How AI Investing Trends Are Shaping the Future
Table of Contents
In recent years, artificial intelligence (AI) has had a dramatic impact on modern investing. AI tools and systems have begun to impact not only how institutional investors operate and make decisions, but also how many everyday individual investors monitor their portfolios, spot new opportunities, and make decisions. From AI-powered robo-advisors to machine learning platforms that adjust portfolios in real time, AI is increasingly embedded in the investment ecosystem.
What does the future of AI in finance hold? Analyzing AI investing trends offers insight into the opportunities — and challenges — that may lie ahead for both institutional and individual investors.
Key Points
• AI investing uses algorithms and machine learning to analyze data, identify patterns, and predict potential trends.
• AI systems process vast amounts of data faster and more objectively than humans.
• Algorithms may be used to efficiently construct, monitor, and rebalance investment portfolios.
• Robo-advisors are gaining popularity, especially among younger investors, due to low costs and automation.
• Future opportunities include models that more deeply integrate AI tools and human advisors, but challenges like data accuracy and ethical governance persist.
The Rise of AI Investing
Artificial intelligence isn’t as new to finance as it might seem. The foundations of AI —- such as automation and algorithm-driven processes —- have quietly shaped the financial markets over the last several decades.
One of the earliest investment applications emerged in the 1980s with algorithmic trading, in which computers automatically executed trades based on certain market data. In the 1990s, finance shifted further towards data-driven AI, as researchers developed algorithms capable of recognizing patterns in datasets. This laid the groundwork for modern machine learning, which is when computer systems are able to learn and adapt without following explicit instructions.[1]
By 2011, deep learning — which uses neural networks to interpret complex data and tackle intricate problems — pushed AI further into finance. Investment firms began testing algorithmic trading systems powered by AI. In 2018, BlackRock established an AI lab to explore the use of machine learning, data science, and natural language processing (which uses machine learning to enable computers to understand and communicate with human language).[2]
Today, AI technologies are advanced enough for investment managers to create everything from AI-informed funds to fully automated, AI-directed funds. Here’s a look at some of the most common applications of AI in investing:
• Algorithmic and high-frequency trading
• Predictive analytics and market forecasting
• Risk management and fraud detection
• AI-driven robo-advisors
Key AI Investing Trends to Watch in 2025
As AI becomes more widespread in investing, it’s important to consider what changes may be on the horizon. Here are some of the top AI investing trends to watch in 2025 and beyond.
Mainstream Adoption of Robo-Advisors
Robo-advisors challenge the traditional advisory model by using algorithms rather than human insight to construct, monitor, and rebalance portfolios. While the number of investors who rely on robo-advisors to invest in stocks is still relatively small, research indicates that adoption may be growing, especially among younger investors.
Here’s how robo-advisor use compares across generations, according to a 2025 investment trends report from the data analytics firm YouGov:[3]
|
Percentage of Investors Who Use Robo-Advisors |
|
|---|---|
| Gen Z | 14% |
| Millennials | 20% |
| Gen X | 14% |
| Baby Boomers | 6% |
According to Fortune Business Insights, the global robo-advisor market is projected to grow from $10.86 billion in 2025 to $69.32 billion by 2032.[4] This suggests that significantly more investors will seek low-cost, automated investment advice online in the coming years.
Learn more: What Is a Robo-Advisor? How Do They Work?
AI-Powered Stock Screening and Market Signals
AI stock screeners can do what the typical investor can’t: process vast amounts of data almost instantaneously to detect patterns and potential market signals.
Powered by machine learning and natural language processing, these tools analyze market data, financial reports, and even investor sentiment, allowing them to conduct a more comprehensive analysis of the market. AI stock screeners may spot potential opportunities to invest in based on both technical and fundamental analysis indicators, and make estimated assumptions about which way a stock may move next.
Of course, no tool can predict investing outcomes, just as no tool can guarantee profits or eliminate risk. An AI stock screener can be a useful co-pilot, however, and may help investors make more informed choices. As AI screeners continue to evolve and become more sophisticated, more investors may turn to these tools to try to identify potentially favorable stocks.
Recommended: Top AI Stocks to Invest In: 2025 Guide
Growth in Thematic and Tech-Driven Investing
Thematic investing refers to choosing investments based on big ideas or trends — such as clean energy, AI, robotics, ESG (environmental, social, and governance), or biotech — rather than traditional factors like sector or geography.
