The AI investment landscape is evolving, with major tech players like Microsoft, Alphabet, Amazon, and Meta projected to increase their combined AI capital expenditures from $148 billion in 2023 to $222 billion in 2024 and potentially $267 billion by 2025. However, despite the significant spending, the return on investment has been limited, and revenues have not yet matched the scale of these investments. The challenge lies in translating technological advancements into tangible profits. While there is hype surrounding AI, the market is still grappling with this issue.
There is a positive sign that the gap between revenue and capital expenditures is narrowing, indicating that monetization of AI may become more pronounced in the future. Leading cloud platforms, which serve as AI data centers, have experienced revenue growth exceeding 25 percent, up from around 20 percent in late 2023. This suggests that investments in AI are starting to yield results, although profitability is still in its early stages. The anticipated monetization of AI is expected to happen more prominently in 2026 and beyond as companies refine their strategies and capitalize on emerging opportunities.
Advancements in AI capabilities are also noteworthy. The development of large language models, such as the ability to use generative AI prompts as inputs (synthetic data), has progressed significantly. NVIDIA is a leader in this space, providing the necessary hardware to power AI applications at unprecedented rates. As these technologies mature, widespread adoption across various industries becomes increasingly apparent.
Recent surveys show a growing trend in AI adoption among U.S. companies, with usage increasing from 3.7 percent in September 2023 to 5.9 percent in September 2024. It is expected to reach 8.7 percent within the next six months. Key sectors leading this adoption include IT, professional services, educational services, finance and insurance, real estate and rental, and healthcare. The transformative potential of AI is highlighted, with confidence that virtually no industry will remain untouched by these technologies.
UBS has developed an investment strategy focused on big tech companies, considering them well-positioned to capitalize on AI advancements due to their financial strength and customer base. The strategy involves three layers: the enabling layer (infrastructure like GPUs, data centers, and power generators), the intelligence layer (large language models), and the application layer (where monetization occurs). The allocation strategy involves investing 50 to 60 percent in the enabling layer, 15 to 20 percent in the intelligence layer, and 30 percent in the application layer.
While the valuations of these tech giants may seem high, UBS believes they are justified by a positive earnings growth outlook that could lead to substantial returns. However, there are risks involved, including regulatory scrutiny, cybersecurity threats, seasonal volatility, and the possibility of export controls on critical components like chips. These factors could impact the pace of AI adoption and the overall investment climate in the sector.
As the AI market continues to mature, the interplay between investment, technological advancement, and regulatory considerations will shape the future of this dynamic field. The journey towards monetization may be gradual, but those who navigate this landscape effectively could potentially reap significant rewards.