AI Semiconductor Industry to Reach $53.4 bn Revenue in 2023, According to Gartner’s Forecast

In a recent report, research firm Gartner has projected that semiconductors designed specifically for artificial intelligence (AI) tasks will create a substantial revenue opportunity for the semiconductor industry in 2023. The forecast indicates that this sector will generate a staggering $53.4 billion in revenue, marking an impressive 20.9 percent growth from the previous year.
Generative AI chips NVIDIAThe increasing prevalence of generative AI and the widespread adoption of AI-driven applications across various sectors, including data centers, edge infrastructure, and endpoint devices, are contributing factors to the surge in demand for high-performance graphics processing units (GPUs) and optimized semiconductor devices. Alan Priestley, VP Analyst at Gartner, emphasized the pivotal role of these developments in driving the production and deployment of AI chips.

The trajectory of AI semiconductor revenue appears promising, with an anticipated 25.6 percent growth in 2024, amounting to $67.1 billion, as highlighted in Gartner’s report. This trend is projected to continue, with experts forecasting that by 2027, the revenue from AI chips will more than double the figures predicted for 2023, reaching an impressive $119.4 billion.

As industries and IT organizations continue to integrate AI-based workloads into their operations, the prevalence of AI chips is expected to expand rapidly. Gartner predicts a surge in the value of AI-enabled application processors used in consumer electronics, estimating that by the close of 2023, the value of these processors in devices will soar to $1.2 billion, a substantial increase from $558 million in the previous year.

The demand for efficient and optimized designs to accommodate cost-effective execution of AI-based workloads is poised to drive the adoption of custom-designed AI chips. Alan Priestley noted that these custom chips are likely to replace the existing standard chip architecture, particularly discrete GPUs, across a wide range of AI workloads, particularly those rooted in generative AI techniques.

The burgeoning field of generative AI is also exerting significant influence on the demand for high-performance computing systems for both development and deployment purposes. Vendors are responding by offering systems centered around high-performance GPUs and networking equipment, which are experiencing notable near-term benefits.

In the long term, as major players in the hyperscale computing sector seek cost-effective methods for deploying these AI applications, Gartner anticipates a surge in the utilization of custom-designed AI chips. This suggests a transformative shift in the industry landscape as AI technologies continue to reshape various sectors, from consumer electronics to data centers.