AI Agents Expand Into Tokenized Stocks as Agentic Finance Race Accelerates

Ondo Finance, Virtuals Protocol, and Treasures opened more than 430 tokenized stocks to over 40,000 autonomous artificial intelligence (AI) agents on Friday, letting the bots trade onchain equities. Treasures handles the execution, while Ondo powers the tokenized equities. At launch, the service covers US stocks on Ethereum and Solana, subject to certain jurisdiction restrictions. AI Agents Step Into Tokenized Equity Trading as Sector Tops $1.5 Billion Tokenized stocks rank among cryptos fastest-growing segments. Their distributed value reached about $1.5 billion, according to the data platform RWA.xyz. That marks roughly 360% year-over-year growth. Ondo Finance leads the segment with more than 57% market share. Virtuals noted that algorithmic systems already handle about two-thirds of US equity volume, though mostly inside large institutions. The integration opens that same direct-trading capability to any agent. According to the latest announcement, traders can now leverage agent hedge funds, run copy-trading vaults, hand portfolios full autonomy, or set programmatic strategies that trade nonstop. Wall Street is now tradeable by AI. And you can access it all through Virtuals Protocol. AI can trade tokenized stocks like SpaceX, Apple, Tesla, and NVIDIA, powered by @OndoFinance, executed through @treasures_io. The launch joins a wider race to make AI agents active financial participants. Mastercard launched Agent Pay for Machines (AP4M), a payment system that enables AI agents to buy and sell services. Robinhood launched Agentic Trading on May 27. Coinbase also introduced a tool to connect AI agents to customer accounts. However, US lawmakers have flagged concerns. House Financial Services Committee Democrats pressed the SEC this week on how it oversees AI agents trading for retail investors. Representatives Bill Foster and Brad Sherman posed 13 questions to SEC Chair Paul Atkins. They set a July 31 deadline and warned that agents trained on similar data could herd and amplify volatility.