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AI Investment Picks: Analyst Reveals Top Stocks for 2026

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  //stocks-investing.news-articles.net/content/202 .. t-picks-analyst-reveals-top-stocks-for-2026.html
  Published in Stocks and Investing on Tuesday, December 30th 2025 at 15:06 GMT by CNBC

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AI Dominance: Analyst Predicts Top Picks & Hints at Meta’s Next Play in 2026

The artificial intelligence boom shows no signs of slowing down, and investors are scrambling to identify the companies poised to capitalize on its continued growth. According to Wedbush Securities Managing Director, David Chiappetta, while the AI landscape is crowded, a select few stocks are set to truly dominate in 2026. In a recent CNBC interview, Chiappetta outlined his top picks and offered intriguing insights into what Meta Platforms might be planning next. The analysis focuses on the evolving infrastructure needs of generative AI models – specifically, the demand for advanced chips and data center capacity – as key drivers for investment.

The Chip Champions: Nvidia Remains King, But Competition Emerges

Unsurprisingly, Chiappetta’s list begins with Nvidia (NVDA). The company has become synonymous with AI hardware, its GPUs being the gold standard for training and deploying large language models (LLMs). Chiappetta emphasizes that Nvidia's dominance isn't just about current performance; it's about their established ecosystem, software tools like CUDA, and a massive installed base. He believes Nvidia will continue to see robust demand, even with increasing competition. As the article points out, Nvidia’s market capitalization has soared, reflecting this confidence (currently exceeding $3 trillion). However, Chiappetta acknowledges that Nvidia's valuation is already high, suggesting potential for limited upside unless they can consistently deliver on future growth expectations.

Beyond Nvidia, Chiappetta highlights Advanced Micro Devices (AMD) as a significant contender. AMD has been aggressively pursuing the AI chip market with its MI300 series accelerators, directly challenging Nvidia’s supremacy. The MI300 chips are designed to be competitive in both training and inference workloads, offering a compelling alternative for companies looking to diversify their supply chain or seeking potentially better price-performance ratios. Chiappetta notes that AMD's success hinges on securing design wins with major cloud providers and AI developers – essentially proving its technology can reliably handle the demanding tasks of modern AI. The article references AMD’s recent earnings call where they highlighted increased MI300 demand, signaling early signs of this adoption.

Finally, Chiappetta includes Taiwan Semiconductor Manufacturing (TSM) on his list. While not a chip designer itself, TSM is the world's largest contract manufacturer of semiconductors and plays a crucial role in producing chips for both Nvidia and AMD – and countless other companies. The demand for leading-edge fabrication capabilities to produce increasingly complex AI chips means TSM’s services are essential. Chiappetta argues that even if Nvidia or AMD stumble, TSM will continue to benefit from the overall growth of the AI market. The article points out that geopolitical tensions surrounding Taiwan add a layer of risk to investing in TSM, but its strategic importance remains undeniable.

The Data Center Powerhouse: DigitalOcean’s Untapped Potential

While chipmakers are essential, powering these chips requires massive data centers. Chiappetta's third pick is DigitalOcean (DOCN), a cloud computing provider that caters to small and medium-sized businesses (SMBs). This might seem like an unusual choice compared to the giants like Amazon Web Services (AWS) or Microsoft Azure, but Chiappetta believes DigitalOcean is uniquely positioned to benefit from the AI boom. He argues that as smaller companies begin experimenting with generative AI applications, they’ll need accessible and affordable cloud infrastructure – a niche where DigitalOcean excels. DigitalOcean's focus on developer tools and ease of use makes it attractive to businesses lacking in-house expertise. The article notes that DigitalOcean has been steadily gaining market share and its stock price reflects growing optimism about its future prospects.

Meta’s Next Move: A Potential AI Infrastructure Play?

Beyond his top three picks, Chiappetta offered a fascinating glimpse into what Meta Platforms (META) might be planning. He suggests that Meta is likely to become a significant player in the infrastructure side of AI, potentially even offering its own AI chips and data center services to other companies. This would represent a strategic shift for Meta, moving beyond solely using AI to enhance its existing social media platforms.

Chiappetta’s reasoning stems from Meta's massive investments in AI research and development, particularly around open-source LLMs like Llama. Running these models requires enormous computing power, and building that infrastructure internally gives Meta a significant cost advantage. He posits that Meta could eventually monetize this internal expertise by offering its resources to other companies struggling with the high costs of AI infrastructure. This would be akin to Amazon’s AWS model – leveraging internal needs to create a profitable external business. The article references Meta CEO Mark Zuckerberg's comments about "metaverse" investments potentially contributing to AI capabilities, hinting at a broader strategic vision.

Risks and Considerations

While Chiappetta’s outlook is bullish, he acknowledges the risks involved in investing in AI stocks. Competition remains fierce, and technological advancements could quickly disrupt existing market leaders. Geopolitical factors, particularly concerning Taiwan Semiconductor Manufacturing, also pose a significant threat. Furthermore, valuations for many AI-related companies are high, leaving limited room for error.

Conclusion:

David Chiappetta’s analysis provides a compelling framework for understanding the evolving landscape of artificial intelligence investments. While Nvidia remains the dominant force in AI hardware, AMD and TSMC offer attractive alternatives. DigitalOcean's potential to serve the growing demand from SMBs adds an intriguing dimension to the sector. And Meta’s possible foray into AI infrastructure could reshape the competitive dynamics entirely. Investors considering exposure to the AI boom should carefully weigh these opportunities against the inherent risks and conduct thorough due diligence before making any decisions.

I hope this article provides a comprehensive summary of the CNBC piece! Let me know if you'd like any adjustments or further elaboration on specific points.