AI helps enable thematic investing by identifying which themes appear to be gaining momentum early. For example, AI tools can help monitor policy changes, patent filings, corporate R&D disclosures, and even scientific publications to see which technologies may be poised for growth. AI can also help model the possible economic impact of emerging industries, estimating growth trajectories, risk factors, and competition.
With all of these options, it’s important to remember that AI is not a perfect investing tool — there’s no such thing. AI’s information is only as useful as the data it processes. With AI’s ability to analyze and model complex data, however, investors may continue to turn to AI thematic investing in 2025 and beyond.
Personalized Portfolios Using Machine Learning
Customization may be a helpful benefit of AI-enabled investing. Rather than having fixed portfolios or only a few models (such as “conservative,” “balanced,” or “aggressive”), AI-powered platforms are increasingly able to tailor portfolios to an investor’s individual goals, risk tolerance, time horizon, preferences, and liquidity needs.
Robo-advisors are an example of this in action. When you join a robo-advisor platform, you’ll typically complete a questionnaire, which is designed to assess your risk tolerance, goals, and investing preferences. If you’re managing investments through an AI-powered robo-advisor, the platform’s algorithm uses machine learning to analyze your responses and make recommendations that are tailored to your situation.
Recommended: A Beginner’s Guide to the Stock Market
Real-Time Risk Monitoring and Portfolio Rebalancing
Markets move quickly —- news, geopolitics, supply chains, inflation, and regulatory decisions can all spark unexpected volatility in the market. AI tools are increasingly being used to monitor risk in real time and help rebalance portfolios more proactively.
AI can quickly analyze historical performance, market sentiment, and price movements to model potential risks, which may help investors stay ahead of sudden changes. Automated rebalancing, a feature of many robo-advisors, helps to keep portfolios aligned with an investor’s target allocation by recommending or executing trades as markets shift.
Most Popular AI Investing Tools and Platforms
The AI investing market is expanding rapidly, with new tools and platforms emerging all the time. Below is an overview of the different kinds of AI-powered tools and platforms that are currently available to assist investors. (While SoFi offers robo investing, it does not currently offer members tax-loss harvesting services or AI-specific analysis tools.)
• Robo-advisors: One way to access artificial intelligence in the investment sphere is through a robot advisor that incorporates AI. These tools leverage machine learning to help improve risk management, portfolio rebalancing, and tax-loss harvesting. One advantage is their relatively low cost and low minimum investment requirements.
• AI-powered screening platforms: If you prefer active trading, AI stock screeners can help you with your investment decisions. Some screeners are stand-alone applications, while others may be incorporated into your brokerage account as a core feature.
• Sentiment analysis tools: AI-powered sentiment analysis sites and tools analyze news and social media posts to gauge investor sentiment. These tools leverage natural language processing to go beyond classifying articles or posts as merely positive or negative, but considers context and nuance in communications. This allows them to help effectively monitor trends, “buzz,” or shifts in perception.
• Thematic discovery engines: Many investment platforms enable thematic investing powered by AI. These engines are able to mine corporate communications (e.g., earnings reports, regulatory filings, and other public information) for common keywords supporting a theme. This may uncover a web of interconnected companies, allowing investors to consider interests beyond traditional market sectors or the well-known industry leaders.
Recommended: How to Invest Using AI Tools
How AI Is Reshaping Investor Behavior
Investors are becoming more receptive to AI in their financial lives. According to a March 2025 Ipsos/TD Bank survey, 43% of Americans are comfortable with a hybrid approach that combines AI with human financial advisors, while 44% are open to using AI to manage investments.[5]
AI’s appeal lies largely in its speed, cost-efficiency, and convenience. Many investors now rely on digital platforms and apps to manage portfolios and gather information. Globally, 77% of investors have at least a part of their portfolio on a digital platform or app, while nearly 75% source investment information through digital means, according to Amundi’s 2025 Digital Investment report.[6] These numbers are likely to climb as AI becomes more integrated into wealth management.
The Future of AI in Finance
As AI’s role in investing deepens, the coming years may bring opportunities but also challenges.
While AI has numerous benefits, there are also potential risks involved in using AI to make investment decisions. One ongoing concern is that the reliability of AI tools depends heavily on the accuracy of their data. Skewed or incorrect inputs or algorithmic bias can undermine recommendations and potentially put investors at risk. The lack of transparency about how AI models operate and how customer data is stored and used are also ongoing concerns.
