eToro has begun rolling out a feature that allows users to connect their own AI agents to live trading accounts. The company said the new function lets developers automate trades directly through eToro with allocated capital and defined risk limits.
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Dubbed Agent Portfolios, the new offering acts as a separate sub-account within a user’s main profile. According o the firm, investors can name the portfolio, set a budget starting from $200, and link an AI agent using a scoped API key. The agent can then open and close trades, check balances, and manage positions within that portfolio’s boundaries.
Adoption of Agentic AI Tools
Agentic AI is a type of AI that can analyze information and take actions for a user, such as moving money or placing trades, within set limits. In finance, it usually means autonomous software agents that follow a goal (for example, managing a portfolio) and interact with external systems like broker APIs without needing constant human prompts.
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The timing also reflects rising demand from retail clients for AI-assisted investing, with eToro recently reporting a 46% jump in AI tool usage in 2025 and strong interest in AI-related themes across its user base.
The rollout marks another step in its push to embed AI deeper into its trading ecosystem and shift more activity toward rules-based, automated strategies. It comes after the platform introduced AI tools such as the “Tori” AI companion and Alpha Portfolios, as well as public APIs aimed at letting users build and automate strategies on top of eToro’s infrastructure.
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The latest platform offers two setup paths via the desktop application or through a direct conversational prompt for integrated AI tools. No coding is required to activate a portfolio.
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For eToro, Agent Portfolios extend the long-running social and copy-trading model into user-built automation, effectively turning the platform into a sandbox where developers can deploy and test AI agents with real capital inside controlled sub-accounts.
Examples include Interactive Brokers, which has discussed agentic AI and autonomous strategy execution in its thought leadership and marketing, though mainly around tools and research rather than retail-facing AI sub-portfolios.
Commentary on Charles Schwab and Fidelity also describes how they explore agentic AI concepts for workflow automation and advisory support, but these efforts remain largely conceptual or internal, not packaged as ring‑fenced AI trading portfolios for end clients.