Global AI server market to hit $72.6 billion by 2029

The Global Artificial Intelligence Server Market is expected to generate USD 72.6 Billion by the end of 2029, up from USD 17.5 Billion in 2022. During the forecast period, 2024-2029, the Global Artificial Intelligence Server Market is expected to expand at a CAGR of 25%, according to Research and Markets.

The research assesses market growth indicators, restraints, sales growth and demand risk, and other important statistics, as well as a full assessment of current and future market trends that are relevant to the market evolution.

The demand for AI servers is driven by the necessity for high computational power to train complex neural networks and execute real-time inferencing tasks. The market for artificial intelligence servers will continue to grow at a rapid pace primarily to the growing acceptance of AI-driven solutions in various industries, as well as the growing complexity and scale of AI applications.

The growth in AI server demand is driven by advancements in hardware technologies, including specialized accelerators like GPUs, TPUs, and FPGAs, optimizing performance and accelerating AI workloads. The overall shipment of Artificial Intelligence servers worldwide is witnessing significant growth, driven by the increasing integration of AI technologies across various industries.

The increasing need for processing power and hardware specifically designed for AI tasks is driving market growth. To address the demand, cloud service providers, technology companies, and businesses worldwide are investing in AI server infrastructure, which contributes to progress in accelerators and hardware designs created especially for AI.

The emergence of GPU technology has been a major driver of the AI Server Industry’s growth. Initially designed for graphics illustration, GPUs have developed into efficient accelerators for workloads related to AI and machine learning. GPUs are essential components for training complicated neural networks because of their superiority in handling matrix operations, which are essential in deep learning, and to their parallel processing capabilities.

Companies like NVIDIA, AMD, and others have been driving the constant advancement of GPU design, which has led to GPUs with increased computing capacity and unique features for AI applications. These developments allow for enhanced model complexity, quicker model training times, and better overall performance. As a result, in order to take advantage of the efficiency and speed provided by these developments, companies looking to implement AI applications are spending more and more in AI servers equipped with the most advanced GPUs.

Moreover, the need for AI servers with high-performance GPUs has increased due to the growth of AI workloads in a variety of industries, including healthcare, finance, and autonomous cars. As a result, the development of the industry is closely related to the continuous advancement of GPU technology, which is still a major factor. Research and Markets