Digital Intelligence Seeks Reality Shares Like Nvidia to Make Money

Nvidia is the company of the moment: the leader in AI hardware and software; number one in gaming GPU technology; their developments are the most in demand given the development of artificial intelligence; they are a pioneer in putting into practice the requirements of the industry… But the market demands more. And much more. Although the company founded by Jensen Huang has issued its first-ever $30 billion invoice, exceeding all expectations, the market has responded by sending its shares falling, as investors do not want the growth rate to slow down. They are looking for the perfect formula for the AI ​​business to achieve what can be achieved in any other activity: money. And not only at Nvidia, but at all the companies that are betting decisively on this technology.

If, despite its best revenue ever and record profits, investors are not betting against the Californian tech company, it is because the development of artificial intelligence is already outpacing the development of pure business. At stake is the next generation of Blackwell chips, which are expected to begin mass shipments in early 2025; and sales margins, whose growth is getting lower due to the large volume of sales it generates due to unstoppable demand for its services.

Advances in artificial intelligence have been so big that announcements from companies like Ndivida about their developments have managed to eclipse such grandiose presentations as the latest iPhone terminals. “AI features are becoming an integral component of all software solutions,” explains Daniel Mayer, head of thematic investing and senior portfolio manager at vontoble Conviction Equities. Spending on AI-based software is expected to reach $81 billion by 2027.

This market represents a “business opportunity,” says Mayer. But above all, the challenge: “monetizing the AI ​​offering.” That is, taking advantage of the economic benefits of a technology that is expanding, but requires a qualitative rather than quantitative incentive to make the sector and companies economically attractive in their development. Edmond de Rotschschild’s firm claims that, for example, ServiceNow (a platform that connects people, functions, and systems through digital workflows) “is one of the few companies that has managed to successfully monetize AI.

While 2023 was the year of increased investment in the infrastructure that enabled the development of artificial intelligence, 2024 should be the year “it will be revealed which companies can effectively capitalize on the opportunities that all these technologies present,” Mayer says. In particular, investors, who are real business thermometers, are betting on businesses like big linguistic models to reap significant rewards. Additionally, generative AI (tools that can create new ideas and content like conversations, stories, images, etc.) could spur a new wave of innovation and therefore make more money by capitalizing on previously undiscovered businesses.

Various analyses conducted in recent months agree that software, cybersecurity spending and, above all, data centers occupy the top positions in surveys of spending priorities of IT managers. Analysts’ assessments continue to be positive for companies like Nvidia precisely because of these forecasts. Its initial success demonstrates this potential, although other major players such as Microsoft (with OpenAI) and Google have also invested heavily.

Of all the business challenges AI faces, data centers are the most important. In fact, data center rentals are on the rise in anticipation of demand for workloads based on the technology.

The problem is that, faced with growing demand for data centers, prices and supply are facing some challenges. Because the main limitations of this technology are power availability, supply chain issues, and capital requirements. Power shortages, especially in the large markets favored by companies looking to install them, are a major obstacle to growing data center capacity.

In addition, addressing energy supply issues will be critical in the coming years. Possible solutions range from on-site energy generation (at the center itself, as in the case of self-consumption) to government-supported initiatives. Supply chain tensions and the need for significant infrastructure investments remain critical issues to keep pace with the growing demand for data center capacity.

To improve the AI ​​business and truly offer company owners value beyond the current benefits of the millions of dollars invested, stock market analysts are looking at specific sectors with potential for the technology. For example, healthcare or biotech. In fact, Europe’s data-rich environment plays an important role as a manufacturing powerhouse, and the diversity of its industries means it is well positioned to exploit this potential.

While AI without Nvidia would be unimaginable right now, there are plenty of other companies that could catapult their business, such as semiconductor manufacturers.

Despite all this uncertainty, there is no doubt that Nvidia has become the best thermometer for the evolution and future potential of artificial intelligence. So much so that its strength is already measured head-to-head with the GDP (gross domestic product) of many of the world’s great powers. Positive company results can bolster confidence in the tech sector and spur new investment, while any signs of a slowdown could cause concern among investors.