Artificial Intelligence (AI) is poised to drive significant growth, creating an ecosystem for companies and investors that is brimming with innovation and financial gains, according to an ET report that quoted a UBS report. This technological shift is expected to open doors for companies and investors, positioning AI at the forefront of global progress.
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Projected Revenues
By 2027, the AI sector is projected to generate massive revenues, with AI data centers expected to contribute USD 331 billion, while cloud AI services will generate USD 185 billion. Large language models (LLMs) are anticipated to bring in USD 255 billion, and applications, the most lucrative layer, are set to drive USD 395 billion in revenue, the report stated.
"For investors, the key focus will be on the ratio of monetisation potential between the AI application layer and the costs of the enabling and intelligence layers, a crucial metric for determining returns," the report said.
A significant rise in capital expenditures (capex) for AI-specific infrastructure is expected, with AI data centers anticipated to account for 75 percent of total data center capex by 2027, up from 30 percent in 2023.
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GPUs and hyperscalers
GPUs, which comprise over 70 percent of AI server costs, are positioned to capture the largest share of AI's value creation. Other components, such as memory and interconnect technologies, will also play vital roles, making up 15 percent and 9 percent of server costs, respectively.
The report indicates that early adopters, particularly hyperscalers, are likely to experience significant revenue and margin growth as AI becomes integral to their operations. This evolution could lead to the rise of a small oligopoly of vertically integrated "AI foundries," dominating the value chain from chip manufacturing to software development.
In software development, AI-driven tools are expected to enhance code creation efficiency, accelerating technological innovation across various industries. Data is identified as a key differentiator; companies with extensive and diverse datasets will have a competitive advantage in optimising AI models.
Proprietary Models in AI
While open-source models are on the rise, proprietary systems continue to outperform them, driven by their superior accuracy and scalability. The high capital expenditures required for foundational AI models create barriers for open-source competition, further solidifying the dominance of tech giants.
"As of August 2024, closed-source models have remained the top performers due to their superior accuracy and scalability," the report stated.
Looking ahead, the report suggests that the merging of application and intelligence layers could accelerate the path toward artificial general intelligence (AGI), with current models achieving impressive results in domain-specific tasks.
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"Current developments show that single language models are achieving above-average scores on domain-specific tasks, indicating the potential for AGI to reshape industries in the years to come," the report said, citing UBS.
