Top 6 AI Mutual Funds to Consider in 2025

AI is changing how businesses operate, and that’s driving real opportunity in the markets. If you’re looking at ways to gain exposure to artificial intelligence without picking individual stocks, mutual funds focused on AI and tech innovation might offer the balance of professional management and sector growth potential. 

Check out my list of top AI penny stocks these mutual funds aren’t buying!

Here are six AI-focused mutual funds worth watching in 2025, each offering different strategies, risk profiles, and levels of exposure to AI-related companies.

Top AI Mutual Funds for 2025

Ticker	Fund Name	Expense Ratio	YTD Return
PRGTX	T. Rowe Price Global Technology Fund	0.92%	16.40%
FSPTX	Fidelity Select Technology Portfolio	0.68%	13.44%
FKDNX	Franklin DynaTech Fund	0.79%	13.67%
SLMCX	Columbia Seligman Communications & Information	1.18%	15.55%
FTQGX	Fidelity Advisor Technology Fund	0.61%	6.52%
GITAX	Goldman Sachs Tech Opportunities Fund	1.17%	11.93%

Before you send in your orders, take note: I have NO plans to trade these funds unless they fit my preferred setups. This is only a watchlist.

The best traders watch more than they trade. That’s what I’m trying to model here. Pay attention to the work that goes in, not the picks that come out.

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1. T. Rowe Price Global Technology Fund (MUTF: PRGTX)

PRGTX offers targeted exposure to global technology companies, including many with deep roots in AI infrastructure and cloud computing. With over 60% of assets tied to leaders like Nvidia Corp, Microsoft, and Broadcom, this fund leans heavily into both semiconductors and software systems powering AI. Its global allocation includes key international players like Taiwan Semiconductor and ASML, giving traders access to high-demand AI supply chain components.

In my experience teaching newer traders, I emphasize the importance of understanding what’s under the hood. This fund holds a tight group of dominant companies benefiting from AI-driven demand for data centers and processing power. While its 5-year returns lag some tech peers, PRGTX has shown strength in periods of AI-led momentum, especially in 2023 and Q1 2025.

2. Fidelity Select Technology Portfolio (MUTF: FSPTX)

FSPTX is one of the most concentrated tech mutual funds available, with over 95% in tech stocks and roughly a quarter of the portfolio in Nvidia. It’s designed for traders who want high exposure to semiconductors, systems, and platforms central to AI growth. The fund also includes Microsoft, ServiceNow, and Marvell Technology—companies deeply embedded in enterprise AI and edge computing.

The price-to-earnings ratio is low relative to category averages, which can be attractive if you’re watching for value within high-growth sectors. FSPTX is aggressive, but that’s the trade-off for the potential gains. I tell traders this often: concentration boosts upside, but it also magnifies risk. When tech gets hit, FSPTX takes it on the chin—but it also tends to recover faster when momentum returns.

3. Franklin DynaTech Fund (MUTF: FKDNX)

FKDNX focuses on innovation leaders across sectors, not just traditional tech. About 51% of the fund is in technology, but it also taps into finance, healthcare, and industrials—sectors increasingly adopting AI tools and platforms. With top holdings in Nvidia, Amazon, Meta, and Shopify, FKDNX blends big-cap AI players with emerging disruptors.

This fund stands out for its multi-sector allocation and relatively low turnover, which appeals to traders who don’t want to manage constant rebalancing. I’ve seen many beginners overlook broader innovation plays when chasing pure AI exposure. FKDNX provides a way to stay exposed to long-term trends while avoiding the whiplash of a narrow portfolio. Its performance has been consistent, and the fund has outpaced its category in 3-year and 5-year returns.

4. Columbia Seligman Communications and Information Fund (MUTF: SLMCX) 

SLMCX has a long history of focusing on communications, semiconductors, and advanced tech infrastructure. With nearly 71% allocated to technology and over 13% to communications, this fund takes a hybrid approach by blending AI hardware names with digital service platforms. Holdings include Nvidia, Alphabet, Lam Research, and Bloom Energy.

SLMCX is one of the more aggressive options on this list, both in terms of sector concentration and volatility. The fund’s beta over the last five years sits above 1.3, which means higher swings during both bull and bear cycles. I’ve taught for years that high volatility isn’t always bad—what matters is if the potential upside justifies the risk. If you’re trading trends or looking for high beta names in your research, SLMCX is worth tracking.

5. Fidelity Advisor Technology Fund (MUTF: FTQGX)

FTQGX is a more recently launched mutual fund with a focused approach—only 30 to 80 holdings at a time, mostly in U.S.-based names. Top holdings include Meta Platforms, Nvidia, and DraftKings, giving it a mix of social data platforms, AI semiconductors, and digital consumer tech. The fund’s lower technology weight (under 40%) suggests a diversified growth strategy with a bias toward AI-influenced sectors.

