Fidelity's AI Stocks: Top Picks for 2026 Investment Growth

The artificial intelligence revolution is undeniably upon us, manifesting as a profound transformation across industries that shows no signs of decelerating. This unprecedented spending surge on advanced AI chatbots and agents has instigated a frenetic refresh cycle among enterprise and cloud data center providers. Older server architectures, traditionally powered by CPUs, are rapidly being supplanted by next-generation racks equipped with specialized chips and memory meticulously engineered for the demanding workloads of AI.

We haven't witnessed such a pervasive level of excitement, nor such a colossal retooling of information technology budgets, since the nascent days of the Internet. While only time will truly unveil whether AI's long-term impact will eclipse that of the Internet, corporations globally are making substantial bets that it will. Hyperscalers, the planet's largest data center operators, are channeling hundreds of billions into acquiring the foundational "picks and shovels" essential for the rigorous development and deployment of sophisticated AI models.

The AI Revolution: A Paradigm Shift in Global Investment

The current technological paradigm shift driven by artificial intelligence evokes strong parallels with the dawn of the internet age, yet it exhibits distinct characteristics, particularly in its financial underpinnings. Fidelity Investments, in a recent research brief, highlighted the extraordinary capital expenditure by industry giants such as Amazon's AWS, Microsoft's Azure, Google Cloud, and Meta Platforms. Their collective spending is projected to skyrocket from approximately $100 billion in 2023 to over $300 billion by 2025, with forecasts suggesting it could exceed half a trillion dollars within the ensuing years. This monumental investment underscores a deep-seated conviction in AI's transformative potential, attracting not only institutional behemoths but also a broad spectrum of individual investors who have actively bid up top AI stocks in anticipation of future profitability.

Fidelity's Analytical Framework: Identifying AI Leaders

Hyperscalers: Translating Infrastructure into Profitability

A recurring critique leveled against the large-cap tech hyperscalers has revolved around concerns that their immense and rapid pace of investment might be overly optimistic, potentially taking years, if ever, for AI-related sales and profits to justify the staggering costs. However, emerging evidence suggests these technology giants are beginning to realize tangible benefits. Priyanshu Bakshi, a portfolio manager for Fidelity Select Communication Services Portfolio (FBMPX), maintains that these companies, despite their significant valuation, are not overvalued. He observes that the "Mag 7" — NVIDIA, Microsoft, Apple, Alphabet, Amazon, Meta, and Tesla — are consistently delivering earnings growth in the mid-20% range, significantly outpacing the mid-single-digit growth observed across the broader S&P 500. Bakshi points to Alphabet and Meta, which constitute nearly half of his portfolio, as prime examples. These two companies collectively generate $500 billion in digital ad sales, and AI-driven tools capable of delivering more relevant advertisements are already beginning to translate into enhanced sales and potentially higher ad rates, laying a robust foundation for future expansion. Alphabet is targeting capital expenditures of $91 billion to $93 billion this year, while Meta Platforms plans investments between $70 billion and $72 billion, signaling continued commitment to AI infrastructure.

The Unassailable Foundation: AI Chip Innovators

Nvidia's trajectory since the launch of ChatGPT in 2022 has been nothing short of meteoric, with sales surging from $27 billion to an impressive $187 billion over the last twelve months. This success is intrinsically linked to its graphic processing units (GPUs), which demonstrate unparalleled efficiency in handling the complex demands of AI training and inference compared to traditional CPUs. Nvidia's formidable lineup, including the H100 and H200 chips based on its Hopper architecture, and more recently, the B100, B200, and GB200 Superchip utilizing the Blackwell architecture, have become the industry's gold standard for AI speed and efficiency. Looking ahead, the company's next-generation AI chips, built on its Vera Rubin platform, are slated for release in 2026. These advanced components are predominantly manufactured by Taiwan Semiconductor Manufacturing Company (TSMC), the world's largest contract chip maker, which operates fabs globally, including in Taiwan and a growing facility in Arizona. Chris Lin, managing Fidelity OTC, posits that despite widespread hype, the ultimate potential of AI remains widely underestimated by investors. He notes that Nvidia is his fund's largest holding, comprising 15.7% of its $35 billion portfolio, while TSMC ranks ninth, accounting for 2.8%. Lin succinctly states, "AI requires computation, and these two companies are the main providers of it."

