The market for chips designed to handle artificial intelligence (AI) tasks is on a steady rise, growing at a rate of over 20 percent each year, according to insights from Gartner, a market analysis firm.
Gartner predicts that the AI chip market will see substantial growth, reaching a value of $53.4 billion in 2023, marking a significant 20.9 percent increase from the previous year. This growth is expected to continue, with a projected 25.6 percent increase in 2024, resulting in a market value of $67.1 billion. Looking ahead to 2027, the revenue generated by AI chips is anticipated to more than double the 2023 market size, soaring to $119.4 billion.
As AI-based workloads become more commonplace in various industries and IT organizations, the integration of AI chips into systems is becoming more prevalent. This trend is particularly pronounced in the consumer electronics sector. Gartner’s analysts estimate that by the close of 2023, the value of AI-enabled application processors used in devices will surge to $1.2 billion, a substantial rise from the $558 million recorded in 2022.
Alan Priestley, an analyst at Gartner, highlighted the driving forces behind the surge in AI chip demand. He pointed out that advancements in generative AI and the expanding array of AI-powered applications across data centers, edge infrastructure, and endpoint devices are necessitating the use of high-performance graphics processing units (GPUs) and specialized semiconductor devices. This, in turn, is spurring the manufacturing and adoption of AI chips.
Priestley further noted that for numerous organizations, custom AI chips will increasingly replace the prevalent chip architecture, which is comprised of discrete GPUs. This shift is particularly expected for a wide range of AI workloads, especially those hinging on generative AI techniques.
The rise of generative AI is also contributing to the need for robust high-performance computing systems, both for development and deployment purposes. Many vendors are now offering systems built around powerful GPUs, and networking equipment providers are also experiencing significant short-term advantages. Looking further down the road, Gartner predicts that as hyperscale companies seek efficient and cost-effective solutions for deploying these applications, the adoption of custom-designed AI chips will grow.
In essence, the AI chip market’s rapid expansion is being fueled by the surge in AI-based applications across diverse sectors. This trend is pushing for the development and integration of specialized AI chips, gradually reshaping the landscape of computing architectures.
