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AI Semiconductor Revenue will Reach $119.4B

The Chief Information Officer (CIO) and/or the Chief Technology Officer (CTO) will guide Generative AI initiatives within the large enterprise C-Suite. They may already have the technical expertise and experience to understand the capabilities and limitations of Gen AI.

They also have the authority and budget to make the necessary investments in infrastructure and talent to support Gen AI initiatives. Enterprise AI infrastructure is proven to be expensive to build, operate and maintain. That's why public cloud service provider solutions are often used for new AI use cases.

AI Semiconductor Market Development

Semiconductors designed to execute Artificial Intelligence (AI) workloads will represent a $53.4 billion revenue opportunity for the global semiconductor industry in 2023, an increase of 20.9 percent from 2022, according to the latest worldwide market study by Gartner.

"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 (GPUs) and optimized semiconductor devices," said Alan Priestley, VP analyst at Gartner.

This huge infrastructure requirement is driving the demand, production and deployment of AI-related chips.

AI semiconductor revenue will continue to experience double-digit growth through the forecast period, increasing 25.6 percent in 2024 to $67.1 billion.

By 2027, AI chips revenue is expected to be more than double the size of the market in 2023, reaching $119.4 billion.

Many more industries and IT organizations will deploy systems that include AI chips as the use of AI-based workloads in the enterprise matures.

In the consumer electronics market, Gartner analysts estimate that by the end of 2023, the value of AI-enabled application processors used in devices will amount to $1.2 billion -- that's up from $558 million in 2022.

The need for efficient and optimized designs to support cost effective execution of AI-based workloads will result in an increase in deployments of custom-designed AI chips.

"For many organizations, large scale deployments of custom AI chips will replace the current predominant chip architecture – discrete GPUs – for a wide range of AI-based workloads, especially those based on Generative AI techniques," said Priestley.

Generative AI is also driving demand for High-Performance Computing (HPC) systems for development and deployment, with many vendors offering high performance GPU-based systems and networking equipment seeing significant near-term benefits.

In the long term, as the cloud computing hyperscalers look for efficient and cost-effective ways to deploy these applications, Gartner expects an increase in their use of custom-designed AI chips.

Outlook for Artificial Intelligence Applications Growth

That said, I believe a CEO typically sets the overall strategic direction for digital transformation initiatives, and they will guide expensive Gen AI projects to ensure they're aligned with top-priority digital growth goals. There is a significant upside opportunity for innovation.

The CFO is responsible for managing the company's finances, and they need to be involved in Gen AI initiatives to ensure that they are cost-effective and that they generate a big return on investment.

The CMO is responsible for marketing the solution, and they also need to be involved in Gen AI initiatives to ensure that they are applied to drive value creation for partners and customers.

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