Expanding Horizons: Beyond Core AI Chips

While Nvidia holds a commanding position, the expansive AI buildout is simultaneously fueling demand for a broader ecosystem of chipmakers. This includes companies developing custom XPUs specifically designed for hyperscaler networks and those innovating in larger, superfast memory solutions. Adam Benjamin, manager of the Fidelity Select Technology Portfolio (FSPTX), argues that achieving human-like intelligence necessitates far more than just GPUs. He elaborates, "Nvidia isn’t just a chip company anymore. They’re selling full rack-scale systems—essentially complete supercomputers designed to train and run AI models. The next wave of gains is happening at the system level, not the chip level. This is a rack-scale problem now." This shift toward system-level solutions creates significant sales and profit opportunities for companies like Broadcom and Marvell Technology, which specialize in manufacturing XPUs and critical interconnect equipment that orchestrates seamless communication within server networks. Memory manufacturer Micron is also a substantial beneficiary, as AI racks are increasingly populated with advanced, high-bandwidth memory (HBM). Marvell Technology is the fourth-largest holding (5%) in the Select Technology Portfolio, and Micron ranks tenth (2.6%) as of October 31, underscoring their strategic importance in the evolving AI landscape.

Powering AI: The Infrastructure and Energy Imperative

The prodigious power consumption required for AI training and application execution is already placing considerable strain on existing power generation grids. Ensuring sufficient power to support increasingly larger and more powerful data centers presents burgeoning opportunities for ancillary companies, according to Clayton Pfannenstiel, co-manager of the Fidelity Select Industrials Portfolio (FIDRX). Pfannenstiel identifies natural gas turbines as a critical immediate solution to alleviate power bottlenecks. While innovative technologies like small nuclear reactors could benefit players such as Rolls-Royce in the long term, their widespread deployment is not anticipated until the 2030s. "If we need power now, the main source is gas turbines," he asserts. GE Vernova (GEV) is his fourth-largest holding, accounting for 5.4% of the portfolio, and is already reporting higher natural gas turbine orders, prompting management to revise earnings guidance upward. Pfannenstiel also favors Eaton (ETN), a provider of essential electrical systems for data centers, and Trane Technologies (TT), an HVAC giant experiencing rising demand due to increased data center cooling requirements. Trane is the fund's second-largest holding, and Eaton is the eighth. Similarly, Shilpa Mehra, manager of Fidelity Growth Strategies Fund and Fidelity Trend Fund, holds shares in Comfort Systems USA (FIX) and EMCOR Group (EME), reflecting the broad impact of AI on industrial services. The reliance on natural gas turbines, in turn, fuels demand for natural gas, providing a tailwind for midstream players like Energy Transfer (ET), which constructs and operates pipelines and processing facilities, as highlighted by Kristen Dougherty, manager of Fidelity Select Energy Portfolio. Pfannenstiel aptly summarizes the current phase, stating, "AI is still in the build phase. There are a lot of ‘picks and shovels’ companies that could potentially benefit."

AI Market Dynamics: A Measured Ascent, Not a Bubble

The vigorous debate regarding whether the recent surge in AI stock valuations signals the formation of a speculative bubble, akin to the dot-com era, is pervasive. However, Jurrien Timmer, Fidelity's Director of Global Macro, suggests that such comparisons may be misplaced. A crucial distinction lies in the funding mechanisms: unlike the Internet boom, where spending was predominantly fueled by debt, current AI investments are largely financed by the substantial cash reserves of highly profitable corporations like Google. Furthermore, the dot-com bubble witnessed astronomical valuations for companies with minimal to no revenue or earnings. In contrast, Timmer notes, "Valuations today are not even close to what’s been experienced during bubble extremes of the past." For instance, Nvidia's forward Price-to-Earnings (P/E) ratio, a widely accepted valuation metric, stands at approximately 24. This figure is notably moderate when juxtaposed with the exorbitant valuations observed among leading Internet companies at their peak, suggesting a more rational market assessment of AI's underlying value and future earnings potential.

In conclusion, Fidelity's managers present a compelling case for a sustained AI investment narrative, identifying a diverse array of companies poised to capitalize on this transformative technological wave. From the foundational chipmakers and hyperscalers to the critical infrastructure and energy providers, their strategic insights offer a panoramic view of the AI landscape for investors navigating this new economic frontier.