Grayscale has completed the filing for the Bittensor ETF - the first spot token AI ETF
Grayscale Investments has filed a Form S-1 application with the U.S. Securities and Exchange Commission (SEC) to convert its existing Grayscale Bittensor Trust into a spot-trading ETF, with the TAO token soon to be included in the Treasury.
1/3/20262 min read


New reserve strategy
In a significant step connecting traditional finance with the booming decentralized artificial intelligence sector, Grayscale Investments has filed a Form S-1 application with the U.S. Securities and Exchange Commission (SEC) to convert its existing Grayscale Bittensor Trust into a spot exchange-traded fund (ETF). The filing, due on December 30, 2025 , marks the first attempt to launch a U.S.-listed spot ETF, providing direct access to Bittensor's native token, TAO.
If approved, the proposed Grayscale Bittensor Trust ETF would trade on the NYSE Arca under the ticker symbol GTAO — positioning it as a regulated, accessible vehicle for institutional and individual investors seeking access to one of the leading decentralized machine learning networks without the complexities of holding tokens directly.
Bittensor has just undergone its first Halving
The filing comes just weeks after Bittensor's (TAO) first Halving event , which reduced the daily TAO issuance from 7,200 to 3,600 tokens — tightening supply in a network with a hard-bound total supply of 21 million (similar to Bitcoin's model). Bittensor has emerged as a leading project in the decentralized artificial intelligence narrative:
A decentralized marketplace for machine intelligence, where members contribute computing power, data, and models.
Rewards are issued in TAO to incentivize high-quality contributions across more than 129 subnets.
The market experienced strong growth following the halving event, with staking locking in approximately 35% of the circulating supply .
Filing for an ETF helps TAO gain wider institutional acceptance amid growing interest in AI-blockchain convergence — a topic that has driven significant capital inflows into related tokens throughout 2025.
Grayscale's strategic model
This filing continues Grayscale's strategy of being a market pioneer with single-asset, thesis-specific ETFs. After helping legitimize Bitcoin and Ethereum through regulated products, Grayscale is now testing whether US investors are ready for the next generation of cryptocurrency narratives.
Unlike meme-based or purely speculative tokens, Bittensor offers a clearer functional narrative than coded incentives for machine intelligence. By filing early, Grayscale can shape how regulators and investors view exposure to AI cryptocurrencies—potentially establishing TAO as the benchmark asset for this type of asset.
Our review
Despite its growth potential, TAO remains a relatively young and volatile asset. Its value depends on the continued widespread adoption of the Bittensor network, the quality of incentive programs, and competition from both centralized AI platforms and other decentralized alternatives.
The ETF structure helps mitigate custody and operational risks—but does not reduce market risk. Investors will still face significant price volatility due to market sentiment, technological advancements, and regulatory developments.
Grayscale's application for the first US-based Bittensor spot ETF represents a bold step toward institutionalizing the AI-crypto sector. This reflects the belief that investors are ready to look beyond Bitcoin and Ethereum—and that decentralized AI networks could form the next investment frontier in the digital asset landscape.
Disclaimer: The information presented in this article is the author's personal opinion in the field of cryptocurrency. This is not financial or investment advice. All investment decisions should be based on careful consideration of your personal portfolio and risk tolerance. The views expressed in this article do not represent the official stance of the platform. We recommend that readers conduct their own research and consult with experts before making any investment decisions.
Compiled and analyzed by HCCVenture
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