CryptoTRON DAO expands AI fund to $1 billion to...

TRON DAO expands AI fund to $1 billion to back agentic economy infrastructure

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TRON DAO, the community-governed organization behind one of the most heavily used blockchain networks for stablecoin settlement, is scaling its AI Fund from $100 million to $1 billion as it doubles down on building infrastructure for the burgeoning agentic economy, according to a Monday announcement.

The fund targets early-stage investments and acquisitions across key areas such as agent identity, stablecoin payments, tokenized assets, and developer tools for autonomous financial systems.

The initiative expands on a 2023 thesis that anticipated the convergence of AI and blockchain.

With that convergence now gaining validation, TRON is positioning AI agents as independent economic actors that require fully onchain systems combining identity, payments, and ownership.

Onchain AI agents have scaled to process millions in payments, but their activity remains a very small portion of overall stablecoin volumes each year. Analyst projections suggest the agentic economy could reach $30 trillion by 2030.

Fee economics and AI agents

Multiple blockchain networks, including Ethereum, Solana, and Base, are actively developing use cases around automated and high-frequency transaction systems, each with varying levels of infrastructure maturity and funding.

TRON’s competitive position is largely driven by transaction cost efficiency. For applications that rely on large volumes of small transactions, the fee structure becomes a critical constraint, favoring networks optimized for low-cost settlement.

New technical standards

The expansion comes as new technical standards develop across the ecosystem, including ERC-8004, an identity protocol for autonomous agents that launched earlier this year and surpassed 24,000 identity NFT registrations in its first month, as well as the x402 protocol, which is designed to facilitate machine-to-machine payments and is starting to see early developer adoption.

Disclosure: This article was edited by Vivian Nguyen. For more information on how we create and review content, see our Editorial Policy.



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