August 2025

* A simple way to think about the chart above: moving from left to right is where the value creation will be; moving from top to bottom means more competition and dispersion of product.

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“The King is Dead! Long Live the King!” – The Mag 7 is dead. Long live…?

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That remains the trillion-dollar question. After over a decade of exceptional—and justified—returns, the future of these mega-cap tech companies feels uncertain amid the rise of AI. Thirty years ago, the internet reshaped the global economy, created new industries, disrupted legacy players, and altered our daily lives. AI may prove just as transformative—perhaps even more.

For investors, understanding how AI will impact the economy—and more specifically, the business models of these systemically important firms—will shape returns and alpha generation over the next decade. Not owning the Mag 7 over the past 10 years meant underperforming the market. Going forward, avoiding those most exposed to AI disruption will be critical.

This note outlines my current thinking on each of the Mag 7: who is positioned to thrive, who will survive, and who may struggle—or even face existential risk.

One core assumption underpins my analysis: LLMs will become commoditized.
Scale is the moat—and scale requires capital. To earn a return, you must monetize the model. I believe value will accrue to those building compelling applications on top of LLMs and distributing them efficiently. As with the internet, adoption accelerated once real utility (e.g., e-commerce, logistics optimization) became available.

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Survive and Thrive

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Amazon (AMZN)

Rather than building its own LLM, Amazon partnered with Anthropic—suggesting it sees more value in the application layer. By combining Anthropic’s LLMs with its own models, Amazon enhances AWS’s infrastructure and its utility to developers and enterprise users.

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Microsoft (MSFT)

Like Amazon, Microsoft has doubled down on its partnership with OpenAI. Its capital spending now emphasizes inference over training, with a clear goal: delivering real, user-facing utility. That said, Microsoft’s SMB franchise could face long-term pressure from AI-native operating systems adopted by startups and younger users.

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Apple (AAPL)

While some claim Apple has fallen behind in AI, I disagree. Apple has structural advantages: no other company combines such global reach, compute density, and hardware desirability as the iPhone. For AI to become truly useful to consumers, iOS-based apps will need to merge LLM-scale knowledge with on-device inferencing to offer personalized intelligence. Apple has the platform and distribution—it only lacks an LLM partner. A pivotal catalyst could be the DOJ’s ruling in its antitrust case against Google. A favorable verdict would likely open the door for Apple to partner with a leading LLM, potentially vaulting it into AI leadership.

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Nvidia (NVDA)

Model upgrades continue to validate AI scaling laws—ensuring demand for Nvidia’s latest chips. Beyond AI data centers, new buyers are emerging: sovereign nations, large enterprises, and more. Many overlook that GPUs also powers crypto and blockchain, both early in their adoption curves. When combining AI, crypto, and blockchain, the total addressable market for Nvidia may be far larger than most assume.

Survive? Yes. Thrive? It Depends

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Alphabet (GOOGL)

The risk: AI disrupts Google's core search business. The response: Gemini and AI Search aim to slow the decline. I’ve been bearish since ChatGPT’s 2022 launch, but now believe Google has the right ingredients: Cloud infrastructure, a competitive LLM, deep data assets (e.g., YouTube), and monetization paths via Android, GCP, and iOS. The DOJ’s upcoming antitrust ruling could serve as a clearing event—especially if it separates traditional search from AI search.

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Meta (META)

Zuckerberg’s hiring of a “super team” of AI engineers raises a question: bold move or desperation? I lean toward the latter. Meta’s open-source LLM strategy has fallen flat. More troubling is the risk that users shift attention toward personalized AI assistants—undermining Meta’s engagement-driven ad model. While Meta owns valuable assets, its AI team must now execute—and fast—against four established LLM players.

Multiple Challenges Ahead

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Tesla (TSLA)

Though not directly threatened by AI, Tesla warrants comment. The company is trying to pivot from EVs to robotics/autonomy—a bold move complicated by CEO Elon Musk’s erratic leadership. Musk overpaid for Twitter, abandoned OpenAI (a strategic blunder), and tainted Tesla’s brand through political theatrics. His AI startup xAI has shipped fast, but burns $1B/month—raising doubts about its sustainability and appeal to enterprise buyers. Tesla shareholders must now contend with a distracted CEO leveraging TSLA equity to fund side projects. This is not a constructive setup.

If you want to be a great active equity manager, you live for these opportunities – picking the right stock winners against a backdrop of a secular growth theme.

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These views are mine alone and may evolve as the technology landscape shifts.

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Sincerely,

Sam Rahman – Portfolio Manager, Hedgeye Asset Management

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