This is a fund I’d consider for traders looking to reduce volatility without stepping away from AI growth potential. The expense ratio is competitive at 0.61%, and while 2025 YTD performance is lighter than some peers, FTQGX has posted strong 3-year average returns. It’s not the flashiest pick, but it’s built for traders who want exposure with better risk balance.

6. Goldman Sachs Technology Opportunities Fund (MUTF: GITAX)

GITAX aims to capture gains from broad technology trends, with an emphasis on software, semiconductors, and digital infrastructure. The fund holds over 70% in tech and features Nvidia, Microsoft, and Meta among its largest positions. With international exposure and a focus on future innovation, GITAX can serve as a high-growth option for traders tracking long-term AI integration.

The fund’s active management style allows it to adapt more quickly than index funds when sector rotations happen. One thing I teach in every session: adaptability is critical. Funds like GITAX benefit from that flexibility, especially when tech volatility spikes. The downside is the 1.17% expense ratio, but for traders focused on momentum and breakout sectors, that cost may be justified.

Historical Performance Highlights

Evaluating AI mutual funds means looking beyond just headline returns. You’ve got to consider how the fund performed in down markets, whether it outpaced peers over 5 and 10 years, and what drove those results. I teach traders to always assess whether returns came from concentrated exposure to names like Nvidia, or from diversified positioning that can handle sector rotation.

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5-Year and 10-Year Returns of Leading AI Funds

PRGTX and FKDNX show consistent 3-year and 5-year gains, largely fueled by mega-cap tech holdings. SLMCX leads in 5-year returns at over 20%, thanks to strong exposure to semiconductors and AI software companies. FSPTX has high returns as well, but its risk is tied to a top-heavy portfolio with over 25% in NVDA alone. When a single stock moves the needle that much, it’s both an opportunity and a risk.

Volatility and Drawdown Analysis

Most AI mutual funds have higher-than-average beta, with SLMCX and FSPTX exceeding 1.25. During the 2022 tech pullback, funds like PRGTX and FSPTX dropped faster than broader indexes. This is what traders need to prepare for: AI and tech funds don’t correct gently. That said, recovery has been strong for funds with exposure to semiconductors and infrastructure names. In my trading classes, I stress the need to match your strategy with your risk tolerance. These funds demand a plan.

Comparison with AI-Focused ETFs

AI ETFs are often more concentrated and rules-based, with heavy allocations to Nvidia, AMD, and Microsoft. Mutual funds, by contrast, allow for more flexibility in rebalancing and trimming high-exposure positions during volatility. For newer traders, mutual funds can help smooth out some of the sharp corrections ETFs may face. But if you’re looking for faster moves and can handle the swings, ETFs might better fit a short-term strategy.

Key Holdings in AI Mutual Funds

AI mutual funds tend to revolve around a handful of dominant companies that provide software, systems, or infrastructure for AI deployment.

Microsoft, Nvidia, Alphabet

Nvidia (NVDA) is the single most common holding across these funds, reflecting its role in powering AI data centers and training models. Microsoft plays both sides—offering Azure infrastructure and deploying AI in business tools. Alphabet (GOOG, GOOGL) brings search, cloud, and autonomous tech into the mix. These companies are foundational AI assets in most portfolios.

Emerging AI Players like ServiceNow and Shopify

ServiceNow and Shopify are examples of next-tier companies using AI to streamline enterprise systems and customer operations. Funds like FKDNX and FSPTX include them for their growth potential, despite smaller market caps. I often remind traders: don’t just chase the leaders—watch the companies building tools for the leaders.

Diversification Beyond Tech (Healthcare, Industrial AI)

Funds like FKDNX also branch out into sectors like healthcare, where AI is improving diagnostics, or into industrials using automation. This diversification can reduce drawdown risk. It’s something I look for in my research: is a fund all-in on one angle, or building around the AI trend across multiple industries?

AI Mutual Fund Strategies and Investment Approaches

AI mutual funds follow different strategies depending on how the fund manager interprets the growth potential of artificial intelligence across sectors. Some focus purely on tech innovators building AI products and systems, while others include companies that are using AI to optimize operations in industries like finance, healthcare, and logistics. These strategies often vary between U.S.-focused and globally diversified portfolios, with differing exposures to foreign securities and market trends.

For investors and advisors making long-term allocation decisions, it’s important to understand whether a fund is aiming for direct AI innovation exposure or broader participation in AI adoption. Some funds prioritize liquidity and shorter-term gains from fast-moving names, while others lean into steadier performers with wider business models. The strategy behind a fund directly impacts fees, turnover rates, and how managers react to market shifts.

