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The next phase of investing is taking shape as brokerages, startups, and individual investors develop artificial-intelligence agents capable of overseeing portfolios and executing trades around the clock. These systems go beyond simple research tools. They are designed to interpret an investor’s goals, risk tolerance, and life circumstances, then act on that information continuously—whether the owner is awake or asleep.

Devin Ryan, head of financial technology research at Citizens, describes the shift in straightforward terms: effectively everyone gains access to a personal family office that never stops working. He expects meaningful adoption within the next few years rather than a decade from now. In his view, the agents will eventually handle far more than stock trades. They could continuously manage tax lots, cash balances, borrowing needs, mortgages, and overall portfolio construction, all calibrated to an individual’s specific objectives.

Most firms are deliberately avoiding a sudden leap to fully autonomous systems. Instead they are introducing AI that informs and recommends while leaving final authority with the human user.

Podium Markets AI offers one example. Its assistant, called Ivy, reviews a client’s holdings across multiple brokerage accounts and produces recommendations aligned with stated goals and risk preferences. The system stops short of placing trades on its own. “The AI informs, but the human decides,” said co-founder and CEO Dirk Mueller-Ingrand. The company’s longer-term vision is a persistent AI finance companion that remains available at all times, yet still requires explicit approval for actions.

Larger platforms are following a similar trajectory. Robinhood has opened its infrastructure so that third-party AI agents can connect to customer accounts. Public is building its own internal agents to automate investing workflows. Leif Abraham, Public’s co-founder and co-CEO, noted that the new era moves beyond independent research and manual order entry toward systems that can execute strategies on a client’s behalf—while still requiring human sign-off at key steps.

Ryan estimates that agentic finance could multiply transaction volumes by at least ten times. An investor who currently places two trades a month might eventually see twenty trades a day under an agent-driven model. He predicts that by the end of next year, agents could account for the majority of trade activity by number on some platforms.

While professional firms refine their products, individual investors have already spent three years testing general-purpose AI tools. Since ChatGPT’s mainstream arrival in late 2022, many have used large language models to summarize earnings reports, research companies, and generate stock ideas. Results have varied widely.

Obioha Okereke, a technology consultant and founder of the financial-literacy platform College Money Habits, built an agent on Anthropic’s Claude to screen for undervalued stocks and options opportunities. He treated the system as a hedge-fund analyst but reviewed every suggestion before acting. “I will always stand by AI being a tool as opposed to a replacement,” he said.

Others have been less successful. Thomas Schlossmacher, a retail investor whose company builds AI systems for businesses, tested automated trading agents after seeing online claims of profitable pattern recognition. He reported consistent losses. His conclusion was blunt: blindly handing capital to an agent and instructing it simply to “make money” is unwise. Professional-grade systems with proper oversight remain preferable for automated approaches.

Translating human instructions into precise machine behavior remains one of the industry’s central challenges. An investor might tell an agent to “grow my portfolio aggressively.” Does that mean higher volatility, concentrated positions, options strategies, or simply a greater willingness to accept loss? An AI can follow the literal command and still produce an outcome the client never intended.

For that reason, many platforms are installing clear guardrails. Public requires users to review and approve an agent’s proposed workflow before any investing activity occurs. “You still have the last word,” Abraham emphasized. “The AI agent will not have its own mind. It will only execute.”

As agents assume greater responsibility, the stakes for firms rise. Ryan stressed that customer best interests must remain paramount. If an agent behaves differently from its intended model, the firm itself faces material risk.

The technology is advancing rapidly, yet the industry consensus is measured: AI agents will increasingly handle routine analysis, monitoring, and even execution, but meaningful human oversight is expected to persist for the foreseeable future. The family office that never sleeps is coming—yet for now, it still reports to its client.

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