Grayscale seeks U.S. listing for Bittensor ETP in first institutional bet on decentralized AI

تكنلوجيا اليوم
2025-12-30 16:51:00
Grayscale is aiming to give U.S. investors exposure to Bittensor’s TAO, pushing decentralized artificial intelligence further into mainstream crypto markets.
The digital asset manager filed an initial S-1 registration statement with the U.S. Securities and Exchange Commission on Tuesday for what would be the first U.S.-listed exchange-traded product (ETP) offering exposure to TAO.
The proposed Grayscale Bittensor Trust, expected to trade under the ticker GTAO, would hold TAO directly if approved, giving investors regulated access to one of the largest tokens associated with decentralized AI. TAO currently has a market cap of around $2.3 billion, according to CoinDesk data.
“Today we filed the initial S-1 for Grayscale Bittensor Trust (ticker: $GTAO) with the SEC,” the firm said in a post on X, calling the filing the next step toward converting the trust into an ETP.
Barry Silbert, chairman of Grayscale, wrote on X that the move reflects how quickly decentralized AI is evolving. “Decentralized AI is developing quickly, and Grayscale is pioneering access,” Silbert said.
The filing marks the first such ETP in the U.S. for TAO. Previously, Deutsche Digital Assets, a Germany-regulated provider of exchange-traded products (ETPs), said it would list a Bittensor ETP, which will trade on the SIX Swiss Exchange under the ticker STAO.
Bittensor operates as an open network that uses crypto-economic incentives to coordinate machine learning development, rewarding contributors of models and computing power with TAO. The project has garnered attention as investors seek exposure to AI-related crypto assets beyond traditional smart contract platforms.
While approval is not guaranteed, the filing underscores how asset managers are increasingly racing to package emerging crypto narratives, including decentralized AI, into regulated investment products, signaling growing institutional appetite for the sector.



