Does winning the AI race still require massive spending?
The artificial intelligence (AI) arms race shows no signs of slowing, and this week’s fourth quarter results announcement by Google, owned by Alphabet Inc. (NASDAQ:GOOG), suggests that significant investment is still seen as a necessity – especially when it comes to powering the next generation of AI models. Following the release of China’s DeepSeek, the question is not only whether the hefty spending is sustainable, but whether it truly gives U.S. tech giants the edge they’re hoping for?
Why is Google doubling down?
A surge in capital expenditure
Google recently announced it will devote US$75 billion to capital expenditure for the coming year, raising eyebrows across the tech world. That figure represents a dramatic jump from last year’s US$52.5 billion and accounts for nearly 19 per cent of Google’s projected annual revenue. Historically, Google has allocated an average of 13 per cent of its yearly revenue toward capital outlays, making this an outsized bet that AI could shape the future.
The news also came amidst mixed financial results. Google’s fourth-quarter earnings fell just short of Wall Street’s expectations, driven by disappointing growth in its Cloud and device divisions. The company’s quarterly revenue came in slightly under the US$96.6 billion projection – its first revenue miss in two years. Following the report, Alphabet’s share price dropped over 7 per cent in after-hours trading.
Why AI demands so much investment
Massive capital outlays have become the norm for companies competing in the AI space. Microsoft (NASDAQ:MSFT) and Meta (NASDAQ:META), Google’s key rivals, are each expected to spend over 30 per cent of their revenue on capital expenditures this year. Microsoft’s spending is anticipated to surpass US$90 billion (excluding any further direct investment in OpenAI), while Meta plans to boost its spending by more than 60 per cent, reaching up to US$65 billion.
Table 1. All in!
| Capital spending, calendar year, US$ billion | ||||
| 2022 | 2023 | 2024 | 2025 | |
| Alphabet | 31.5 | 32.25 | 52.54 | 75 |
| Amazon | 64.3 | 53.4 | 77.1 | 86 |
| Microsoft | 28.4 | 41.2 | 75.6 | 93.7 |
| Meta | 32 | 28.1 | 39.2 | 65 |
What’s driving these numbers? Generative AI demands immense computational resources to train advanced models to infer and then and them. Powerful computing chips, such as those from Nvidia (NASDAQ:NVDA), are the backbone of AI advancements. The belief is that without continuous investment in cutting-edge infrastructure, a company risks being left behind by rivals who can scale faster and develop more efficient models.
As we have written previously, however, the revenue models for all of these AI advancements remain nascent at best. Microsoft might incorporate AI into its Office software and call it Co-Pilot but are many users paying much more for a subscription? The answer is not yet.
The billions being invested are therefore ‘on spec’. Speculative.
Is there a spending ceiling?
While the consensus has largely been that spending heavily on infrastructure is essential, a recent twist has cast some doubt. A Chinese AI startup, DeepSeek, recently demonstrated that advanced AI models could potentially be built with less computational power and energy than previously thought. This revelation led to a significant market selloff, with Alphabet’s stock falling over four per cent and Nvidia’s experiencing a near 20 per cent drop.
Perhaps to save face, or perhaps to save their share prices and therefore their own wealth, the major tech company leaders have been quick to push back on this narrative.
Meta CEO Mark Zuckerberg recently argued that heavy investment in capital expenditures provides a strategic advantage, allowing companies to outpace competitors in both performance and scale. In other words, there may be more efficient ways to build a large language model (LLM), but the best ones will be the most expensive to build. During Tuesday’s earnings call, Google’s CEO, Sundar Pichai, reinforced this stance, emphasising that Google’s AI development strategy prioritizes cost efficiency while scaling.
Google’s strategic advantages
Unlike smaller players in the AI race, Google has several factors working in its favour:
Strong revenue streams: Google’s core search advertising business remains a cash cow, with operating margins for its Google Services segment increasing to 39 per cent from 35 per cent year-over-year. This profitability ensures the company can fund its ambitious AI investments without jeopardising its financial health.
Improved cloud profitability: Although Google Cloud’s revenue growth underwhelmed, its operating income more than doubled year-over-year, reaching over US$2 billion. This provides another layer of financial stability.
Cash reserves: With US$99 billion in net cash – significantly higher than Microsoft’s US$42 billion and Meta’s US$49 billion – Google is well-positioned to weather fluctuations in the market and maintain its aggressive spending strategy.
Does spending guarantee success?
The short answer is we don’t know for sure, but presumably the chances of success are higher.
Pichai’s statement regarding AI, that “it’s as big as it comes”, highlights how he and the company views this AI moment as pivotal.
While heavy investment is currently seen as crucial, when it comes to technology, the future winner isn’t always today’s biggest player. Companies must focus on building AI models that are not only powerful but also efficient and therefore cost-effective. Google’s emphasis on reducing the cost per query is one way it aims to achieve this balance.
The AI race is far from over, and for now, substantial spending on computing infrastructure is seen as critical for staying ahead. However, as technological breakthroughs like those demonstrated by DeepSeek emerge, companies may find their massive spending is either unnecessary or leads to oversupply. While Google’s deep pockets and strategic advantages give it a leg up, the next phase of AI development may reward those who can innovate efficiently – not just those who can outspend.
Remember the metaverse?
Roger Montgomery is the Founder and Chairman of Montgomery Investment Management. Roger has over three decades of experience in funds management and related activities, including equities analysis, equity and derivatives strategy, trading and stockbroking. Prior to establishing Montgomery, Roger held positions at Ord Minnett Jardine Fleming, BT (Australia) Limited and Merrill Lynch.
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