I always teach traders to evaluate whether a fund’s strategy fits their goals and risk tolerance before acting on any news or expert opinions. It’s not just about the company names in the portfolio—it’s about what the fund is trying to accomplish and how that aligns with your investment decisions. If you don’t understand the logic behind the strategy, you’re guessing, not trading.

Pure AI Innovation Exposure

Some funds, like FSPTX and SLMCX, focus heavily on companies creating AI products—chips, software, and services. These are aggressive, often volatile, but have the most potential when AI demand surges. They rely on gains from innovation, not defensive positioning.

Broader Technology with AI Allocation

Funds like PRGTX or FKDNX mix traditional tech leaders with newer AI adopters. This gives more stability, which can help traders who want exposure to growth but need more risk control. This is the style I recommend to traders who can’t stomach 10% drawdowns overnight.

Global vs. U.S. Focused Portfolios

PRGTX and GITAX have significant foreign exposure, including Taiwan Semiconductor and ASML. That global allocation adds diversification, especially as countries compete to lead in AI. U.S.-focused funds may benefit from stronger regulation and data infrastructure, but international access broadens your reach.

Opportunities and Challenges Associated with AI Mutual Funds

AI mutual funds offer a path to participate in the rapid transformation of business through artificial intelligence, but they’re not without risks. While many funds are positioned to benefit from rising demand in data analytics, automation, and cloud infrastructure, high prices and stretched valuations make timing critical. That’s why I tell traders to avoid chasing hype. If rates change or inflation pressures spike, growth-oriented AI funds can correct sharply, especially when capital flows shift toward safer bonds or cash-based assets.

The opportunity lies in long-term integration of AI across nearly every industry. From advisors using AI-driven tools to improve client outcomes to companies reducing loan default risk with predictive systems, the real value goes beyond just software stocks. But investors should also weigh challenges like changing regulation, global competition, and ethical debates that may influence securities law and company policy.

Potential Growth from AI Adoption Across Industries

AI is being integrated into logistics, manufacturing, medicine, finance, and more. This expansion increases the growth potential for companies powering these systems, especially Nvidia, Microsoft, and emerging software platforms. That demand flows directly into mutual fund performance when positioned correctly.

Risks of Overvaluation in AI Stocks

AI enthusiasm has pushed valuations to extremes, particularly for Nvidia. That’s great when the trend runs, but dangerous when sentiment shifts. If earnings don’t match the hype, these stocks can drop fast. It’s something I constantly warn traders about: never confuse a good story with a good entry.

Impact of Regulation and Ethical Considerations

Governments are increasing oversight of AI usage, especially in defense, surveillance, and employment displacement. Regulatory risks can affect future performance of AI leaders and the funds that hold them. Ethical concerns may also limit adoption in some sectors, affecting demand and pricing power.

Key Takeaways

• AI mutual funds give traders diversified access to fast-growing companies like Nvidia, Microsoft, and Meta.
• Performance is driven by both stock selection and sector allocation—understanding that breakdown is critical.
• Funds differ in strategy: some are pure tech plays, while others spread risk across industries adopting AI.
• Volatility is a factor—traders need a clear risk management plan when allocating to AI-focused mutual funds.

This is a market tailor-made for traders who are prepared. AI stocks thrive on volatility, but it’s up to you to capitalize on it. Stick to your plan, manage your risk, and don’t let FOMO drive your decisions.

These opportunities are fast and unpredictable, but with the right strategy, you can make them work for you.

If you want to know what I’m looking for—check out my free webinar here!

Frequently Asked Questions

What Role Do Experts Play in Choosing AI Mutual Fund Investments?

Experts provide valuable insight into AI mutual funds by analyzing company fundamentals, sector trends, and macroeconomic conditions that influence performance. Their advice can help investors avoid common mistakes and weigh the real costs of investing, especially in actively managed funds with higher fees. I always remind traders to use expert analysis as a tool, not a crutch—your investing decisions should still be based on your own rules and risk tolerance.

Are AI Mutual Funds a Good Fit for Long-Term Investing?

AI mutual funds can align with long-term investing goals if the fund’s strategy is consistent with broader technology adoption trends and sustained company earnings growth. Still, costs like expense ratios and tax impact should be evaluated carefully before committing capital. I teach traders that even growth-focused investments need structure—chasing performance without a plan rarely ends well.

What Costs Should Be Considered When Investing in AI Mutual Funds?

Beyond the expense ratio, investors should factor in advisory fees, fund turnover-related costs, and potential tax implications from active management. These hidden costs can chip away at long-term investments if you’re not paying attention. That’s why I always stress the importance of reading fund documents and seeking advice from experienced sources before making any financial commitment.