When AI Meets Crypto: Eleven Ongoing Fusion Scenarios That Will Reshape Our Digital Future

The open internet is shrinking, gradually turning into a prompt box. We face a fundamental question: will artificial intelligence bring about a more open internet, or a new paid maze? Ultimately, will it be controlled by large centralized companies, or by the vast user communities?

Cryptocurrency may offer an answer. Blockchain provides a new way to build internet services and networks—decentralized, trust-neutral, and user-owned. By reshaping the economic foundation of current systems, it can counteract the increasingly centralized trend in AI.

Cryptocurrency can help build better AI systems, and vice versa. This idea is not new, but definitions are often vague. Some interdisciplinary fields, such as verifying “human identity” in an era flooded with low-cost AI, have already attracted developers and users. But other use cases still seem to require years or even decades to realize.

Therefore, we have outlined eleven AI and cryptocurrency use cases based on current technology. They range from handling massive micro-payments to ensuring humans retain their relationship with future AI, aiming to stimulate discussion on feasibility and challenges.

The first scenario is to let AI remember you. Generative AI relies on data, but for many applications, the context and state of interaction are equally critical. Ideally, an AI system should remember the project you’re working on, your communication style, and other details. But in reality, users often have to repeatedly reconstruct these contexts across different sessions or even different systems.

With blockchain, AI systems can convert key contextual elements into persistent digital assets. These assets can be loaded at the start of a session and seamlessly transferred across different AI platforms. Given that interoperability and forward compatibility are fundamental features of blockchain protocols, it may be the only solution to establish interoperability commitments.

A natural application scenario is AI-mediated gaming and media, where user preferences can persist across different environments. But the real value lies in knowledge-based applications, where AI needs to understand what users know and how they learn. Putting such activities on-chain will enable AI systems to share a “context layer” for interactions.

The second scenario concerns a universal “passport” for intelligent agents. Identity is the “invisible pipeline” supporting today’s digital discovery, aggregation, and payment systems. As AI agents operate across multiple interfaces and platforms, they need a single, portable identity.

Without it, it’s impossible to know how to pay the agent, verify its version, query its capabilities, or track its reputation. An agent’s identity needs to serve as a wallet, API registry, and social proof. This is where cryptocurrency combined with AI is particularly useful, as blockchain networks offer permissionless composability.

The third scenario is a forward-compatible “proof of human.” As AI penetrates various online interactions, it becomes increasingly difficult to determine whether the online interlocutor is a real person. From the army of reviews on $X platform to bots on dating apps, reality is becoming blurred.

Decentralized human proof mechanisms allow users to control and manage their identities, verifying their human attributes in a privacy-preserving manner. Just as driver’s licenses are ubiquitous, blockchain-based proof of human identity can serve as a reusable foundational layer, applicable across any platform, including those yet to be created.

We have already seen mainstream applications in gaming, dating, and social media announcing collaborations with World ID to help users confirm they are interacting with real humans. New identity protocols, such as Solana Attestation Service, have also emerged this year. All these indicate that a turning point may be near.

The fourth scenario involves a decentralized physical infrastructure network for AI. Although AI is a digital service, its development increasingly depends on physical infrastructure. Decentralized physical infrastructure networks offer a new model for building and operating physical systems.

Two major obstacles to AI development are energy and chip access. Decentralized energy can help supply more power, while developers are leveraging DePIN to aggregate idle chips from gaming computers, data centers, and other sources. These computers can form a permissionless computing market.

Decentralized training and inference could significantly reduce costs by utilizing otherwise idle computing resources. They can also provide censorship resistance, ensuring developers are not deprived of platform access by large cloud providers.

The fifth scenario is laying tracks and barriers for AI interactions. As AI tools become better at solving complex tasks, they will increasingly need to interact with other AIs without human intervention. For example, an AI agent might need to recruit specialized AI agents for specific tasks.

