How AI Technology Drives Stablecoin Innovation?

Stablecoins, as a key infrastructure in the cryptocurrency field, are experiencing a rapid development period. Between 2023 and 2025, the supply, trading volume, and turnover speed of stablecoins are all expected to grow significantly, particularly in the fields of payment and cross-border transactions. At the same time, the regulatory environment is becoming increasingly clear, and the degree of institutional adoption is continuously rising. Several large banks and payment companies are actively laying out stablecoin businesses, and some enterprises are also beginning to explore the use of stablecoins for payments to reduce transaction costs.

With the in-depth application of traditional finance, the innovation of stablecoins in the AI field is also advancing, aiming to address the challenges faced in the Web3 AI ecosystem.

Challenges Facing the AI Ecosystem

Challenge 1: The contradiction between AI token design and DeFi ecosystem construction

Many AI projects design their tokens as core components of the ecosystem, but this often leads to market volatility and hinders the participation of key players. For example:

• The VIRTUAL and AGENT liquidity pools of Virtuals have the issue of impermanent loss.
• Aethir uses $ATH as a payment method, bringing price volatility risk.
• Bittensor pays subnet coins to participants, resulting in frequent exchanges of stablecoin.

These designs, while beneficial for the accumulation of token value, also make it difficult to build on the DeFi ecosystem.

To address this challenge, Maitrix has launched an over-collateralized native stablecoin (AI USD) for various AI ecosystems. Users can mint and burn AI USD by depositing AI tokens and their derivative assets through CDP. Maitrix has established partnerships with several top AI ecosystems to build a financial infrastructure layer for AI projects.

Challenge 2: AI Computing Resource Expansion Financing Demand

With the widespread application of AI, the demand for computing resources in the market has surged. However, the high prices of enterprise-level GPUs and the complex processes of traditional financing make it difficult to meet the rapid expansion needs of data centers.

Gaib and USDAI have emerged to tokenize the future cash flow of GPUs, helping data centers to finance efficiently.

Gaib packages GPU revenue cash flows into tokenized securities products, allowing investors to purchase and receive regular rewards. They have launched the artificial intelligence synthetic dollar "AID", supported by GPU-financed trading portfolios, with government bonds and other assets as reserves. Currently, they have accumulated approximately $22 million in total locked value.

USDAI is a stablecoin supported by hardware assets ( such as GPUs, telecommunications equipment, etc. ) as collateral for loans. Borrowers obtain loans from USDAI and pay interest, and these earnings belong to USDAI holders. The target annual yield of USDAI is 15-25%, utilizing CALIBER technology to simplify the loan issuance process.

Other AI-related stablecoin innovations

Almanak has launched alUSD, a tokenized AI yield optimization strategy that maximizes risk-adjusted returns by investing stablecoins across multiple DeFi platforms.

AixFi and interstable are developing a DeFi protocol vault for the automatic deployment of USDC assets, with plans to gradually introduce AI decision-making mechanisms.

Future Outlook

In the future, protocols focused on leveraging GPU computing power to create high yields for stablecoins may emerge. More tokenized AI strategies are expected to arise, combining the ability of AI to optimize yields with the composability of DeFi. As infrastructure for stablecoins is built for the AI ecosystem, more value generated by AI will flow into the DeFi space, enhancing the value capture capability of the entire Web3 ecosystem.

Although these innovations are exciting, risk management, anchoring mechanisms, and clearing mechanisms are crucial in the stablecoin field. Investors must fully understand all risk factors before participating.