AI Investment Surge Faces Profitability and Regulatory Challenges as Semiconductor Stocks Outperform

The technological landscape is expanding, with artificial intelligence starting to play a seminal role in the next generation of computing. Many notable companies are establishing or integrating AI capabilities into their technological infrastructure. The proliferation of AI and its potential to bring about work efficiencies and newfound innovations is raising the expectations not only of consumers but also of investors who have exposure to companies within the AI ecosystem.

While much of the discussion about AI has centered on the Magnificent Seven – Apple, Amazon, Google, Meta, Microsoft, Nvidia and Tesla – with a particular focus on Nvidia, the AI ecosystem is expansive and reflects differing stakeholders. Essential to AI development are semiconductors or chips; tiny electronic devices designed to enable functions such as processing, storing, sensing and moving data or signals. AI models employ different types of chips, including memory chips to store large amounts of data and logic chips to process the data. According to Gartner, revenues from AI semiconductors are forecast to be $137 billion by 2027, growing by a five-year compound annual growth rate of 26.5%.

As reported by Market Watch, chips/semiconductor stocks outweighed software stocks in the S&P 500 for the first time in June and had the largest overall sector weighting. The changing of the guard reflects Wall Street's expectations about the semiconductor sector's ability to capitalize financially on AI. On a company level, Nvidia and Advanced Micro Devices are chip designers leading innovation by continuing to push the limits of chip performance, enabling more complex and powerful AI applications. Conversely, end-user companies, such as Meta, are making material investments in their AI capabilities as they continue accelerating infrastructure investments to support their AI roadmap.

In Q2 2024, Meta reported total revenues of $36.46 billion and a net income of $12.37 billion, increasing by 27% and 117%; respectively, compared to the same period in 2023. The firm anticipates full-year 2024 capital expenditures will be in the range of $35-40 billion, an increase from their prior range of $30-37 billion, due to their ongoing AI spending.

While AI's potential is significant, growing concerns exist about firms' overinvestment and whether it will manifest as profit or be a cash pitfall. As noted by Forbes, there is a growing sentiment that for the millions that have been invested in AI, the returns thus far have been underwhelming – chatbots lacking a clear monetization strategy, cost-cutting approaches such as AI-driven coding and customer service and AI-powered search that occasionally generates inaccuracies. It would seem that the AI return on investment, thus far, isn't living up to the large capital expenditures being made. Still, many leading big tech firms remain committed to investing in this space.

On the regulatory side, the European Commission recently ratified the European Artificial Intelligence Act (AI Act), the world's first comprehensive regulation on AI. The AI Act aims to ensure that AI developed and used in the European Union is trustworthy and includes safeguards to protect fundamental rights. The regulation seeks to create a harmonized internal market for AI within the EU, fostering the adoption of this technology and creating a supportive environment for innovation and investment. Given the intense regulatory focus placed on big tech companies, including Alphabet, Amazon, Apple, ByteDance, Meta and Microsoft in Europe, the implications of the AI Act on their operations have yet to be determined.

For traders looking to gain leveraged exposure to the fits and starts caused by the volatility of companies involved in the AI ecosystem, Direxion's Daily AI and Big Data Bull and Bear 2X Shares offer enhanced, pure-play exposure to companies from the United States that have business operations in artificial intelligence applications and big data. These high-risk ETFs are best suited for those who can actively manage the inherent risks of leverage and are looking to capitalize on short-term trends occurring in the AI and big data industry.