Robinhood Opens Retail Trading to AI Agents

28 May 2026 - 19:07 CEST
Robinhood company logo
Credit: Robinhood

Retail brokerage Robinhood is pushing deeper into the idea that retail investing could eventually be navigated by AI agents as much as by humans, introducing tools aimed at enabling autonomous systems to interact with financial markets with minimal user input.

The company unveiled on 27 May a beta version of its "Agentic Trading" product, allowing users to connect third-party AI agents directly to Robinhood accounts. The system currently supports equities trading, though Robinhood said crypto, event contracts, futures and options will follow in later releases.

Robinhood shares rose about 3% following the announcement and extended gains in after-hours trading, climbing a further 5.4% to $80.47 by 16:40UTC on 28 May.

Crypto expansion ahead

Under the new framework, users allocate funds into separate "sandboxed" accounts where AI agents can autonomously execute trades, monitor portfolios and rebalance positions without requiring manual approval for every action.

While the launch focused on equities, Robinhood included digital assets in its longer-term roadmap, aligning with a broader industry push toward so-called agentic finance, where AI systems can transact autonomously using blockchain infrastructure and stablecoins

The concept has gained momentum across crypto markets this year. At the ETHDenver conference in February, Ethereum co-founder Vitalik Buterin argued that AI agents could accelerate blockchain-based and pay-per-use internet economies. 

AI agents enter finance

Robinhood also launched an "Agentic Credit Card" product, enabling AI systems to make purchases through dedicated virtual cards with configurable spending limits and optional manual approvals.

The company acknowledged the risks tied to autonomous finance, warning AI agents could misinterpret instructions, rely on stale data or behave unpredictably.

The regulatory backdrop also remains uncertain. Regulators have identified autonomous AI systems as a growing supervisory challenge, particularly around accountability and best execution when software, rather than humans, initiates trades.