To The Moon

🔥🤖 Dan Ives’ 2026 AI Top 5: What He’s Really Betting On — And Why the Market Is Still Arguing

Dan Ives just laid out his Top 5 AI Tech Stocks for 2026, and the list is less about chasing what’s hot — and more about where AI value ultimately concentrates.

$MSFT

$PLTR

$TSLA

$AAPL

$CRWD

At first glance, it’s controversial.

No $NVDA in the Top 5 for the coming year.

$PLTR widely considered one of the most overvalued stocks in modern market history.

$AAPL included not as an AI lab, but as a consumer platform.

But the logic underneath the list is consistent.

Ives’ core theme is simple: the AI revolution is being monetized through hyperscalers, consumer platforms, and enterprise software — not just chips.

On the hyperscaler side, $MSFT sits at the center of AI distribution. It’s not just about models — it’s about cloud, enterprise relationships, and workflow dominance. Microsoft is where AI becomes default infrastructure.

On the consumer side, $AAPL is the wildcard. Ives’ view is that AI at scale doesn’t require the best model — it requires the best distribution. With billions of devices, Apple becomes the interface layer where AI quietly embeds itself into daily behavior.

The most debated name is clearly $PLTR.

Ives predicts Palantir could reach a $1 trillion valuation within two to three years. That sounds extreme, especially given how frequently Palantir is cited as “overvalued.”

But that’s exactly the point.

This is not a traditional software valuation call. It’s a bet that AI-native enterprise platforms with deep data integration become strategic assets, not optional tools. If governments and enterprises increasingly rely on Palantir-style systems for decision-making, valuation frameworks shift from SaaS multiples to infrastructure logic.

$CRWD fits cleanly into this thesis.

As AI expands, so does the attack surface. Security isn’t discretionary — it scales with complexity. CrowdStrike benefits not from AI optimism, but from AI inevitability.

$TSLA’s inclusion reinforces Ives’ broader view that AI leadership isn’t limited to data centers. Autonomous systems, robotics, and real-world AI deployment matter just as much as models and chips.

What about $NVDA?

Ives made it very clear: he remains extremely bullish. He still calls Jensen Huang the “godfather of AI.” The omission isn’t a downgrade — it’s an acknowledgment that NVIDIA is already recognized as the core supplier, while the next leg of AI upside may spread outward to platforms and applications.

He also flagged something the market continues to debate: a potential renaissance at $ORCL.

Ives argues investors are underestimating Oracle’s positioning, pointing to a $530B RPO backlog and a $300B OpenAI-related order pipeline. Whether those numbers fully materialize or not, the message is clear — legacy cloud players with scale and enterprise trust may surprise on the upside.

Taken together, Ives’ list isn’t about who builds the best AI.

It’s about who controls distribution, workflows, and long-term customer dependency.

The real question for 2026 isn’t whether AI spending grows.

It’s whether investors are still too focused on the front-end of the stack — while the back-end platforms quietly absorb the value.

📮 I focus on long-term AI positioning across hyperscalers, enterprise software, and real-world deployment — especially where market skepticism and structural importance collide.

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