From Wall Street to Your Smartphone: The Growth of AI Trading Apps in 2025

Before online trading took off in the 90s, traders like you had to call brokers to place trades. The entire process was tedious and costly. It was also marred by transparency since traders couldn’t countercheck asset prices in real time.  Then online trading came, and the rest is history. Now, you can trade with a simple gadget small enough to fit in your pocket – your smartphone.

To add to the upside, you can leverage the power of AI through powerful mobile-compatible trading apps. Most of these tools are free, and many of the premier products charge pocket-friendly fees. If you’re yet to be familiar with these power-packed modern systems, the comparison of apps for AI trading by InvestingGuide can help. That aside, here’s an overview of AI trading apps.

Wall Street’s AI Foundations

AI trading started way before the prevalence of computers. Its roots begin with Richard Donchian, a commodities and futures trader who formulated a list of rules for automated trading in 1949. This remarkable individual’s rules were centered on breakout trading. For instance, one of his rules was, in simple terms, to buy when the price exceeds the high from the previous X number of days.

After Donchian planted the idea, expert systems designed to automate tasks such as credit scoring started popping up. In the 60s and 70s, solutions like the first electronic trading platform, NASDAQ, came into existence. Then, between 1990 and 2010, major institutional traders like banks developed branded algorithmic strategies, and high-frequency trading gained traction.

Also, the 2000s saw the early adoption of self-learning trading models, thanks to advancing technology and increased computing power. These systems gradually replaced rule-based trading and are now the backbone of popular AI trading models powered by machine learning and other technologies

2025 Landscape of AI Trading Apps

Unlike in the past, where automated trading systems were exclusively accessible to institutional and high-net-worth traders, AI-powered apps can be leveraged by everyone in 2025. Many popular service providers allow users to enjoy the perks of AI-powered trading, such as eToro, Pepperstone, and Saxo.

The AI trading apps you have access to as a modern trader can do a lot. For instance, they can recommend buy/sell opportunities based on aspects like historical prices, trends, and breakouts. They can also monitor assets in your portfolio and rebalance whenever necessary. Finally, many allow their users to build bots without coding skills – users can use simple English to key in instructions.

What Makes These Apps So Powerful?

AI trading apps are on a new level; they’re more powerful, intuitive, and extremely easy to use. Their power comes from multiple elements, with cutting-edge infrastructure on the frontline. Large language models, neural-symbolic systems, and reinforcement learning agents are at the core of the best AI trading apps.

Modern AI-powered trading apps are also incredibly powerful due to their ability to process vast amounts of data from different modalities. They are designed to handle massive data volumes within less than a second, from economic reports and earnings data to news headlines and price action.

Not to forget, today’s AI-driven trading apps don’t use the same strategies for all investors. These tools are designed with hyper-personalization in mind. They learn everything about you as a unique trader, from your trading history and obvious preferences to your risk appetite and behavioral patterns. That enables them to provide tailored alerts, recommendations, and more.

Modern AI systems are also better than their older counterparts because they leverage a concept known as Explainable AI (XAI). This technology enables them to explain their actions, decisions, and predictions in a way that you, a human, can understand. That is crucial in building confidence and making seamless human oversight possible.

Role of Human Judgment in an AI Era

AI trading apps might have dazzling capabilities, but they can’t operate without human judgment and oversight for the following reason:

No real-world context

AI can’t understand real-world context like you, a human trader. For instance, if Apple were to postpone the release of a new product to align with a significant event, AI might flag the phrases “Apple” and “delays,” interpret that as a negative signal, and recommend sell orders. You, on the other hand, can grasp real-world context and causal relationships and adjust your portfolio accordingly.

Decision framing

AI-powered trading apps are terrific at pattern recognition but don’t perform so well when it comes to decision framing. For example, if the US Federal Reserve announces that interest rates won’t change, this tool might not understand why or use the Fed’s tone to draw plausible interpretations. That is why you must keep a close watch on the AI app you choose to trade with and modify, reject, or approve trades based on your understanding of crucial events and data.

Black swan events

AI models learn from historical data and patterns. Most assume that future outcomes will mirror current ones and don’t factor in unprecedented happenings, otherwise known as black swan events. If two nuclear countries start a full-scale cyberwar that affects financial institutions today, AI will likely keep trading as if nothing of significance happened. This tool needs you to read between the lines and make decisions that align with the possible repercussions of a black swan event.

Ethics and accountability

An AI trading app is incapable of assessing ethics and accountability. This tool will invest in any asset without factoring in the ethical ramifications, as long as its deductions are labeled as likely to generate returns. For instance, an AI trading system can buy stocks from a company accused of polluting water bodies with toxic waste, despite this move being highly likely to come with an ethical cost. You must monitor it closely and ensure that trades match top priorities like ESG principles.

What’s Next for AI Trading in 2025 and Beyond?

AI trading apps are far from cresting – they keep getting better by the day. Soon, you’ll have access to next-gen solutions that integrate seamlessly with everything from your favorite budgeting tools to your bank account and insurance data. They will be able to adjust every trade based on crucial aspects like your job security and savings balance.

The next wave of AI-powered trading systems will likely be able to leverage more than one AI at a time. For instance, you’ll have access to apps with multiple agents for managing risk exposure, forecasting price movements, etc. They’ll all collaborate to ensure your portfolio is in optimum condition. Future apps might also be tailored to use biometric feedback from wearables to detect emotional upheaval and suggest solutions like breathing exercises during trading sessions.