The artificial intelligence (AI) revolution has driven a massive expansion in the semiconductor industry, with Nvidia often grabbing the spotlight. Over the past five years, Nvidia’s stock has soared by more than 1,200%, primarily powered by its dominance in supplying GPUs for AI and machine learning workloads in data centers. As AI technologies mature and diversify, however, the next phase of growth may come from less-heralded competitors addressing new, specialized market demands.

As advancements in generative AI, autonomous devices, and edge computing push computational requirements to new limits, a diverse set of chipmakers is developing solutions beyond traditional processors. Qualcomm, Marvell Technology, and NXP Semiconductors are three such companies building the hardware infrastructure to power AI’s next act. This article explores how these underappreciated players could deliver substantial growth through 2030.

1. Qualcomm: Catalyzing AI in Mobile and Consumer Devices

For years, major AI models such as OpenAI’s GPT series and Google’s Gemini have primarily operated on cloud servers, requiring immense computational resources. While a select few high-end devices, like Apple’s iPhones and Microsoft’s latest Surface laptops, have begun integrating AI-capable processors, mass-market mobile AI is still in its early stages.

Qualcomm (NASDAQ: QCOM) stands at the forefront of this transition, leveraging its deep expertise in mobile chipsets. Its Snapdragon 8 Gen 3 platform, launched in late 2023, was the industry’s first mobile processor purpose-built for generative AI. Since its debut, Qualcomm’s AI hardware capabilities have been rapidly adopted by leading smartphone manufacturers, with Samsung, Xiaomi, and OnePlus integrating Snapdragon chips to offer on-device generative AI features such as real-time translation, AI camera enhancements, and digital assistants.

With Qualcomm’s Snapdragon X Elite and Snapdragon X Plus powering upcoming AI PCs, and Microsoft electing to use Qualcomm’s latest chips in its Copilot+ AI laptop portfolio, the company’s silicon is set to become synonymous with affordable, powerful AI everywhere. In fiscal 2024, Qualcomm’s revenues reached $36.3 billion, with AI-driven chip shipments expected to double by 2026, according to company projections.

As AI workloads shift closer to end users—demanding privacy, speed, and cost-savings—Qualcomm is poised to capture growth in the rapidly expanding mobile and edge AI processor markets, currently forecast by IDC to rise to $67 billion by 2028.

2. Marvell Technology: Powering the Backbone of AI Data Centers

While the excitement around AI often centers on processing units (GPUs and NPUs), the backbone of next-generation AI data centers extends far beyond chips. Marvell Technology (NASDAQ: MRVL) is uniquely positioned as a provider of advanced interconnects, memory accelerators, chiplets, and custom silicon that collectively enable the ultra-fast, energy-efficient AI server farms underpinning large-scale model training and inference.

Marvell’s Compute Express Link (CXL) products allow hyperscale data centers to expand memory bandwidth and lower operating costs by connecting pools of DRAM directly to processors—maximizing each server’s useful life. In 2025, Marvell announced the expansion of its Bravera and CXL portfolio, targeting growing demand from major customers like AWS, Microsoft, and Google Cloud, all of whom are building data centers purpose-built for AI workloads.

Industry analysts at Technavio project the global AI data center market will grow at a compound annual rate of nearly 29% through 2029, putting Marvell at the core of an explosive infrastructure upgrade cycle. The company’s fiscal 2025 revenue hit $6.4 billion, with its data center revenue segment up 35% year-over-year, outpacing broader semiconductor market growth. Despite some volatility, Wall Street remains bullish, with the consensus price target for MRVL stock reflecting nearly 30% upside potential from current levels.

3. NXP Semiconductors: Enabling AI at the Edge

As AI’s utility expands beyond big cloud infrastructure into real-world applications—such as autonomous vehicles, smart factories, healthcare wearables, and logistics—customized edge computing silicon is in high demand. NXP Semiconductors (NASDAQ: NXPI) focuses precisely on these areas, targeting industries where reliability and efficiency are more important than brute computing power.

NXP’s i.MX RT700 neural processors and eIQ Neutron AI/ML accelerators are being embedded into everything from wearable ECG monitors and fitness devices to industrial robotics and advanced driver assistance systems (ADAS). In early 2025, the company announced partnerships with BMW for autonomous vehicle systems and with Siemens for smart factory automation, consolidating its lead in embedded AI.

NXP’s diversified portfolio—spanning automotive, industrial automation, healthcare, and IoT—positions it as a leading provider of AI hardware outside the data center. Analysts forecast NXP’s revenue will grow from $12.4 billion in 2024 to nearly $15 billion by 2027, with earnings growth supported by both operational margin expansion and robust order inflows. With a current price-to-earnings ratio of just 16 (well below the semiconductor sector average), NXP offers a rare value opportunity, while also paying a dividend yield near 1.8%.

Investor Takeaway: The Next AI Winners May Be Hiding in Plain Sight

The AI chip race is entering a new phase, one where specialized needs—ranging from mobile and consumer AI to high-bandwidth data centers and rugged edge computing—require a broad set of hardware pioneers. Qualcomm, Marvell Technology, and NXP Semiconductors are well positioned to benefit from these trends, even as a select group of mega-cap competitors dominate headlines.

As capital pours into new AI hardware, investor attention is likely to extend beyond the current favorites. Those with the foresight to invest in these “AI enablers”—the companies creating the foundation for AI adoption at scale—could be well rewarded in the next five years. Investors should perform their due diligence but may want to give these names a spot on their AI watchlist.