3 Most Important Growth Stocks to Buy in the First Half of 2026


The new year doesn’t seem so new anymore. January is already almost halfway over. Before you know it, we’ll be looking ahead to 2027.

No one can slow down time. It is important to seize great opportunities as early as possible. That’s why I think the following three top growth stocks are great picks to consider buying in the first half of 2026.

A clock showing "It's time to buy."
Image source: Getty Images.

I really like the growth prospects Metaplatforms (NASDAQ:META) has with its Meta Ray-Ban Display glasses. These are the first artificial intelligence (AI) glasses with a private display integrated into the lens and a neural band wrist control. I consider Meta’s first mover advantage a big plus.

Is Meta CEO Mark Zuckerberg correct that glasses are “the ideal form factor for AI”? Yeah. No other device can process everything a user sees and hears. I’m not at all surprised that Meta sold so many of its glasses in the US that it had to delay the global rollout.

While I’m excited about Meta’s latest AI glasses, they’re not the main reason to buy this stock at the moment. That honor belongs to the company’s huge user base, which gives it pricing power with advertisers. On average, 3.54 billion people used Meta apps every day in September 2025. This number reflects an 8% year-over-year increase. This also represents almost 43% of the world’s population.

These users don’t seem to disappear. As long as that remains the case, Meta will generate billions of dollars in revenue and profits – and the company’s stock should perform well. AI glasses and Meta’s big bet on AI superintelligence (AI) are just the icing on the cake.

If you’re looking for a bargain in AI stocks, you might want to buy shares of Micron technology (name: mu). It is forward price/earnings ratio is 10.8. Micron’s price-to-earnings-to-growth (PEG) ratio, based on analysts’ five-year earnings growth projections, is remarkably low at 0.6.

Why is Micron stock so cheap? Its price is based on an outdated paradigm that views memory as a simple cyclical product. This perspective was correct until high-bandwidth memory (HBM) became such a critical component of AI chips and the demand for AI chips exploded.



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