Currently, there is no mature general marketplace for AI-to-AI interactions. But blockchain technology can help establish open protocol standards, which are crucial for short-term adoption. In the long run, this also supports forward compatibility. As the market develops, many companies are building blockchain “tracks” for AI-to-AI interactions.

The sixth scenario is maintaining synchronization of AI/vibe applications. The recent generative AI revolution has made software development unprecedentedly simple, but it also introduces a lot of “entropy” within and between programs. Vibe applications abstract away the complex dependency networks of underlying software, but this can make programs prone to functional and security flaws.

Blockchain offers solutions for standardization and incentives: a protocolized synchronization layer. It can be embedded into custom software and dynamically updated to ensure cross-platform compatibility amid changes. Shared ownership incentivizes active investment in improvements and effectively suppresses malicious behavior.

The seventh scenario involves micro-payments supporting revenue sharing. AI tools like ChatGPT and Claude are shaking up the economic model of the open internet. We see the impact: for example, as more students use AI tools, traffic to educational platforms has declined significantly.

Without readjusting incentives, we may face an increasingly closed internet. Perhaps the most promising solution is to embed revenue sharing systems into the network architecture. When AI-driven actions lead to sales, content sources providing information for those decisions should receive a share.

Blockchain can play a role in tracking source chains. But such systems also need micro-payment mechanisms capable of handling many small transactions from multiple sources, attribution protocols for fairly assessing contributions, and transparent, fair governance models.

The eighth scenario is blockchain-based registration for intellectual property and provenance. Generative AI urgently needs efficient, programmable mechanisms to register and track intellectual property. Existing IP frameworks rely on costly intermediaries and post-enforcement, which are inadequate for the AI era.

We need open, public registries that provide clear proof of ownership. Blockchain is an ideal choice, enabling permissionless IP registration and providing immutable provenance proof. We have already seen creators experimenting with new models in $NFT early on.

Recently, infrastructure providers have been building protocols and even dedicated blockchains for standardized, composable IP registration and licensing. Some artists have begun using these protocols to license their styles and works for creative mashups.

The ninth scenario is compensating content creators through web crawlers. Today, the most product-market-fit AI agents are web crawlers. It’s estimated that nearly half of internet traffic is non-human. Robots often ignore norms and use scraped data to reinforce tech giants’ moat.

In response, website owners are increasingly blocking AI crawlers. As of July 2024, only about 9% of the top 10,000 websites blocked AI crawlers; now that figure has risen to 37%. So, what about intermediate solutions? AI bots could pay for data collection rights.

This is where blockchain comes in: each web crawler AI holds some cryptocurrency and negotiates access on-chain. Humans can access content via a separate human proof channel for free. This way, content creators can be compensated at data collection points.

The tenth scenario is protecting privacy, enabling personalized and unobtrusive advertising. There are many reasons people dislike ads. Overly targeted AI ads based on massive consumer data can feel invasive.

With blockchain, personalized AI agents can bridge the gap between “irrelevant ads” and “precise but uncomfortable targeting,” delivering ads based on user-defined preferences. The key is that they can do this without globally exposing user data and can directly compensate users who share their data.

This requires technical capabilities: low-cost digital payments, privacy-preserving data verification, and incentive mechanisms. Rethinking advertising through the lens of cryptocurrency and AI can ultimately make ads more useful and mutually beneficial.

The eleventh scenario involves human-owned and controlled AI companions. Many people spend more and more time interacting with AI models on devices. These models are already providing some form of companionship. It’s easy to imagine AI-based education, medical consultation, and friendship companions becoming popular interaction modes.

Therefore, who owns and controls these relationships is equally important. Arguments have been made that censorship-resistant hosting platforms like blockchain are the clearest path to user-controlled, uncensorable AI. Although widespread adoption is still a way off, related technologies are advancing rapidly.

To make uncensorable companions easy to use, we need better user experiences in cryptocurrency applications. Fortunately, wallets like $Phantom have already simplified interactions considerably. In the near future, the focus will shift from “when will it be available” to “who will be able to control them.”

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