In an analyst note on Tuesday, the financial services arm of Swiss banking giant UBS raised its guidance for long-term AI end-demand forecast from 20% compound annual growth rate (CAGR) from 2020 to 2025 to 61% CAGR between 2022 to 2027.
“We don’t think AI is a bubble given clear use cases and solid long-term visibility, but recommend investors consider companies with clear monetization trends,” wrote Solita Marcelli, the global wealth management chief investment officer Americas of UBS Financial Services.
The report is an acknowledgment of the huge financial potential of the emerging sector surrounding generative AI and related technology.
So far, the total global tech market capitalization has grown by $6 trillion year-over-year, of which AI-related enterprises contributed $2 trillion, according to the UBS note.
UBS predicts that global AI demand will grow from $28 billion in 2022 to $300 billion in 2027. The note identified two main components of the AI sector: an infrastructure layer as well as an application and data layer.
Today, it said, most of the spending is found in the infrastructure component, with concentration on building and training huge data sets. But in the medium and long term, the application and data will be the larger segment with the increasing use of innovative deployments of gen AI technologies like copilots, imagery and big data analytics.
“We see significant opportunities over the next few quarters, such as in the integration of AI “copilots” in office productivity software, rising demand for big data analytics, and AI integration in image/video and other enterprise applications,” said Marcelli.
UBS analysts laid out how they expect the applications and data segment to bring $170 billion in revenues, compared to $130 billion for the infrastructure layer, in 2027. Those are CAGRs of 139% and 38%, respectively.
In short, UBS thinks investors should be paying extra attention to the companies in the AI software ecosystem, as today’s infrastructure-adjacent semiconductor and hardware businesses, such as Nvidia, continue to have high valuations.
“Given the rich valuations, we are waiting for a pullback to turn positive on the segment again,” the note read. “Meanwhile, we think the risk-reward is more attractive for software stocks, which, in our view, are well positioned to ride the broadening AI demand trends.”
Some companies have set out to capture both verticals. Nvidia recently announced the wide-accessibility of its cloud-based AI supercomputing software service, DGX Cloud, which will be powered by thousands of virtual Nvidia GPUs.
“With DGX Cloud, now any organization can remotely access their own AI supercomputer for training large complex LLM and other generative AI models from the convenience of their browser, without having to operate a supercomputing data center,” Tony Paikeday, senior director for DGX Platforms at Nvidia, told VentureBeat.
Investment into AI-based companies continues to be strong. Last week, German enterprise software giant SAP announced it directly invested in three AI startups: Cohere, Anthropic (maker of the Claude 2 LLM service) and Aleph Alpha.
Previously, SAP-backed Sapphire Ventures announced a $1 billion commitment to gen AI startups. All of this activity follows Microsoft’s $10 billion bet on OpenAI in January 2023.
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In an analyst note on Tuesday, the financial services arm of Swiss banking giant UBS raised its guidance for long-term AI end-demand forecast from 20% compound annual growth rate (CAGR) from 2020 to 2025 to 61% CAGR between 2022 to 2027.
“We don’t think AI is a bubble given clear use cases and solid long-term visibility, but recommend investors consider companies with clear monetization trends,” wrote Solita Marcelli, the global wealth management chief investment officer Americas of UBS Financial Services.
The report is an acknowledgment of the huge financial potential of the emerging sector surrounding generative AI and related technology.
So far, the total global tech market capitalization has grown by $6 trillion year-over-year, of which AI-related enterprises contributed $2 trillion, according to the UBS note.
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Current focus on infrastructure; apps and data in long term
UBS predicts that global AI demand will grow from $28 billion in 2022 to $300 billion in 2027. The note identified two main components of the AI sector: an infrastructure layer as well as an application and data layer.
Today, it said, most of the spending is found in the infrastructure component, with concentration on building and training huge data sets. But in the medium and long term, the application and data will be the larger segment with the increasing use of innovative deployments of gen AI technologies like copilots, imagery and big data analytics.
“We see significant opportunities over the next few quarters, such as in the integration of AI “copilots” in office productivity software, rising demand for big data analytics, and AI integration in image/video and other enterprise applications,” said Marcelli.
Applications vs. infrastructure
UBS analysts laid out how they expect the applications and data segment to bring $170 billion in revenues, compared to $130 billion for the infrastructure layer, in 2027. Those are CAGRs of 139% and 38%, respectively.
In short, UBS thinks investors should be paying extra attention to the companies in the AI software ecosystem, as today’s infrastructure-adjacent semiconductor and hardware businesses, such as Nvidia, continue to have high valuations.
“Given the rich valuations, we are waiting for a pullback to turn positive on the segment again,” the note read. “Meanwhile, we think the risk-reward is more attractive for software stocks, which, in our view, are well positioned to ride the broadening AI demand trends.”
Some companies have set out to capture both verticals. Nvidia recently announced the wide-accessibility of its cloud-based AI supercomputing software service, DGX Cloud, which will be powered by thousands of virtual Nvidia GPUs.
“With DGX Cloud, now any organization can remotely access their own AI supercomputer for training large complex LLM and other generative AI models from the convenience of their browser, without having to operate a supercomputing data center,” Tony Paikeday, senior director for DGX Platforms at Nvidia, told VentureBeat.
The money keeps flowing into AI
Investment into AI-based companies continues to be strong. Last week, German enterprise software giant SAP announced it directly invested in three AI startups: Cohere, Anthropic (maker of the Claude 2 LLM service) and Aleph Alpha.
Previously, SAP-backed Sapphire Ventures announced a $1 billion commitment to gen AI startups. All of this activity follows Microsoft’s $10 billion bet on OpenAI in January 2023.
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Author: Bryson Masse
Source: Venturebeat