Moving forward, success will likely come from balancing automated investing and human judgment, ensuring transparency, and managing risks responsibly. Here’s a look at how AI in investing may play out over the next several years:
• Deeper integration and hybrid models: The most successful AI strategies will likely be human advisors and AI systems working together. In a hybrid approach, AI handles data processing and monitoring, while humans continue to bring judgment, ethics, and clients’ unique needs into investment decisions.
• Transparency and ethical governance: Financial institutions that address bias and adopt transparent and fair AI practices may gain investor confidence and trust.
• Shift to customer-facing applications: While much of the investment in AI has been concentrated on foundational systems, such as hardware and AI models, many institutions are now focusing more on AI-powered products and services to enhance the retail investor experience.
The Takeaway
AI investing trends aren’t a passing fad — they represent a fundamental shift in how many inventors (both institutions and individuals) approach investing. AI systems and tools are now widely used to help improve efficiency, lower costs, and potentially increase investment returns.
That said, AI is still best thought of as a supporting tool, not a replacement for human judgement. While it can help investors of all experience levels make more informed decisions, AI isn’t a magic wand. Understanding risk, knowing your goals, keeping an eye on fees, and being skeptical of overhyped promises remain essential.
As adoption of AI grows, investors who learn how to use this technology responsibly — balancing the benefits with the risks — may be better positioned to navigate markets and build long-term wealth.
Ready to start investing for your goals, but want some help? You might want to consider opening an automated investing account with SoFi. With SoFi Invest® automated investing, we provide a short questionnaire to learn about your goals and risk tolerance. Based on your replies, we then suggest a couple of portfolio options with a different mix of ETFs that might suit you.
FAQ
What is the biggest change AI brings to investing?
The biggest change AI brings to investing is speed and precision in decision-making. Traditional methods rely heavily on manual analysis, but AI can process vast amounts of financial data, news, and market trends in real time. This allows investors to spot potential opportunities or risks much faster than before. While no AI tool can predict outcomes or guarantee results, this technology helps make investing more data-driven, efficient, and accessible.
Will AI replace human financial advisors?
AI is unlikely to fully replace human financial advisors but may instead complement their roles. While AI excels at analyzing data, spotting trends, and automating tasks like portfolio rebalancing, it lacks the human qualities needed for personalized advice, empathy, and building trust. Advisors provide guidance that goes beyond numbers, such as understanding life goals, emotions, and unique circumstances. AI allows advisors to focus on relationship-building and strategic planning rather than routine calculations.
How does AI help with managing investment risk?
AI may help manage investment risk by continuously analyzing market conditions, company performance, and global events. AI may also help detect early warning signals, such as unusual trading patterns or shifts in economic indicators, in real time. AI also uses predictive models to stress-test portfolios against different scenarios, which may help identify potential downturns. That said, it’s important to remember that AI, nor any tool, can definitively predict how assets will perform.
How is AI impacting new investors?
AI can help make investing more accessible and less intimidating for beginners. By automating portfolio creation, rebalancing, and risk assessments, AI may also allow beginners to start investing with more confidence. Ultimately, AI reduces barriers to entry, potentially helping new investors learn more about their options and strategies.
What are the main benefits of AI in investing?
The main benefits of AI in investing include efficiency, accuracy, and accessibility. AI can process massive datasets quickly, providing insights that would take humans weeks or months to uncover. By reducing emotional bias and relying on data-driven analysis, AI may also improve accuracy, and potentially improve portfolio performance. For individuals, AI makes professional-level investing tools available at lower costs, often through robo-advisors or apps. It’s important to keep in mind, however, that no AI tool can predict outcomes or guarantee results.
About the author
Article Sources
- Medium. AI in the 1980s and 1990s: The Decades That Changed Everything.
- Binance. Biggest Asset Manager Company Blackrock.
- YouGov. US investment trends report 2025.
- Fortune Business Insights. Robo Advisory Market Size, Share & Industry Analysis.
- Ipsos. Majority of Americans (89%) Are Comfortable Adapting to New Technology in Daily Life.
- Amundi. Retail investors go digital while confirming the key role of professional advice.
Photo credit: iStock/Don Wu
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