high cost of cloud inference, the latency bottleneck of network transmission, and increasingly strict data privacy compliance requirements together constitute the three major driving forces for the sinking of computing power. Against this backdrop, edge AI chips have ushered in a true demand turning point.

Looking at the performance of terminal devices, the penetration rate of global AI smartphones in 2026 has broken the critical point, becoming the main engine driving the growth of global semiconductor shipments. Not only mobile phones, but the personal computer market has also welcomed a long-overdue replacement cycle amid the substantive implementation of the AI PC concept. The core feature of these devices is the built-in independent NPU units optimized for AI large model inference, enabling local large language model dialogue, image generation, and system-level intelligent scheduling without network connectivity. This physical migration from "cloud computing power" to "terminal computing power" directly detonated the massive demand for edge-side chips, making the shipment scale of edge AI chips surpass some cloud inference chips for the first time in 2026. This is not just a change in statistical figures, but a signal of the reconstruction of value distribution across the entire semiconductor industry chain.

2. Technology Barriers and Supply Chain Restructuring: Why Edge AI Chips Have Become Core Investment Assets

To understand "why invest in chips," one must deeply analyze the technological barriers and supply chain restructuring logic of the chip industry. Edge AI chips are not simply scaled-down cloud chips; they face extremely stringent physical constraints on their technological path: power, area, and cost, commonly known in the industry as PPA metrics. In battery-powered micro-devices like mobile phones and IoT, edge AI chips must not only provide TOPS computing power sufficient to support large model inference with tens of billions of parameters, but also keep power consumption at the milliwatt level. This extreme requirement directly drives a comprehensive upgrade in semiconductor manufacturing and design technologies.

1. Deep Coupling of Process Nodes and Advanced Packaging

To cram more transistors into a tiny chip area and control leakage rates, edge AI chips are fully embracing advanced processes. In 2026, the 3-nanometer process has become standard for high-end AI phones and AI PC chips, and the mass production schedule for the 2-nanometer process has also been significantly advanced due to the forced push from terminal demand. More critically, edge AI chips are becoming the largest application market for advanced packaging technologies. To break the shackles of memory bandwidth on computing power, 2.5D and 3D packaging technologies based on Chiplet architecture are widely used in terminal SoCs. Heterogeneous packaging of compute chiplets, NPU chiplets, and high-bandwidth memory chiplets not only shortens data transmission paths and reduces power consumption, but also significantly lowers the manufacturing cost and yield risk of a single chip. This technological evolution gives foundry manufacturers with advanced packaging capacity extremely high bargaining power, making them one of the links with the strongest investment certainty in the chip industry chain.

2. Architectural Innovation: From General-Purpose Computing to Domain-Specific Architecture (DSA)

The explosion of edge computing power has also spawned a paradigm shift in chip design architecture. Traditional CPU and GPU architectures have low energy efficiency when processing AI tensor calculations, failing to meet the stringent requirements of terminal devices. Therefore, major chip design companies are turning to Domain-Specific Architectures. Customized NPUs, Tensor Processing Units (TPUs), and integrated neural network accelerators have become the core IP of edge chips. This architectural innovation not only improves computing power utilization but also builds a deep moat at the software ecosystem level. Chip design companies capable of providing full-stack solutions from underlying hardware and compilers to upper-level AI frameworks are rapidly seizing market share, forming a Matthew effect where the strong get stronger. For investors, finding chip design companies with deep accumulation in DSA architecture design and software-hardware co-optimization is tantamount to finding the ten-bagger stocks of the next semiconductor cycle.

3. Changes in Supply-Demand Landscape: Profit Redistribution in the Semiconductor Industry Chain

The explosive growth of edge AI chips is profoundly changing the supply-demand landscape and profit distribution mechanisms of the global semiconductor industry chain. In the past, large cloud chips were characterized by "few varieties, large batches, and high unit prices," with a few giants monopolizing the vast majority of computing power purchasing power. Edge AI chips, on the other hand, exhibit the characteristics of "multiple varieties, massive shipments, and a high degree of customization." This transformation has had a profound impact on every link of the industry chain.

