Imagine having an AI agent tell you how much risk you’re willing to take, your retirement goals, when your kids will go to college, and manage your portfolio while you sleep.
The vision of agent trading, where artificial intelligence not only recommends investments but also executes them, is moving from concept to reality. Brokerage firms, startups, and even individual investors are building AI agents that can oversee portfolios and automate investment tasks previously handled by humans.
“Virtually everyone has their own family office and they work there 24 hours a day, seven days a week, whether they’re awake or asleep,” said Devin Ryan, head of financial technology research at Citizens. “This isn’t going to happen in 10 years. It’s going to happen in the next few years.”
Ryan believes these agents will eventually do more than buy and sell securities. He envisions AI continuously managing taxes, cash balances, debt, mortgages, and investment portfolios, all aligned to investors’ financial goals. Fully autonomous investing is still a work in progress, but the race to build it has already begun.
build the future
Rather than trying to build a fully autonomous trading system overnight, many companies are taking a step-by-step approach.
Startup Podium Markets AI is one of the companies building AI specifically for investing. Its assistant, Ivy, analyzes a customer’s portfolio across multiple brokerage accounts and generates recommendations based on the investor’s goals and risk tolerance.
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But it stops short of acting alone. The user decides for himself whether to execute the trade according to the recommendations.
“AI provides the information, but humans make the decisions,” said Dirk Muller Englund, co-founder and CEO of Podium Markets AI. “The average investor should still be largely responsible for the final decision. … We’re going down the path of a permanent AI financial or trading companion that’s always with you.”
Major brokerages are also moving in the same direction. In May, Robinhood introduced a tool that allows third-party AI agents to connect to customer accounts. Meanwhile, brokerage firm Public is developing an in-house AI agent that can automate investment workflows within its platform.
“What this agent age is about… is that it’s not just about being able to research things yourself and formulate your own ideas and trade them the way you’ve always traded them, but it’s becoming increasingly automated and AI agents can actually execute your investment strategy on your behalf,” said Leif Abraham, co-founder and co-CEO of Public.
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Ryan estimated that agent financing could increase transaction volumes by at least 10 times. Retail investors who currently trade about twice a month could eventually be able to trade 20 times a day under the agent model, he said.
“If you can believe it, by the end of next year, the majority of volume-based trading activity on some of these platforms will be driven by agents,” Ryan said.
From ChatGPT to investment agent
While Wall Street has been building agent investing tools, retail investors have spent the past three years testing what general purpose AI can do.
Since ChatGPT went mainstream in late 2022, many investors have been using AI tools like ChatGPT and Anthropic’s Claude to summarize earnings reports, research companies, and generate stock ideas. Results have been mixed, with some users treating AI as a research assistant and others considering it unreliable in making investment decisions.
Obioha Okereke, a 29-year-old Georgia technology consultant and founder of the financial literacy platform College Money Habits, used Claude to build an agent that looks for undervalued stock and options opportunities.
“Essentially, I just asked Claude to act as a hedge fund analyst to find undervalued stocks,” he said, adding that he still considers all recommendations before making a trade. “I always support AI as a tool, not a replacement.”
Thomas Schlossmacher, a 31-year-old individual investor and founder of Specialty Tokens, which builds AI systems for enterprises, tested the trading agent after seeing claims online that AI could discover profitable market patterns. Instead, he said, “we’re just consistently losing money.”
“If you’re using an automated system or relying on an agent, you’re probably going to have a professional do it for you,” he said. “I think it’s foolish in a sense to blindly hire an agent and say, ‘Please make me money.'”
building guardrail
This debate highlights one of the industry’s biggest challenges. Teaching an AI agent to buy and sell stocks is relatively easy. It’s much harder to teach investors what that actually means.
An investor might simply tell the agent, “Grow your portfolio aggressively.” But does that mean accepting greater volatility, concentrating stock holdings, using options, or accepting the possibility of greater losses? AI agents can follow instructions faithfully and still produce outcomes that investors did not intend.
That’s why many companies are building guardrails before giving AI major powers. For example, public requires users to review and approve agent workflows before performing investment tasks.
“You still have the last word,” Abraham said. “AI agents will no longer have a mind of their own. … They will just execute.”
The more responsibility AI agents take on, the more important it becomes for businesses to ensure the technology works as intended.
“We have to put the customer’s best interests first,” Citizen’s Ryan said. “If an agent doesn’t behave according to the model or as expected, that’s a risk to the company.”
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