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Alphabet (GOOGL) reports earnings this afternoon, and expectations are high. Consensus estimates call for revenue of $101.28 billion, representing 23.9% year-over-year growth, and earnings of $2.87 per share, a 24.2% increase from the prior-year period.
Last year marked a breakout period for Alphabet, as its vertically integrated ecosystem of proprietary hardware, software and large language models pushed Gemini toward the leading edge of the AI race. That progress was accompanied by blistering growth in the company’s cloud business.
Year to date, however, Alphabet appears to have lost some momentum in model development and is no longer clearly keeping pace with the industry leaders, particularly Anthropic and OpenAI.
Even so, the underlying business remains strong. Search, YouTube and Google Cloud have all shown accelerating growth, reinforcing the durability of Alphabet’s core operations. Among the Magnificent Seven, GOOGL currently sits near the middle of the pack this year, modestly outperforming the S&P 500.
I should also note that I am excluding Tesla from my Magnificent Seven comparison. Tesla is undoubtedly a strong company, but I do not believe it currently belongs in the same fundamental category as the rest of the group. The other six businesses generally combine compelling economics, strong growth forecasts, secular tailwinds, reasonable valuations and durable competitive advantages. Tesla, by contrast, has produced more moderate growth, trades at an exceptionally rich valuation and operates in a highly competitive industry, and thus is not quite the same caliber of business.
Image Source: Zacks Investment Research
The Mixed Performance Among Magnificent Seven Stocks
Each company in the group has faced a distinct set of challenges, opportunities and investor narratives, producing widely different performance this year.
Apple (AAPL) has been the standout performer. As concerns about hyperscaler overspending have come to dominate the AI narrative, Apple has benefited from its comparatively limited capital expenditures on data centers. It also controls one of the world’s most valuable pieces of digital real estate, serving as a primary gateway through which consumers can access leading AI models and applications. That unique position has attracted significant investor interest this year.
Apple currently trades at 37.4x forward earnings. Sales are expected to grow 15.1% this year and 8.2% next year, while earnings are projected to increase 13.2% annually over the long term.
Nvidia (NVDA) remains the central pillars of the AI boom. Its GPUs provide the critical computing infrastructure behind the development and deployment of advanced AI models. Nvidia also benefits from a relatively capital-light business model, designing its chips while outsourcing manufacturing to semiconductor foundries.
The stock trades at 22.8x forward earnings, near the low end of its historical range. Revenue is projected to rise 79.6% this year and 39.7% next year, while earnings are expected to grow 58.3% annually over the next three to five years.
Amazon (AMZN) is leading the group in capital spending, with approximately $200 billion in planned expenditures this year, much of it dedicated to expanding its data center infrastructure. Amazon Web Services has continued to accelerate as AI usage grows, while the company is also building out its own custom-chip business to support both its internal operations and external customers.
Interestingly, Amazon has remained somewhat outside the center of the AI conversation over the past year despite its enormous infrastructure investments. The stock trades at 27.7x forward earnings, near its lowest historical valuation levels. Sales are projected to grow 15.3% this year and 13.1% next year, while earnings are expected to increase 17.3% annually over the long term.
Meta Platforms (META) has experienced a more volatile ride. In typical Zuckerberg fashion, the company has committed aggressively to its newest strategic priority, spending billions on acquisitions, large compensation packages for leading AI researchers and a massive expansion of its data center footprint. Meta now ranks second among the hyperscalers in capital expenditures, with an estimated $125 billion to $145 billion planned this year.
At the same time, Meta’s efforts to compete at the leading edge of large language model development have produced mixed results. While its strategy has occasionally appeared less coherent than those of its peers, the company’s enormous infrastructure buildout may now be opening a new opportunity.
With vast computing capacity but less differentiated model technology, Meta has begun selling access to its data center infrastructure through its emerging Meta Compute business. That could create an entirely new revenue vertical for a company that has historically relied overwhelmingly on advertising. Execution will be critical, but I am interested to see the early financial contribution from this business.
Meta trades at 19.5x forward earnings, near the low end of its historical range. Sales are expected to grow 26% this year and 20% next year, while long-term earnings growth is projected at 20.1% annually.
Microsoft (MSFT) has been the clear laggard. Despite its partnership with OpenAI and its extensive portfolio of productivity software, the company has struggled to translate its early AI advantage into compelling product adoption and monetization. Microsoft was also caught in the broader software selloff, driven by concerns that generative AI could disrupt many established software business models.
The stock trades at 20.6x forward earnings. Sales are projected to grow 16.9% this year and 15.9% next year, while long-term earnings are expected to increase 16.9% annually.
What Comes Next for Alphabet and the Magnificent Seven?
Broadly speaking, the Magnificent Seven have lagged behind the strongest parts of the AI trade this year, particularly semiconductors and other infrastructure-oriented stocks. That leadership has been unusually narrow, however, and many of those names have recently undergone sharp corrections.
Against that backdrop, the Magnificent Seven now appear increasingly attractive. The group combines reasonable valuations, strong earnings growth and continued leadership across the most important areas of the digital economy.
The key variable remains investor sentiment toward AI infrastructure spending. Markets are increasingly questioning whether hyperscalers can generate sufficient returns on the enormous sums being committed to data centers, chips and model development. So long as those concerns remain contained, I believe the group is positioned for stronger performance into year-end.
The quarterly results themselves are often less surprising than the market reaction suggests. These companies generally manage expectations carefully and tend to issue conservative guidance, though unexpected developments are always possible.
Unless one of the companies delivers a truly unusual report, I expect the market’s broader interpretation of AI spending, monetization and returns on investment to matter more than any single quarter’s headline numbers.
This article originally published on Zacks Investment Research (zacks.com).
