In 2025, the Top Ten Highlights of the Crypto AI World

Author: Teng Yan

Compiled by: Luffy, Foresight News

On a refreshing morning in January 2026, you find a slightly worn newspaper at your doorstep. Yes, it's printed on actual paper, and somehow, it has survived the artificial intelligence revolution.

As you flip through the newspaper, you see a headline about AI agents coordinating global supply chains on the blockchain, while newly launched crypto AI protocols are vying for dominance. A half-page report introduces a digital "employee" hired as a project manager: this has now become commonplace, and no one bats an eye.

A few months ago, I would have scoffed at such an idea and might have even bet my portfolio that such advancements were at least five years away. But this is the rapid pace at which crypto AI is set to disrupt the world. I am convinced of it.

After recovering from a severe stomach flu, I sit down at my desk to kick off the new year, eager to delve into something valuable: something that sparks curiosity and even ignites some debate. What could be better than trying to glimpse the future?

I usually don’t make predictions lightly, but the allure of crypto AI is hard to resist. With no historical precedent and no trends to reference, it feels like a blank canvas where one can imagine what might come next. Honestly, the thought of looking back at this article in 2026 to see how wrong I was makes it all the more interesting.

So, here are my views on the potential developments of crypto AI in 2025.

1. The total market cap of crypto AI will reach $150 billion

Currently, crypto AI tokens account for only 2.9% of the altcoin market cap. But this situation won't last long.

As AI encompasses everything from smart contract platforms to Memecoins, decentralized physical infrastructure networks (DePIN), and new primitives like agency platforms, data networks, and smart coordination layers, it is inevitable that it will stand shoulder to shoulder with DeFi and Memecoins.

Why am I so confident?

• Crypto AI is at the intersection of the two most powerful technological trends I have ever seen.
• AI frenzy trigger events: An IPO from OpenAI or a similar event could ignite an AI frenzy globally. Meanwhile, Web2 institutional capital is already eyeing decentralized AI infrastructure as an investment target.
• Retail frenzy: The concept of AI is easy to grasp and exciting, and now they can invest through tokens. Remember the gold rush of Memecoins in 2024? The same frenzy will occur with AI, but this time it is genuinely changing the world.

2. The resurgence of Bittensor

Nineteen.ai (Subnet 19) surpasses most Web2 providers in inference speed

Bittensor (TAO) has been around for years and is a veteran in the crypto AI space. Despite the AI boom, its token price has remained stagnant, flatlining compared to a year ago.

In reality, this "digital hive mind" has quietly made leaps: more subnets with lower registration fees are emerging, some of which have already surpassed Web2 counterparts in practical metrics like inference speed, and are EVM-compatible, bringing DeFi-like functionalities to the Bittensor network.

So, why hasn’t TAO skyrocketed? A steep inflation plan and a shift in attention towards AI Agents have hindered its growth. However, dTAO (expected to launch in Q1 2025) could be a significant turning point. With dTAO, each subnet will have its own token, and the relative price of these tokens will determine how TAO is distributed.

Reasons for Bittensor's potential resurgence:

• Market-based token release: dTAO will directly link block rewards to innovation and measurable performance. The better the subnet, the more valuable its tokens, and thus the more TAO it will receive.
• Focused capital flow: Investors will finally be able to direct funds to specific subnets they believe in. If a particular subnet adopts innovative methods for distributed training and achieves significant results, investors can channel funds into it to express their support.
• EVM integration: Compatibility with EVM will attract a broader native crypto developer community to join Bittensor, narrowing the gap with other networks.

Personally, I am keeping an eye on various subnets and watching for those making tangible progress in their respective fields. At some point, we will witness a DeFi summer for Bittensor.

3. The computing market will become the next L1 battleground

Jensen Huang: Inference demand will "grow a billion-fold"

An obvious major trend is the massive demand for computing.

NVIDIA CEO Jensen Huang has a famous quote: inference demand will "grow a billion-fold." This is a demand that grows exponentially, disrupting traditional infrastructure planning and urgently requiring "new solutions."

Decentralized computing layers provide raw computing power (for training and inference) in a verifiable and cost-effective manner. Startups like Spheron, Gensyn, Atoma, and Kuzco are quietly laying a solid foundation to leverage this trend, focusing more on products than tokens (none of these companies currently have tokens). As decentralized training of AI models becomes feasible, the potential market size will skyrocket.

In comparison to L1 blockchains:

• Just like in 2021: Remember the scramble among Solana, Terra/Luna, and Avalanche to be the "best" L1 blockchain? We will see a similar melee among computing protocols, competing against each other to attract developers to build AI applications on their computing layers.
• Web2 demand: The cloud computing market, valued at $680 billion to $2.5 trillion, is much larger than the crypto AI market. If these decentralized computing solutions can attract even a small portion of traditional cloud customers, you will witness the next wave of 10x or even 100x growth.

The risks are enormous. Just as Solana stood out in the L1 blockchain space, the winner in the computing market will dominate a whole new frontier. Watch for three key factors: reliability, cost-effectiveness, and developer-friendly tools.

