Top 10 Predictions for Encryption AI in 2025

With the rapid development of the AI industry, the field of encryption AI has quickly emerged. A researcher focused on encryption AI has made 10 predictions for 2025, and here are the details of those predictions.

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

Currently, the market capitalization of encryption AI tokens accounts for only 2.9% of the market capitalization of altcoins, but this ratio is expected to increase significantly. AI encompasses various fields ranging from smart contract platforms to memes, DePIN, Agent platforms, data networks, and smart coordination layers, and its market position is expected to rival that of DeFi and memes.

The reasons for being confident about this include:

• Encryption AI is the fusion of two of the most powerful technologies.
• Possible AI frenzy triggering events, such as IPOs of large AI companies, etc.
• Web2 capital has begun to pay attention to decentralized AI infrastructure
• The concept of AI is easy to understand and exciting, allowing retail investors to invest through tokens.

2. Bittensor Revival

As a long-established project in the encryption AI field, the decentralized AI infrastructure Bittensor(TAO) has been running for many years. Despite the AI boom, its token price still hovers around the level of a year ago. However, Bittensor's digital hive mind(Digital Hivemind) is quietly making leaps: more subnet registration fees are reduced, subnet performance surpasses that of Web2 peers, and EVM compatibility introduces DeFi-like functionalities.

The reasons why the TAO token has failed to surge include the inflation plan and the market's focus on the Agent platform. However, the dTAO, expected to be launched in the first quarter of 2025, may become a significant turning point. dTAO will allow each subnet to have its own token, and the relative prices of these tokens will determine the distribution of emissions.

Potential reasons for the revival of Bittensor:

• Market-based emission mechanism
• Investors can deploy capital to specific subnets.
• EVM integration attracts a broader range of encryption native developers

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

The most obvious trend currently is the endless demand for computing power. A CEO of a well-known chip company once predicted that reasoning demand will grow "a billion times." This exponential growth will disrupt traditional infrastructure planning, urgently requiring new solutions.

The decentralized computing layer provides raw computing power in a verifiable and economically efficient manner. Several startups are quietly building a solid foundation, focusing on products rather than tokens. As decentralized training of AI models becomes feasible, the entire potential market size will expand dramatically.

Comparison with L1 market:

• Similar to the L1 competition in 2021, there will also be competition among computing protocols.
• The cloud computing market size of 680 billion to 2.5 trillion US dollars makes the encryption AI market look small in comparison.

The winner will dominate a whole new field. Focusing on reliability, cost-effectiveness, and developer-friendliness will be the key to victory.

4. AI agents will flood blockchain transactions

It is expected that by the end of 2025, 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 feedback.

Everything built over the past seven years, including ( L1, rollup, DeFi, and NFT ), has laid the groundwork for a world where AI operates on the blockchain. Ironically, many builders may not realize that they are creating infrastructure for a machine-led future.

The reasons for this transformation include:

• Reduce human errors
• Supports smaller, more frequent, and more efficient micropayments
• Simplify user operations

AI agents will generate a large amount of on-chain activity, which also explains why all L1/L2 are embracing agents. The biggest challenge is to ensure that these agent-driven systems are accountable to humans. As the proportion of transactions initiated by agents increases, new governance mechanisms, analytics platforms, and auditing tools will be needed.

5. Rise of Intelligent Body Clusters

The concept of an Agent cluster refers to micro AI agents seamlessly collaborating to execute grand plans. Currently, most AI agents operate independently, with minimal interaction and unpredictability. Agent clusters will change this status quo, enabling AI agent networks to exchange information, negotiate, and make collaborative decisions.

Clusters can coordinate distributed computing resources, handle error messages, and other complex tasks. Each agent is an expert, precisely executing its tasks. These cluster networks will produce a more powerful intelligence than a single isolated AI.

To ensure that clusters thrive, universal communication standards are crucial. Multiple teams are laying the groundwork for the emergence of Agent clusters. Decentralization plays a key role in this, and transparent on-chain rule management makes the system more resilient and adaptable.

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

A certain protocol has hired an AI Agent as a social media intern, signaling that in the future AI Agents will become true collaborators, with autonomy, responsibilities, and even salaries. Companies across various industries are testing human-machine hybrid teams.

Advantages of collaborating with AI Agents in the future:

• Productivity surge
• Establish trust through smart contracts
• Social norms are constantly evolving

The boundary between "employees" and "software" will begin to blur in 2025.

7. 99% of AI Agents will perish - only the useful ones can survive

In the future, we will see a "Darwinian" elimination among AI agents. Running AI agents requires spending on computational resources, and if an agent cannot generate enough value to pay its "rent," it will be eliminated.

Agent survival game example:

• Carbon Credit AI: Identifying inefficiencies in the energy network and trading carbon credit quotas
• DEX arbitrage bot: Utilize price differences between decentralized exchanges
• Social Media Shitposter: Fun but lacks a sustainable source of income

Utility-driven agents will thrive, while distraction-driven agents will gradually disappear. This elimination mechanism is beneficial for industry innovation, prompting developers to prioritize practicality over gimmicks.

8. Synthetic data exceeds human data

AI relies on data development, but its enormous demand has raised concerns about data depletion. Synthetic data provides a scalable, ethical, and privacy-friendly alternative to human data.

Advantages of synthetic data:

• Unlimited Scale
• Privacy-friendly
• Customizable

The next wave of decentralized AI is expected to revolve around "micro-laboratories" that can create highly specialized synthetic datasets tailored for specific use cases. These micro-laboratories will cleverly circumvent the policy and regulatory barriers in data generation.

9. Decentralized training is more practical

In 2024, some pioneers broke through the boundaries of decentralized training. Although these models perform worse than existing foundational models, changes are expected in 2025.

Recently, a team has made progress in significantly reducing the communication requirements between GPUs. This means that large model training can be conducted over slow bandwidth without the need for specialized infrastructure.

With technological advancements, micro models will become more practical and efficient. The future of AI lies not in scale, but in becoming better and more user-friendly. High-performance models that can run on edge devices and even smartphones are expected to emerge soon.

10. Ten new encryption AI protocols reach a market capitalization of $1 billion

The encryption AI market is vast and still underdeveloped, making it unlikely to be dominated by a few participants. By the end of 2025, it is expected that at least ten new encryption AI protocols ( will issue tokens that have a circulating market value exceeding $1 billion.

Decentralized AI is still in its infancy, and the talent pool is continuously growing. New protocols, token models, and open-source frameworks will keep emerging. These new participants may replace existing projects through innovative incentive mechanisms, technological breakthroughs, and improvements in user experience.

The enormous market size lays the foundation for project explosions. Although many projects may gradually disappear, a few may possess transformative power. The dominance of current leading projects may be difficult to maintain, as new $1 billion encryption AI protocols are about to emerge, providing savvy investors with ample opportunities.

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