The AI hardware market is expected to grow rapidly. Global AI chip sales are expected to exceed 100 trillion won, and AI PCs are expected to account for 100% of the enterprise market.

According to Gartner, global AI semiconductor sales are expected to reach $71 billion (approximately KRW 100 trillion), a 33% increase from last year, it announced on the 30th.

AI semiconductor sales are expected to continue to grow at a double-digit rate each year during the forecast period, with the highest growth rate expected in 2024 during the period. Sales are expected to reach $91.9 billion in 2025.

Gartner forecasts that AI chip sales in the computer electronics sector this year will total $33.4 billion, accounting for 47% of total AI semiconductor sales and recording the highest share in the electronic equipment sector. It also forecasts that AI chip sales in the automotive electronics sector this year will reach $7.1 billion and in the consumer electronics sector $1.8 billion.

With CPUs for AI PCs being launched in earnest this year, led by Intel and AMD, laptop manufacturers such as Samsung Electronics, LG Electronics, Lenovo, and HP are producing and releasing AI PCs on a large scale. Gartner predicts that AI PC shipments will reach 22% of total PC shipments this year and that AI PCs will account for 100% of corporate PC purchases by the end of 2026.

It is expected that AI PCs equipped with NPUs will be able to operate for longer periods of time, and AI functions and tasks running in the background will create new opportunities in work and daily life.

Alan Priestley, VP analyst at Gartner, said, “Generative AI today is spurring demand for high-performance AI chips for data centers,” adding, “The value of AI accelerators, which offload data processing from microprocessors in servers, will reach $21 billion this year, and grow to $33 billion in two years.”

As AI-related industries grow exponentially, fierce competition between semiconductor suppliers and tech companies is also expected.

While much attention is focused on the use of high-performance graphics processing units (GPUs) in new AI workloads, major hyperscalers Amazon Web Services (AWS), Google, Meta, and Microsoft are all investing in developing their own AI-optimized chips.

According to Gartner, chip development is expensive, but custom-designed chips can improve operational efficiency and reduce the cost of providing AI-based services to users. In addition, Gartner said users can also reduce the cost of accessing new AI-based applications.

“The current trend is likely to continue as the market shifts its focus from AI development to deployment,” said Priestley VP Analyst.