Artificial intelligence will change everything from booking flights to brewing beer. Financial analysts estimate that AI will raise global GDP by about 10% to 20% over the coming decade. Just as most businesses became internet businesses in the 1990s and 2000s, nearly every business will be an AI business a decade from now.
To deliver the compute power fueling this transformation, companies, countries, and capital markets have mobilized resources at an unprecedented scale. When Chinese AI firm DeepSeek released its latest open-source model at a fraction of the expected training cost, it called these investments into question, inviting a tech selloff. Yet shares have rebounded. As economists would point out, for products with strong demand like AI, technological developments that lower costs through resource efficiency drive greater overall usage. Not surprisingly, Meta and Microsoft have since doubled down on their AI investments.
While cost reductions and open-source models make AI development more accessible to startups, supporting demand and pushing the frontier of AI will remain costly. Four major U.S. tech firms in particular—Meta, Alphabet, Microsoft, and Amazon—are spending massively on AI investments. And while returns to these investments have yet to materialize in their bottom lines, the sums needed in this development race have already rewritten the traditional rules of finance.
Running on cloud computing credits
While venture deal volume trended flat to down since the heady days of 2021 and early 2022, the rise of AI brought about two significant shifts. First, it crowded out other areas of investment, with 62% of all North American startup funding headed toward AI companies in the fourth quarter of 2024. Second, while deal volumes are down, deal values are up.
The staggering costs of compute needed to drive these AI companies sparked not just sky-high funding rounds but also solidified Big Tech’s dominance—few companies have sufficiently deep pockets to place these bets. OpenAI found its patron in Microsoft, Anthropic followed with Amazon. Both eschewed standard investment terms. Only a small part of Microsoft’s $10 billion 2023 investment went directly to OpenAI. Instead, most of the money was allocated as credits for OpenAI to purchase computing power from Microsoft’s cloud services.
In the age of AI, cloud computing credits have become currency. Access to GPUs and compute has made AI giants like Nvidia the investors of choice for most startups. As Elon Musk told investors at a conference in 2023, “GPUs at this stage are much more difficult to obtain than drugs.” AI companies spent an average of 22% of their expenses on computing costs in the first three months of 2024—more than double the amount spent by traditional software companies. Musk himself put his prodigious fundraising talents to work, closing a $6 billion fundraising round to build the largest supercluster in the world.
Through strategic funding arrangements offering cloud compute credits, Microsoft, Google, and Amazon have made the up-and-comers of the AI world reliant on the giants of the internet’s Gilded Age. These deals offer a host of benefits beyond the investment itself. The cloud providers not only gather new customers and acquire market share, they also benefit from the high margins on cloud computing services. Valuations increase in turn.
Fueling the AI future
While Big Tech firms can provide access to enough compute to support the growth of the industry, they also need to source sufficient power to actually run the GPUs, which are massively energy-intensive. AI-powered searches require as much as 10 times more electricity than a standard Google search. And usage is expected to grow dramatically over the next five years: Data center demand will likely take up 8% of total U.S. energy demand by 2030.
At the same time, giants like Google and Amazon have been under careful scrutiny for their energy consumption for years, and have responded with bold climate targets over the last decade. Historically, the vast majority of data centers were run off the grid, buying power like everyone else. Meanwhile, long-term power purchase agreements (PPAs) have been common in the energy industry for decades. They provide an energy purchaser with a stable rate and the supplier with guaranteed demand and have been common tools for corporations looking to advance their climate goals. Only in the last few years have tech giants begun using similar agreements as a solution to their new energy demand.
In this vein, Microsoft has revived the dormant Three Mile Island nuclear plant in Pennsylvania, the scene of the United States’ worst nuclear accident. Amazon recently purchased a data center campus near a 960-megawatt nuclear power plant for $650 million; the center’s power will move off-grid via an agreement with plant-operator Talen Energy. Google has signed an agreement to source energy from a fleet of mini nuclear reactors, while OpenAI’s Sam Altman and many other tech moguls are investing heavily in nuclear fusion. Energy markets have taken note, with the S&P 500 Utilities Index almost doubling its growth rate in 2024.
Gathering AI talent and technology
Faced with aggressive antitrust actions, Big Tech firms have also adopted creative mechanisms toward industry consolidation. Last year, joint ventures and partnerships increased by 40%. As talent becomes an increasingly valuable resource, companies have returned to “acquihires” to grow their research teams while steering clear of antitrust restrictions.
In 2023, Microsoft hired Mustafa Suleyman, the cofounder of Inflection AI, a company that raised over a billion dollars to support its own AI model. Along with him came hundreds of key employees and a $650 million licensing deal. In 2024, Google secured a licensing agreement with Character.ai, acquiring the company’s chatbot technology at the same time as it rehired its CEO and other key technologists. Both Microsoft and Google gained access to critical talent while distributing payments to employees and investors with sophisticated deal structures.
While talent-centric acquisitions have been a tool in the tech finance landscape for years, the clever coupling of acquihires with technology licensing is a new phenomenon. The popularity of these deals reflects the vigorous competition over AI talent and the market’s shift to consolidation in vanguard frontier models. With the prospect of artificial general intelligence and recursive self-learning creating a flywheel effect of continuous progress, the most valuable asset isn’t a product or service—it is the researchers and engineers driving the revolution.
The U.S. tech giants, which now represent a fifth of the S&P 500, will find new ways to adapt the world of finance to deliver on the promise of AI. AI’s productivity promises may still be in their infancy, but the race to procure AI has already delivered us a new era of technology finance.
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