세계의 AI 칩 시장 전망(2023-2028년) : 수요 및 공급 측면 인사이트

The release of Generative AI has rapidly ignited a global frenzy. While developing large language models (LLMs) is crucial, the real game-changer is executing AI inference tasks on edge devices after training. This will drive the creation of new applications and demands, suggesting that future AI business opportunities will be even more significant. The key to delivering this computing power lies in AI chips, making their development not just a focal point but a critical necessity for the industry. This urgency has led many companies to enter the AI chip market, focusing primarily on GPUs and self-developed ASIC accelerators, intensifying competition and opening a new chapter in the semiconductor industry.

This research report explores the evolving AI chip market, extending the discussion to the upstream and downstream sectors, including advancements in manufacturing processes, packaging technologies, and the emergence of various AI hardware devices. From the perspective of the AI chip market, demand for high-end datacenter GPUs is expected to increase by 218% in 2024, while ASIC accelerators will grow by 178%, driving the high-bandwidth memory (HBM) market to US$13.9 billion. At the edge, the introduction of AI smartphones and AI PCs will boost related chip shipments, with projected shipments of 260 million and 50 million units, respectively, in 2024, reflecting annual growth rates of 293% and 79%. The surge in AI applications is poised to drive exponential growth in AI chip shipments in 2024, heralding a promising market future and increasing industry investment.

This research report will analyze the competitive landscape across various chip segments, focusing on AI chip development trends through perspectives such as market share and development roadmaps. The report will examine not only major chipmakers like Nvidia, AMD, Intel, MediaTek, and Qualcomm but also the chip development strategies of companies like Apple, Amazon, Google, and Microsoft, highlighting the diverse advancements in AI chips and exploring emerging trends in the chip market driven by AI applications.

As AI applications expand and new AI chips are introduced, the demand for improved AI model performance - particularly regarding response speed, accuracy, and reliability - continues to grow. Enhancing AI chip performance across all dimensions will hinge on advancements in chip manufacturing technology. The report will conclude by assessing the impact of AI development on the semiconductor market, focusing on IC manufacturing. This includes examining advanced process technologies that are becoming increasingly important due to AI demands, as well as the planning and capacity layout of advanced processes and packaging by foundries.

Before 2024, the development of generative AI focused on AI model training. However, as large language models begin to enter edge devices, AI's implementation will drive more business opportunities, including new applications, new chips, and new products. This will not only expand existing markets proportionally but also change existing technology and capacity demands under new requirements, altering the competitive landscape of the chip market and leading to unprecedented changes in the semiconductor ecosystem. This is the core focus of the research report.

Table of Contents

Chapter 1 - Research Background and Scope

• 1.1. Factors and Dynamics Driving AI Growth
• 1.2. Demand for Chips in Generative AI Applications
• 1.3. Research Definition and Scope

Chapter 2 - Cloud AI Accelerator Shipment Forecast

• 2.1. Cloud AI Accelerators - GPU, 2023-2028
• 2.2. Could AI accelerators - ASIC, 2023-2028
• 2.3. HBM Market Analysis from 2023 to 2028
• 2.4. Summary

Chapter 3 - Consumer Edge AI Chip Shipment Forecasts - AI Smartphones and AI PCs

• 3.1. Demand for Edge AI Chips: AI Smartphone, 2023-2028
• 3.2. Edge AI Chip Demand for AI PCs, 2023-2028
• 3.3. Summary

Chapter 4 - Forecast of High-End AI Chip Supply - Wafer Foundries

• 4.1. Technology Roadmap for High-End AI Chip Manufacturing
• 4.2. Analysis of Advanced Wafer Fabricating Capacity, 2023-2028
• 4.3. Summary

Chapter 5 - Conclusion