1. Wafer Foundry: "Dual-track" Prosperity of Mature and Advanced Nodes

The diversification of edge devices means an explosive growth in chip types. In addition to core SoCs relying on advanced processes, peripheral power management chips, RF chips, sensor chips, and interface chips heavily rely on mature processes like 28nm to 40nm. In the second half of 2026, wafer foundry capacity utilization showed a significant structural divergence: advanced processes are in short supply due to the AI terminal replacement wave, while mature processes have also ended a two-year price war due to the popularization of edge IoT devices, with quotes starting to stabilize and rebound. This "dual-track" prosperity has restored the overall profitability of the wafer foundry industry, bringing fundamental improvements to the financials of related listed companies.

2. Storage and Materials: New Storage Technologies Usher in Spring

Edge AI's demand for storage is equally huge, but unlike cloud HBM (High Bandwidth Memory), edge devices, limited by physical space and power consumption, cannot stack DRAM on a large scale. This has triggered a simultaneous increase in volume and price for LPDDR (Low Power Double Data Rate Memory), while also providing fertile ground for the commercialization of new storage technologies like MRAM and ReRAM. In addition, edge chips have raised higher requirements for the number of layers and circuit density of packaging substrates, leading to a renewed rebound in the prosperity of IC substrates and ABF materials. From silicon wafers to specialty gases, the semiconductor materials end is experiencing a cyclical recovery on the demand side brought by edge AI after previous destocking.

4. Investment Logic Reconstruction: Why Now is the Best Time to Position in Edge Computing Chips

Returning to the core proposition of "why invest in chips," positioning in edge computing chips at this current juncture possesses three irreplaceable investment logics.

1. Closed-Loop Business Models and Realization of Profitability

Unlike cloud AI chips, which are still in massive capital expenditure and difficult to realize a return on computing power investment in the short term, the business model of edge AI chips has formed a perfect closed loop. Consumers are willing to pay a premium for terminal devices equipped with high-computing-power AI chips in exchange for smarter interactive experiences, longer battery life, and safer privacy protection. This direct monetization path facing the C-end market allows chip design companies to quickly translate technological advantages into revenue and profit on financial statements. The Q2 2026 earnings season showed that the gross margins of several tech companies focusing on AI phone and AI PC chips hit record highs, and the realization of profitability provided solid fundamental support for stock prices.

2. The Golden Window for Domestic Substitution

Against the backdrop of global semiconductor supply chain restructuring, edge AI chips provide a historic opportunity for domestic substitution. Compared to the stringent technological blockades and ecosystem barriers faced by high-end cloud GPUs, edge-side chips are diverse in variety and have fragmented application scenarios, providing broad space for localized chip enterprises to compete in different segments. Especially in vertical fields such as smart security, industrial control, in-vehicle infotainment systems, and smart homes, domestic chip design companies are accelerating the completion of domestic substitution by leveraging the service advantage of being close to local market demands and iterating quickly. At the policy level, the Phase III National Semiconductor Fund and industrial support funds from various levels of government are continuously tilting towards edge computing and terminal-side AI fields. Investing in domestic edge computing chips is not only complying with industrial development trends, but also a core path to share the dividends of national technological self-reliance.

3. Excess Returns from Long-Term Compound Growth in Demand

The essence of semiconductor investment is investing in the future of technology. The underlying driving force of edge AI chips is the long-term trend of human society's evolution towards intelligence. From feature phones to smartphones, from traditional PCs to AI PCs, every revolution in interaction methods has been accompanied by a tenfold leap in semiconductor value. Over the next decade, with the commercialization of cutting-edge technologies such as embodied AI, terminal-side large models, and spatial computing, edge computing power will permeate every corner of human society like electricity. Assets with such strong anti-cyclical nature and long-term compound growth rates rightfully deserve a core strategic position in investment portfolios.

Conclusion: Grasping the Heartbeat of Chips in the AI of Things Era

Standing at the crossroads of the second half of 2026, the global semiconductor industry is undergoing a profound transformation from cloud computing power monopoly to ubiquitous edge computing power. The explosion of edge AI chips is not only an inevitable result of technological evolution, but also a reshaping of the industry's supply-demand landscape and profit distribution. From capacity competition in advanced processes, to ecosystem battles over Chiplet architectures, to the perfect closed-loop of terminal business models, edge computing chips are showing unprecedented investment appeal. For global investors, deeply understanding the new connotation of "why invest in chips" in the AI of Things era and accurately positioning in the core assets of the edge computing industry chain will be the key to piercing through the fog of cycles and obtaining excess returns in the next semiconductor super cycle. In this era where computing power is productivity, investing in edge chips means investing in the future of human intelligence.