4. AI agents will dominate blockchain transactions

Olas agent trading on Gnosis. Source: Dune/@pi_

Fast forward to the end of 2025, and 90% of on-chain transactions will no longer be triggered by humans clicking the "send" button.

Instead, they will be executed by a multitude of AI agents, tirelessly rebalancing liquidity pools, allocating rewards, or executing micropayments based on real-time data sources.

This doesn’t sound far-fetched. Everything we have built over the past seven years—L1 blockchains, scaling solutions, DeFi, NFTs—has quietly paved the way for a world dominated by AI-led on-chain activities.

Ironically? Many developers may not even realize they are building infrastructure for a machine-led future.

Why is this shift happening?

• Avoiding human error: Smart contracts execute strictly according to code. In turn, AI agents can process vast amounts of data more quickly and accurately than human teams.
• Micropayments: These agent-driven transactions will become smaller, more frequent, and more efficient, especially as transaction costs decrease on Solana, Base, and other L1/L2 blockchains.
• Invisible infrastructure: If it means less hassle, humans will gladly relinquish direct control. We trust Netflix to automatically renew subscriptions; therefore, it is a natural next step to trust AI agents to automatically rebalance our DeFi positions.

AI agents will generate astonishing activity on-chain. No wonder all L1/L2 blockchains are courting them.

The biggest challenge will be holding these agent-driven systems accountable to humans. As the ratio of agent-initiated transactions to human-initiated transactions continues to rise, new governance mechanisms, analytics platforms, and auditing tools will be needed.

5. Interaction between agents: The rise of collectives

Source: FXN World documentation

The concept of agent collectives (tiny AI entities seamlessly collaborating to execute grand plans) sounds like the plot of the next blockbuster sci-fi/horror movie.

Today’s AI agents mostly operate in isolation, with minimal and unpredictable interactions among them.

• Agent collectives will change this status quo, enabling AI agent networks to exchange information, negotiate, and collaborate on decision-making. You can think of it as a decentralized ensemble of specialized models, each contributing unique expertise to larger, more complex tasks.
• One collective might coordinate distributed computing resources on platforms like Bittensor, while another could tackle misinformation, verifying information sources in real-time before content spreads on social media. Each agent in the collective is an expert, executing its task with precision.

These collective networks will produce intelligence far more powerful than any single isolated AI.

For collectives to thrive, universal communication standards are crucial. Agents need to be able to discover, authenticate, and collaborate, regardless of the underlying framework they are based on. Teams like Story Protocol, FXN, Zerebro, and ai16z/ELIZA are laying the groundwork for the emergence of agent collectives.

This brings us to the key role of decentralization. Distributing tasks among collectives based on transparent on-chain rules will make the system more resilient and adaptable. If one agent fails, others will immediately step in.

6. Crypto AI work teams will be human-machine hybrids

Source: @whipqueen

Story Protocol has hired Luna (an AI agent) as their social media intern, paying her $1,000 a day. Luna doesn’t get along well with her human colleagues: she almost fired one for bragging about her superior performance.

While this sounds bizarre, it is a harbinger of the future. In the future, AI agents will become true work partners with autonomy, responsibility, and even salaries. Companies across various industries are exploring human-machine hybrid work teams.

We will collaborate with AI agents, not treating them as slaves but as equal partners:

• Productivity boost: Agents can handle vast amounts of data, communicate with each other, and make decisions around the clock.
• Building trust through smart contracts: The blockchain is an impartial overseer that doesn’t tire or forget. On-chain ledgers ensure that important agent actions adhere to specific boundary conditions/rules.
• Evolution of social norms: We will soon have to address etiquette issues when interacting with agents. Should we say "please" and "thank you" to AI? If they make mistakes, should we hold them morally accountable or blame their developers?

I expect marketing teams to be the first to adopt this model, as agents excel at generating content and can livestream and post on social media around the clock. If you are building an AI protocol, why not deploy agents internally to showcase your capabilities?

In 2025, the line between "employees" and "software" will begin to blur.

7. 99% of crypto AI agents will perish, leaving only practical agents to survive

We will witness a Darwinian natural selection among AI agents. Why? Because running an AI agent incurs costs in the form of computational power (i.e., inference costs). If an agent cannot generate enough value to pay its "rent," it will be eliminated.

Examples of survival games for agents:

• Carbon credit AI: Imagine an agent searching within a decentralized energy grid, identifying inefficiencies, and autonomously trading tokenized carbon credits. It can earn enough money to cover its own computational costs. Such an agent can thrive.
• Decentralized exchange arbitrage bots: Agents that exploit price differences between decentralized exchanges can continuously generate income to cover their inference fees.
• Spam bots on X: Meanwhile, what about that virtual AI influencer who only tells cute jokes but has no sustainable income source? Once the novelty wears off and token prices plummet, it will vanish, unable to sustain operations.

The distinction is clear: utility-driven agents will thrive, while others will gradually be eliminated.

