According to the report, revenue growth will quicken, increasing by more than a quarter to $67.2 billion next year and more than doubling to over $120 billion by 2027. Gartner experts predict that by the end of this year, the market value of AI-enabled application processors used in devices would increase by more than doubling yearly to $1.2 billion. As the use of AI-based workloads is anticipated to expand further, this will be driven by the anticipated rush of more sectors and IT organizations adopting systems that use AI into their operations, it said.
According to Gartner, the deployment of specially designed AI chips will rise as a result of the requirement for effective and optimized designs to support the economical execution of workloads based on artificial intelligence. While businesses have long used AI in their operations, it has recently gained popularity thanks to generative AI, which was made popular by Microsoft-backed Open AI’s ChatGPT. ChatGPT caused a sensation because it can generate a variety of data types, including audio, code, images, text, simulations, 3D objects, and videos. Following a spike in interest in 2019, investors invested more than $4.2 billion into generative AI start-ups through 215 deals in 2021 and 2022, according to latest CB Insights data.
Manufacturers are already taking advantage of the technology’s possibilities. One of the top chip makers in the world, Nvidia, had its share price increase by around 174% over the past year as it capitalized on the generative AI boom with potent new semiconductor solutions. This helped it join the exclusive club of companies with trillion-dollar market caps. While all is going on, SoftBank Group’s British semiconductor division Arm is creating a stir with its anticipated massive initial public offering in September, which might be the third-largest listing in the history of technology and the biggest IPO in the US this year. In order to better serve its clients that manufacture chips for data centers, which are increasingly integrating AI capabilities, the company wants to concentrate less on the smartphone industry.
In its most recent Hype Cycle For New Technologies report, Gartner this week also labeled generative AI as overhyped and placed it at the pinnacle of “inflated expectations” for new technology in 2023, just behind AI-augmented software engineering and cloud-native technology. Before plateauing—a condition in which little to no progress is being achieved after a time of development—generative AI, in particular, is anticipated to give these benefits within two to five years, it claimed.
In this week’s report, Alan Priestley, a vice-president analyst at Gartner, stated that “the developments in generative AI and the increasing use of a wide range AI-based applications in data centers, edge infrastructure, and endpoint devices require the deployment of high performance graphics processing units and optimized semiconductor devices.” This is influencing the development and use of AI chips.
Due to the large near-term benefits they anticipate, numerous semiconductor makers are now providing high-performance GPU-based systems and networking equipment. Gartner anticipates that the use of specially built AI processors will rise over time as hyper-scalers seek more efficient and affordable ways to deploy these applications, according to the study.
