AI Reshapes the Global Technology Landscape in 2026: TrendForce Releases Ten Major Technology Trends
As global digital transformation accelerates, artificial intelligence (AI) is becoming the core force driving change in the technology industry. According to TrendForce's latest forecast, AI will further rewrite the global technology landscape in 2026. From intensifying competition in AI chips to the proliferation of liquid cooling technology, and breakthroughs in HBM and optical communications, a new wave of technological advancement is brewing.
AI Server Shipments Continue to Rise
Driven by increased capital expenditures from major North American cloud service providers (CSPs) and the rise of global sovereign cloud projects, demand for AI data center construction remains high. TrendForce expects AI server shipments to grow by more than 20% year-over-year in 2026. NVIDIA, the leader in the AI field, will face more intense competition. AMD plans to launch the MI400 full-rack solution, similar to NVIDIA's GB/VR systems, targeting CSP customers directly in an attempt to challenge NVIDIA's market position. Meanwhile, mainstream North American CSPs are increasing their efforts in developing proprietary ASIC chips. In China, geopolitical tensions have accelerated the process of technological self-sufficiency. Companies such as ByteDance, Baidu, Alibaba, Tencent, Huawei, and Cambricon are all strengthening their investments in self-developed AI chips, and global competition in AI chips will become increasingly fierce.
Liquid Cooling Technology Moves Toward Large-Scale Deployment
With the leap in AI processor performance, the thermal design power (TDP) of a single chip is rising rapidly. From 700W for NVIDIA H100/H200, the upcoming B200/B300 will exceed 1000W. The surge in cooling demand is accelerating the adoption of liquid cooling technology, and it is expected that the penetration rate of liquid cooling in server racks will reach 47% in 2026. Microsoft has even introduced advanced chip-level microfluidic cooling technology to improve cooling efficiency. In the near to medium term, cold plate liquid cooling will continue to dominate, and CDUs (coolant distribution units) are transitioning from liquid-to-air to liquid-to-liquid types. In the long term, the market will evolve toward more refined chip-level thermal management.
HBM and Optical Communications Break Through Bandwidth Bottlenecks
As AI workloads expand from training to inference, data volume and memory bandwidth requirements increase dramatically, and system design faces the dual challenges of transmission speed and power efficiency. HBM (High Bandwidth Memory) and optical interconnect technologies have emerged to become key pillars of next-generation AI architectures. Currently, HBM significantly shortens the distance between processors and memory through 3D stacking and through-silicon via (TSV) technology, achieving higher bandwidth and efficiency. The upcoming HBM4 will introduce higher channel density and wider I/O bandwidth to support the enormous computing power demands of AI GPUs and accelerators. However, as model parameters cross the trillion-scale threshold and GPU cluster sizes expand exponentially, memory bandwidth will once again become a bottleneck for system performance. Optical communication, as one of the breakthrough directions, will play an increasingly important role in AI cluster architectures.