What is Alaya Governance Token (AGT)?

By CMC AI
24 May 2026 09:06PM (UTC+0)
TLDR

Alaya Governance Token (AGT) is the native utility and governance token for Alaya AI, an open Web3 platform that connects distributed communities to create and label AI training data.

  1. Governance & Staking – AGT holders govern the platform and can stake tokens to support AI model development and earn rewards.

  2. Dual-Token Economy – Works alongside the AIA token and a dual NFT system to create a sustainable incentive cycle for data contributors.

  3. Core Purpose – Powers a decentralized infrastructure for sourcing, sampling, and auto-labeling high-quality AI training data.

Deep Dive

1. Governance & Utility

AGT is central to Alaya AI’s decentralized governance. Holders can participate in decision-making and stake tokens in AI model pools. Staking incentivizes active contribution to the platform’s auto-labeling models and helps secure the network by deterring malicious actors (Alaya AI).

2. Economic Ecosystem

The platform employs a dual-token system: AGT for governance and staking, and AIA as a utility token. This is integrated with a dual NFT system—tradeable Alaya NFTs for task access and wallet-bound medallion NFTs for specialized qualifications (Alaya AI). Together, they form a circular economy that rewards users for contributing data, ensuring high-quality output through network effects.

3. Platform Purpose & Function

Alaya AI is an open, composable Web3 data infrastructure. Its primary function is to provide tailored data sampling and auto-labeling for AI training. Inspired by swarm intelligence, it uses customizable Web3 incentives and techniques like RLHF (Reinforcement Learning from Human Feedback) to gather and process multimodal data—including text, image, audio, and video—from a distributed community (Alaya AI).

Conclusion

Fundamentally, AGT is the economic and governance engine for a decentralized network that aims to democratize access to high-quality AI training data. How will its staking and reward mechanisms evolve to balance data quality with contributor growth?

CMC AI can make mistakes. Not financial advice.