In a very upbeat and confident stance regarding the worldwide AI cycle, Dan Ives, a technology analyst at Wedbush Securities, made it clear that the need for AI infrastructure in Asia is extremely high, to the extent that he sees the market as still being in its early stages. His recent supply-chain channel checks across Asia have revealed a huge demand-supply mismatch, especially for Nvidia's GPU chips. According to Ives, this is a clear indication of a sustained upcycle in capital expenditure and a wider "AI revolution" that is still largely overlooked by investors.

Asia’s AI Thirst: Demand Outstripping Supply

Craig Ives from Needham, in his CNBC "Fast Money" interview, mentioned that the advanced chips from Nvidia are in such high demand that the ratio of 10:1 to 12:1 relative to supply could be recorded. This means that the shortage is not only a temporary spike but also a structural change in the AI ecosystem.

"It is about 10 to 1, possibly 12 to 1, the demand-supply ratio for Nvidia chips," Ives told the Hong Kong audience.

These revelations came from his trip to Asia, where, apart from the extensive on-the-ground checks with manufacturers, cloud providers, and data centers, he had local AI startup sessions too. Ives believes that these channel checks indicate that most market forecasts are still conservative and that the real momentum in Asia is way below the ground.

Ives uses a baseball analogy to explain the situation, stating that we are only in the "second inning" of the AI growth cycle, which means that the big move is yet to come.

Beyond Nvidia: Spillover to the Entire Ecosystem

Nvidia may be the company that gets most of the media attention, but Ives claims that the ripple effects will be of great help to a number of players across the AI stack. He anticipates that the fortunes of the following companies will significantly improve:

TSMC (Taiwan Semiconductor Manufacturing Company)

AMD

Intel

Companies that manufacture semiconductor equipment and materials

Suppliers of cloud and infrastructure

Data center colocation companies

Ives points out that the demand resulting from the situation is not only for chips but also for the full infrastructure that supports them—from cooling systems, power, memory, and networking to software orchestration layers. The whole value chain is being elevated by this AI wave.

On top of that, he cautions that numerous analysts are underestimating the capital expenditure (CapEx) that hyperscalers (Microsoft, Google, Amazon, Oracle, etc.) will be willing to make in the next 12-24 months. The extent of the deployment will probably be a big surprise for the market.

Use Cases Drive the Surge

One of Ives's main points is that AI demand is not a bet on the future but rather a result of new use cases that come from various industries. He mentions that:

Corporates are rapidly implementing AI projects for the purposes of automation, predictive analytics, supply chain resilience, and smart operations.

Asian governments are investing in AI-powered health solutions, urban planning, surveillance, and defense sectors.

Startups are competing to develop domain-specific models, generative AI services, and edge solutions.

Geopolitics, Trade Friction, and Resilience

Such an assumption could be made that the differences between the U.S. and China, including export controls as well as trade policies, would slow down the AI development in Asia. However, Ives is of a contrary opinion—the demand for high-performance AI components is still there, and it has not been significantly affected by the political conflicts.

Basically, Ives interprets the continued growth as partly resulting from the need to be strategic: states and companies do not want to lose their position in the AI field. So, even if there are limitations in supplies and restrictions, local development, sourcing, and substitute solutions are getting more and more vigorous.

Just to give an example, he points out that Alibaba, Baidu, and Huawei might be trying to close the AI technology gap by increasing their efforts drastically. According to him, an "AI arms race" is happening silently in different areas.

Market Implications and Investment Outlook

Investors might derive various implications from Ives’s remarks, which are as follows:

Valuation Uplift for Core AI Players

Under such circumstances where the demand is robust and the supply is limited, it is quite possible that the valuations of Nvidia, TSMC, AMD, Intel, and the companies that are similar to them might be elevated to a level that is beyond the current expectations. As a result, analysts will probably be required to revisit the growth models.

Extended Cycle Longevity

By using the metaphor of the "second inning," Ives implies that the current boom is not just a temporary one, and hence the duration of the structural expansion could be years, and maybe even 2026 or later.

Wedbush expects the AI industry to consolidate as a result of the acquisition of strategic capabilities by the larger players. Ives states that the “AI M&A floodgates” are about to open, and companies are in a hurry to buy scale, talent, or niche IP.

The Larger Narrative: AI as a Multi-Year Megatrend

Ives is essentially conveying that AI is not just a fleeting moment in the spotlight typical of a hype cycle but rather a fundamental change in the way technology infrastructure is built, used, and monetized. He compares AI's impact on the world to the changes brought by the tech revolutions before—almost calling AI chips the new "oil and gold" of the digital economy.

He is of the opinion that, like previous cycles, which had to be played out over several innings (for example, the internet boom and mobile revolution), the AI wave will also take years rather than quarters to unfold. This perspective of his serves to remind investors that they should take a long-term view of the game instead of looking for a quick gain.

Conclusion

The bull case of Dan Ives from Wedbush is very convincing: AI demand in Asia is not only a strong one but also a deep structural trend that is hardly recognized by many market players. According to his channel checks, the demand is greatly exceeding the supply, especially for Nvidia's GPUs, which, therefore, is paving a way for a lengthy capital expenditure cycle across the whole AI ecosystem.

As a result of his forecasts, the following chapters of the AI story could be extreme valuation reratings, a significant increase in M&A activities, and semiconductor and cloud infrastructure markets having a positive trend lasting for a long time. Investors who make an early move in this cycle stand to make a great profit—however, they should also be careful with execution risk, regulatory changes, and supply chain bottlenecks.