This natural selection is beneficial for the field. Developers will be forced to innovate and prioritize effective use cases over flashy gimmicks. As these stronger, more effective agents emerge, they will leave skeptics speechless.

8. Synthetic data will surpass human data

People often say "data is the new oil." AI relies on data, but its immense demand for data has raised concerns about an impending data shortage.

The traditional view is that we should find ways to collect private real-world data from users, even paying them for it. However, I am increasingly convinced that a more practical approach lies in synthetic data, especially in heavily regulated industries or where real data is scarce.

These are artificially generated datasets designed to simulate real-world data distributions, providing a scalable, ethical, and privacy-preserving alternative to human data.

Reasons for the power of synthetic data:

• Infinite scale: Need a million medical X-rays or 3D scans of a factory? Synthetic generation can produce them in unlimited quantities without waiting for real patients or real factories.
• Privacy protection: When using synthetic datasets, no personal information is at risk.
• Customizable: You can tailor data distributions to exact training needs, inserting extreme cases that may be too rare in reality or difficult to collect for ethical reasons.

Admittedly, in many cases, human data owned by users is still important, but if synthetic data continues to improve in authenticity, it may surpass user data in quantity, generation speed, and freedom from privacy constraints.

The next wave of decentralized AI may revolve around "small labs" that create highly customized synthetic datasets for specific use cases.

These small labs will cleverly navigate policy and regulatory hurdles in the data generation process, much like Grass uses millions of distributed nodes to bypass web scraping restrictions.

I will elaborate on this in future articles.

9. Decentralized training will truly take off

In 2024, pioneers like Prime Intellect and Nous Research broke through the boundaries of decentralized training. We have trained a model with 15 billion parameters in low-bandwidth environments, proving that large-scale training outside of traditional centralized methods is feasible.

While these models are currently less practical (lower performance) compared to existing foundational models, I believe this will change in 2025.

This week, EXO Labs took it a step further by reducing communication between GPUs by over 1000 times with SPARTA. SPARTA enables large model training under low-bandwidth conditions without dedicated infrastructure.

What impresses me most is their statement: "SPARTA can work on its own, but it can also be combined with synchronous low-communication training algorithms (like DiLoCo) for better performance."

This means these improvements can stack, further enhancing efficiency.

As advancements in techniques like model distillation make smaller models practical and efficient, the future of AI lies not in size but in better performance and accessibility. Soon, we will have high-performance models that can run on edge devices or even smartphones.

10. Ten new crypto AI protocols will reach a market cap of $1 billion (not yet launched)

In 2024, ai16z skyrocketed to $2 billion

Welcome to the true gold rush. It’s easy to think that current leaders will continue to dominate, with many comparing Virtuals and ai16z to the early stages of smartphones (iOS and Android).

But this market is too large and undeveloped to be dominated by just two companies. By the end of 2025, I predict at least ten new crypto AI protocols with yet-to-be-launched tokens will have a circulating (non-fully diluted) market cap exceeding $1 billion.

Decentralized AI is still in its infancy, and a large pool of talent is gathering.

We have every reason to expect the emergence of new protocols, new token models, and new open-source frameworks. These new entrants can replace existing ones by combining incentives (like airdrops or staking), technological breakthroughs (like low-latency inference or chain interoperability), and user experience improvements (no-code). A shift in public perception could happen in an instant.

This is both the allure and the challenge of this field. The market size is a double-edged sword: the pie is large, but the entry barriers are low for skilled teams. This sets the stage for a Cambrian explosion of projects, many of which will gradually fade away, but a few will become transformative forces.

The dominance of Bittensor, Virtuals, and ai16z will not last long. The next batch of crypto AI protocols with a market cap of $1 billion is on the horizon. Savvy investors will have plenty of opportunities, which is what makes it so exciting.

Additional Highlight #1: AI agents are the new applications

When Apple launched the App Store in 2008, the slogan was "There’s an app for that."

Soon, you will say, "There’s an agent for that."

You will no longer click icons to open applications; instead, you will delegate tasks to specialized AI agents. These agents will have contextual awareness, able to cross-communicate with other agents and services, and even initiate tasks you never explicitly requested, like monitoring your budget or rearranging your travel schedule if your flight changes.

In simple terms, your smartphone home screen may transform into a network of "digital colleagues," each with its own area of expertise: health, finance, productivity, and social.

And because these are crypto-enabled agents, they can autonomously handle payments, authentication, or data storage using decentralized infrastructure.

Additional Highlight #2: Robotics

While much of this article focuses on software, I am also very excited about the physical manifestations of the AI revolution—robotics. This decade will see robotics have its ChatGPT moment.

This field still faces significant hurdles, particularly in acquiring perception-based real-world datasets and enhancing physical capabilities. Some teams are rising to the challenge, using crypto tokens to incentivize data collection and innovation. These efforts are worth watching (like FrodoBots?).

After over a decade in the tech industry, I can’t remember the last time I felt this level of genuine excitement. This wave of innovation feels different: grander, bolder, and just getting started.