Stories
AI Agent Users Surge Six-Fold as Investors Bypass Traditional Advisers
- •Alpaca reports a nearly six-fold increase in individual users running parallel AI agent strategies over the past 18 months, accompanied by a surge in API activity.
- •Investors who previously paid traditional advisers 1 to 2 percent annually for passive index-tracking portfolios are now using language models and APIs to simulate and run strategies at a lower cost.
- •Clients routinely manage dozens or even close to a hundred concurrent agent-driven strategies, testing approaches from simple index replication to active rules-based systems.
- •While simple buy-and-hold mandates shift to LLM-orchestrated systems, complex portfolios involving private markets or heavy regulatory oversight still require human expertise.
- •Financial platforms face growing pressure to prioritize multi-account infrastructure, robust API access, and agent-friendly tooling to support this shift.
Key Questions Answered
A significant rise was recorded by Alpaca over an 18-month period as simple buy-and-hold mandates shifted to LLM-orchestrated systems. Clients who previously maintained one or two accounts are now running dozens of concurrent agent-driven strategies to test different approaches at a much lower cost.
Complex and judgement-heavy portfolios still require human oversight. This includes concentrated equity books, private-market exposure, and portfolios with significant regulatory and risk considerations where soft skills and edge-case risk assessment are difficult to automate.
Brokers face growing pressure to prioritise multi-account infrastructure, robust API access, and agent-friendly tooling. Additionally, software engineers hired by these platforms are increasingly expected to be AI-native, focusing on supervising and verifying what agents produce rather than writing every line of code by hand.
