Key takeout
- Stock market returns over the remainder of the year can be strongly influenced by infrastructure spending, cloud computing trading, and positive sentiment to lift AI and tech stocks.
- Some experts warn that an increasingly “cyclical” AI ecosystem (companies investing in their own customers) are vulnerable to changes in the business environment.
- The sentiment around AI, and the possibility that early technology will disappoint investors, remain important risks for AI stocks.
The US stock market was boosted by hitting near record highs in the final quarter of this year and surged AI stocks, which are increasingly important to market performance.
Most of the most performant stocks in the S&P 500 this year are directly linked to the AI boom. Data storage companies Seagate Technology (STX) and Western Digital (WDC) see almost three value in their stock this year, while Palantir (PLTR) and Applovin (APP) have more than doubled two software companies that are better at translating AI features into revenue. And despite a rough start to 2025, all seven epic stocks have been growing since the beginning of the year.
Why is this important to you?
The artificial intelligence boom has been the main source of fuel driving the bull market over the past few years. As a result, the performance of most investment portfolios is increasingly linked to the performance of AI stocks.
These are seven spectacular explanations that account for a third of the S&P 500, and therefore have a major impact on the performance of the broader market. Experts say these stocks are increasingly linked to AI.
“Stock prices are a daily referendum on whether AI is considered hype or reality,” wrote Christopher Gannatti, global research director at WisdomTree in a recent blog post. They said, “The price is as though AI is not just a growth driver, Growth drivers,” added Gunnatti.
Therefore, investment, trading and optimism that drives AI trade could be crucial for the stock market as a whole in the coming months.
Capex could stay in the spotlight
Large infrastructure investments from Microsoft (MSFT), Alphabet (Goog), Amazon (AMZN), Meta (Meta) and others are the major fuel sources for AI rally. Their spending exploded the revenues of chipmakers like Nvidia (NVDA), Broadcom (AVGO), and Micron (MU), supporting the narrative that AI demands are insatiable.
Hyperscalar updates all investors on capital expenditure plans when reporting quarterly results from late October to early November. While Alphabet and Meta each raised CAPEX forecasts in their latest revenue reports, Microsoft and Amazon said they will continue to invest heavily in infrastructure throughout the year.
A tax change codified by one big beautiful bill that allows businesses to write off their infrastructure investments immediately could give reasons to raise CAPEX even further. Experts should note that immediate amortization should promote free cash flow and allow companies to invest more in AI. Hyperschool took months to figure out how the bill signed into law by President Donald Trump on July 4th would affect the finances and therefore how the investment was signed.
Citi analysts on Tuesday estimated that HyperScalers, including Oracle (ORCL) and CoreWeave (CRWV), will spend $490 billion on infrastructure, up from the previous estimated $420 billion. “The key hyperscalers hope to reflect this incremental spending on guidance discussions during the 3Q results,” the analyst wrote.
An unexpected increase in CAPEX guidance could bolster Wall Street's bullishness against semiconductor, software and energy companies that benefit most from AI buildouts.
Large multi-year deals attract more attention
“There's a bit of an evolution in the AI Rally drivers,” Gunnatty said. Investopedia.
“It started with Hyperscalers from Microsoft, Amazon and Alphabet. “We have a certain amount of cash flow. We're going to make an investment.” Today, Gannatti says, AI companies are investing in each other and using those investments to buy goods and services.
The most notable example of this was announced last month when Openai committed to deploying a 10-gigawatt Nvidia system to train and run next-generation models. In return, NVIDIA will invest $100 billion in Openai, effectively subsidizing the startup's infrastructure costs as capacity is provided online.
“So there's a bit of cyclicality,” Gunnatty says. “None of these are guaranteed,” he said. This includes Openai's commitment to spending $300 billion on Oracle's cloud computing services over the next five years. “If the business environment changes, music may not necessarily be forever and may need to stop for a while.”
Concerns about AI bubbles that are likely to last
Investors have been worried about the AI bubble for quite some time, and the rally faces the risk of AI sentiment being sour, squeezing investment and stock prices down.
So far, tech companies have been able to show investors enough AI profits because Wall Street is happy with its spending, says Gannatti. “But you always feel like you're always away from one revenue cycle from a negative interpretation of a particular announcement.
Several events this year seemed temporarily to be this fork moment. In January, investors gained winds from the super-efficient reasoning model of Chinese startup Deepseek, temporarily questioning the wisdom of Silicon Valley's AI spending. AI was also surprised at the summer when a survey by MIT found that 95% of corporate-generated AI pilot projects failed to achieve return on investment. However, at every opportunity, investors shaking panic and continuing to build up on AI stocks.
There is reason to be optimistic that today's AI boom is more resilient than the bubbles that are often compared. “The positive is that at least it's not funded with debt yet,” Gunnatti said. “So, for example, it wasn't like the optical buildouts of fiber in 1999 and 2000, and the companies didn't have the basics.”
Instead, companies that fund AI build-outs have the biggest business, the healthiest balance sheet, and the deepest pocket of any company on the planet. Their highly profitable non-AAi companies can mitigate the fallout of emotional change to AI.
