In recent years, artificial intelligence (AI) has transformed how businesses operate, from automating customer service to optimizing supply chains. As AI adoption accelerates across industries, one of its most critical components—compute workloads—is undergoing a significant shift. While training models have traditionally dominated the AI landscape, the focus is now turning toward inference, which involves using trained AI models to make real-time predictions or decisions.

This transition has created new opportunities in the semiconductor industry, particularly for companies that specialize in inference-focused chips. While giants like Nvidia and Broadcom are still major players, they’ve underperformed this year despite strong sector-wide gains. Enter Qualcomm—another tech giant with a different strategy and valuation profile that could position it as one of the top AI inference stocks to watch over the next three years.

The Rise of Inference in AI Workloads

Inference is the phase where an already trained AI model processes new data to produce results, such as identifying objects in images or recommending products. Unlike training, which requires massive computational power and energy, inference demands efficiency and speed. As a result, it’s becoming increasingly important for businesses looking to deploy AI at scale without breaking the bank.

According to Deloitte, inference workloads are expected to account for two-thirds of all AI-focused compute in data centers this year—up from 50% in 2025. This shift is driven by the growing need for real-time decision-making and cost-effective deployment of AI models across industries like healthcare, finance, and logistics.

This surge in demand has led to a sharp increase in interest for inference-optimized chips, which are designed to deliver high performance while consuming less power and costing less to operate. While Nvidia remains the leader in this space with its range of AI accelerators, Qualcomm is making significant strides by targeting both data centers and edge computing.

Why Qualcomm Is Poised to Outperform

Qualcomm has long been known for its dominance in mobile technology, particularly in smartphones and 5G connectivity. However, the company is now expanding into a new frontier: AI inference chips. Unlike traditional chipmakers that focus on general-purpose processors, Qualcomm is leveraging its expertise in low-power computing and wireless communication to develop specialized hardware tailored for AI workloads.

At its Investor Day 2026, Qualcomm revealed ambitious plans to capture a significant share of the data center market. The company expects to generate at least $15 billion in revenue from data centers by fiscal 2029, which is a massive leap for a firm that has historically relied on consumer electronics.

Qualcomm’s strategy involves offering a wide range of AI-powered solutions, including:

• Custom AI processors optimized for inference tasks
• Liquid-cooled rack-scale servers designed for high-density computing
• Connectivity solutions to support edge-to-cloud data flows
• High-bandwidth memory systems to improve performance

One of the most notable partnerships is with Meta Platforms, which has already begun deploying Qualcomm’s Dragonfly C1000 server CPU in its data centers. This collaboration suggests that Qualcomm is not only gaining a foothold in the AI inference market but also securing long-term contracts with major tech players.

A Valuation Advantage That Could Pay Off

Despite its strong growth potential, Qualcomm currently trades at a more attractive valuation compared to Nvidia and Broadcom. While both semiconductor giants have seen their stock prices rise this year, they’ve struggled due to high valuations that make them less appealing for investors looking for upside potential.

Qualcomm’s current price-to-earnings (P/E) ratio stands at 17 times forward earnings, significantly lower than Nvidia’s 30x and Broadcom’s 61x. Its sales multiple is also more favorable, sitting at 4.6x compared to Nvidia’s 18.6x and Broadcom’s 24x.

This valuation gap suggests that Qualcomm could see a substantial price appreciation if its growth projections materialize. If the company achieves its goal of $18 per share in earnings by fiscal 2029, and assuming it trades at a P/E ratio similar to the Nasdaq-100 index (around 26x), its stock price could rise to $473—a potential increase of over 150% from current levels.

The Broader Implications for AI Adoption

The shift toward inference in AI is not just a trend—it’s a fundamental change in how businesses deploy and scale AI. As companies look to reduce costs while maintaining performance, the demand for efficient, specialized hardware will only grow. Qualcomm’s entry into this space with its focus on low-power, high-efficiency chips positions it well to benefit from this transition.

Moreover, the company’s ability to secure long-term contracts with major clients like Meta indicates that it is not just a short-term play but rather a sustainable growth opportunity. This stability could make Qualcomm an attractive investment for both retail and institutional investors looking to capitalize on AI-driven innovation.

Conclusion

Qualcomm may not be the first name that comes to mind when thinking about AI, but its recent moves into inference-focused computing suggest it’s well-positioned to become one of the biggest winners in the AI revolution. With a strong pipeline of products, strategic partnerships, and a more attractive valuation than its competitors, Qualcomm could deliver significant returns over the next three years.

As the demand for efficient AI inference continues to rise, investors should keep an eye on how Qualcomm executes its expansion into data centers and edge computing. The company’s ability to innovate in this space—and secure long-term contracts with industry leaders—could make it a standout stock in the AI era. For those looking to invest in the future of artificial intelligence, Qualcomm may be one of the most promising opportunities available.

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