Investment tools are powerful, but largely reactive. They help investors research, analyze and act, but they still depend on the investor to decide what deserves attention and when. AI agents could change that relationship, turning investment technology from a tool investors operate into something closer to a teammate that works alongside them.
Financial products already automate a considerable amount of work. Portfolios can be rebalanced, risk monitored and trades executed according to predefined rules. These systems act, but usually within narrow workflows designed around a specific event or instruction. Agents introduce a more flexible form of automation, capable of reasoning through changing circumstances rather than following a predefined path.
For Anmol Verma, who spent several years in public markets before founding AI wealth management platform Finn, this represents a more fundamental shift in the role of financial technology: from products that wait for investors to direct them to systems capable of understanding enough context to determine next steps. "The promise of agentic finance is not that investors make more decisions," Verma says. "It is that they can bring more intelligence to every decision, without being constrained by how much information a human can individually track and process."
Becoming proactive is not simply about detecting more signals. It is about knowing which ones matter. An agent that reacts to every market movement, company announcement or missed target would create more work for the investor, not less. To be genuinely useful, it needs to understand which changes are relevant, how urgently they matter and, just as importantly, when no action is warranted.
AI makes it possible to incorporate more of that context into the systems that investors rely on. Instead of simply processing more information, these systems can begin to build an evolving understanding of the investor and the investment process they are supporting. Verma expects adoption to happen in phases, with agents initially helping investors understand what is happening, then recommending what to do and eventually taking on more of the work required to carry a decision through.
This shift towards agentic finance has the potential to automate more of the work around a decision while keeping investors focused on the areas where judgment matters most. The power of the learning loop is key, with every interaction revealing something new and allowing the agent to learn from the decisions it supports, not just the information it processes.
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