Top 10 Predictions for the Encryption AI Field in 2025

With the booming development of the AI industry, the field of encryption AI has rapidly emerged. An expert focused on encryption AI research made 10 predictions for 2025, and the following are the details of the predictions.

1. The total market value of encryption AI tokens reaches 150 billion USD

Currently, the market value of encryption AI tokens only accounts for 2.9% of the market value of altcoins, but this proportion is expected to increase significantly. AI encompasses everything from smart contract platforms to memes, DePIN, Agent platforms, data networks, and smart coordination layers, and its market position is expected to be on par with DeFi and memes.

The reasons for this confident prediction include:

• Encryption AI is at the convergence of two of the most powerful technologies.
• Possible global AI frenzy, such as OpenAI IPO and other triggering events.
• The enthusiasm of retail investors for AI concepts, as well as the convenience of investing through tokens.

2. Bittensor Revival

As a long-established project in the encryption AI field, Bittensor(TAO) has recently achieved significant breakthroughs: lower registration fees for more subnets, performance superior to Web2 peers, and the introduction of EVM compatibility.

The launch of dTAO ( is expected to be an important turning point in the first quarter of 2025. Each subnet will have its own token, and the relative price will determine the emission distribution.

Reasons for the revival of Bittensor:

• Market-based emission mechanism
• Investors can deploy capital for specific subnets.
• EVM integration attracts more developers

3. Calculating the market to become the next "L1 market"

The exponential growth in computing demands is driving new infrastructure solutions. The decentralized computing layer provides raw computing power in a verifiable and cost-effective manner.

Similar to the L1 market:

• A similar competitive landscape will emerge between the calculation protocols.
• The huge demand from Web2 provides growth potential for the encryption AI market.

Reliability, cost-effectiveness, and developer-friendliness will be the key factors for success.

4. AI agents will dominate blockchain transactions

By the end of 2025, it is expected that 90% of on-chain transactions will be executed by AI agents, rather than direct human operation. These agents will continuously rebalance liquidity pools, allocate rewards, or execute small payments based on real-time data.

The reason for this transformation:

• AI agents can process large amounts of data faster and more accurately.
• The decrease in transaction costs promotes small and frequent transactions.
• Humans tend to delegate tedious tasks to automation systems.

As the proportion of agent-driven transactions increases, there will be a need for new governance mechanisms, analytical platforms, and auditing tools.

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5. The Rise of Agent Clusters

The concept of Agent clusters refers to the seamless collaboration of micro AI agents to execute complex tasks. This will enable the AI agents network to exchange information, negotiate, and make collaborative decisions.

The application scenarios of the cluster include:

• Coordinate distributed computing resources
• Real-time verification of information sources
• Perform specialized tasks

The universal communication standard is crucial for cluster development. The transparent rules of blockchain will make the system more resilient and adaptive.

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6. The encryption AI working team will be a human-machine hybrid.

The company has begun to experiment with hybrid teams composed of humans and AI agents. In the future, AI agents will become true collaborators, possessing autonomy, responsibilities, and even salaries.

Advantages of human-machine collaboration:

• Significantly improve productivity
• Establish trust through smart contracts
• Social norms are constantly evolving

The boundary between "employees" and "software" will gradually blur.

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7. 99% of AI Agents will perish

Only agents that can generate enough value to cover operational costs can survive. This elimination mechanism is beneficial for industry development, encouraging developers to prioritize practicality over gimmicks.

Survival Game Example:

• Carbon Credit Trading AI
• DEX arbitrage bot
• Social media content creator

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8. Synthetic data exceeds human data

Synthetic data provides a scalable, ethical, and privacy-friendly alternative for AI training. Its advantages include:

• Unlimited Scale Generation
• Protect Privacy
• Can be customized according to needs

Decentralized AI may develop around "micro-laboratories" that specialize in creating targeted synthetic datasets.

9. Decentralized training is more practical

With the advancement of technology, the efficiency and performance of decentralized training will be significantly improved. High-performance models that can run on edge devices and even mobile phones are expected to emerge.

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10. Ten new encryption AI protocols reach a market value of 1 billion USD

The encryption AI market is huge and has not yet been fully developed, providing opportunities for new projects. It is expected that at least ten new encryption AI protocols ) have not yet issued tokens, and the circulating market value of ( will exceed $1 billion.

The new protocol may replace existing participants through innovative incentive mechanisms, technological breakthroughs, and improvements in user experience. This presents a wealth of opportunities for investors and is also what makes this field exciting.