From Tools to AI Teammates: The Next Era of Investing
September 13, 2026 – 5:35 pm
Photo by Anmol Verma
Credit: Anmol Verma
Investment tools are powerful, but largely reactive. They help investors research, analyze, and act, yet they still depend on the investor to decide what deserves attention and when. Though they respond intelligently, they rarely take initiative.
AI agents could change this dynamic, transforming investment technology from a tool investors operate into something closer to a teammate that works alongside them.
Financial products already automate much work: portfolio rebalancing, risk monitoring, 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. Instead of executing a single rule, they can interpret changes across an investment portfolio, relate them to an objective, and coordinate the steps required to respond. For investors, whether retail or institutional, this could mean understanding how new information impacts an investment thesis or portfolio, identifying what deserves attention, and helping determine what should happen next.
For Anmol Verma, who spent years in public markets before founding AI wealth management platform Finn, this represents a 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."
Knowing what matters
Becoming proactive isn’t simply about detecting more signals; it’s 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.
That requires context. The same information can mean something very different depending on the portfolio, investment objective, and time horizon. A company announcement could be market noise or evidence that an important assumption behind an investment has changed.
AI makes it possible to incorporate more of that context into the systems 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.
Earning the right to act
Understanding what matters is different from being trusted to act on it. Agentic finance raises the stakes because a system can understand the objective and still make the wrong decision. It could misunderstand an investment thesis, miss an important risk, or act on incomplete information. The more responsibility it takes on, the more confidence investors need in its judgment and its boundaries.
Verma expects adoption to happen in phases. Agents may first help investors understand what is happening, then recommend what to do, and eventually take on more of the work required to carry a decision through. Initially, this might mean contained tasks like updating a model after earnings or monitoring developments in a specific sector.