Forget Palantir: 2 Unstoppable AI Stocks to Buy Instead

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By Alex Sirois Published

Quick Read

  • Retail traders are chasing Palantir’s AI hype despite extreme valuations, while Alphabet and Meta are actually generating the cash flows to fund AI infrastructure buildout at rational multiples of 16x and 22x earnings respectively.

  • The analyst who called NVIDIA in 2010 just named his top 10 stocks and Google wasn't one of them. Get them here FREE.

Forget Palantir: 2 Unstoppable AI Stocks to Buy Instead

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Palantir (NASDAQ:PLTR | PLTR Price Prediction) is the AI stock retail traders cannot stop talking about, with Reddit sentiment scores spiking to 88 on May 19 and CEO Alex Karp boasting the company is “an n of 1” with a Rule of 40 score of 127%. Yet the valuation tells a very different story.

The Palantir Problem: Priced for a Decade of Perfection

Palantir trades at a price-to-earnings ratio of 191, a price-to-book of 42, and a price-to-free-cash-flow multiple near 148. At those numbers, the math requires flawless execution every quarter, in every product line, in every geography, for the next ten years.

The fundamentals are real. Q4 2025 revenue grew 70% to $1.41 billion, and management is guiding FY2026 revenue between $7.18 billion and $7.20 billion. The price is the issue, not the business. The stock is already down 23.9% year to date, with sentiment swinging from bearish scores of 35 to bullish 88 inside a single week. That is a crowded retail trade. Risk flags in the filing, including $684 million in stock-based comp, contracts terminable at customer convenience, and customer concentration, get ignored at this multiple. They will not stay ignored forever.

Retirement investors need cash flow. Here are the two stocks generating it.

Alphabet: The Cash-Flow King of AI Infrastructure

Alphabet (NASDAQ:GOOG) just delivered one of the cleanest AI quarters on record. Q1 2026 EPS of $5.11 crushed the $2.63 consensus, a 94.1% beat, on revenue of $109.90 billion, up 21.8% year over year. Three things matter for the long-term investor.

First, the full-stack moat is intact. Google owns the chips, the Gemini models, the training data, and the distribution. Gemini is now processing more than 16 billion tokens per minute via direct API use, up 60% from the prior quarter.

Second, enterprise demand is institutional. Google Cloud revenue grew 63% to $20.03 billion, with backlog nearly doubling quarter over quarter to over $460 billion. That backlog is the kind of commitment Palantir cannot match at any scale.

Third, the price is rational. Alphabet trades at roughly 16 times earnings with a 35.7% return on equity. The stock is up 22.74% year to date, and the fundamentals are still catching up.

Meta: The Most Profitable AI Distribution Engine on Earth

Meta Platforms (NASDAQ:META) is doing what Palantir is trying to do, just at twenty times the scale. Q1 2026 EPS of $10.44 beat the $6.66 consensus by 56.79% on revenue of $56.31 billion, up 33.1% year over year.

Three reasons it belongs in a retirement portfolio over the hype name. One, distribution scale that cannot be replicated: 3.56 billion daily active people across the Family of Apps, each monetized by AI ranking and ad targeting. Two, valuation discipline: roughly 22 times earnings with an 82% gross margin and 41.4% operating margin. Three, a proprietary AI stack. Meta Superintelligence Labs released its first model, and Llama means Meta pays no one else for the inference layer.

Meta is also down 8.63% year to date. That is the discount the crowd refuses to take while it chases the 191 multiple.

The Action

While retail traders chase Palantir, Alphabet and Meta stand out as the AI winners actually generating the cash to fund the buildout.

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About the Author Alex Sirois →

Alex Sirois is a financial writer with experience spanning both retail and institutional investing. He has written for InvestorPlace and held roles at BNY Mellon and Bernstein, giving him a perspective that bridges Main Street portfolios and Wall Street analysis.

Alex holds an MBA from George Washington University and has built his career across multiple industries, including e-commerce, education, and translation — a breadth of experience that informs how he breaks down complex financial topics for everyday investors. His writing is conversational, actionable, and grounded in long-term, buy-and-hold investing principles.

At 247 Wall St., Alex focuses on delivering analysis that is both accessible and useful, with a clear emphasis on helping readers make more informed decisions with their money.

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