From Stablecoins To Autonomous AI: Exploring Key Trends Shaping The Future Of Web3 And Crypto At Hack Seasons Opportunity Mixer
In Brief
Key trends at the intersection of crypto and AI include the rise of stablecoins, the need for verification systems, the growth of decentralized infrastructure, and the evolution of DAOs and AI autonomy.
At the forefront of blockchain innovation, the latest Hack Seasons Opportunity Mixer held in Seoul brought together prominent figures from the AI and blockchain sectors to explore the evolving intersection of these two transformative technologies. Moderated by Amos Zhang, OG at Near Foundation, the panel “When AI Rewires Web3, Who Wins?” included speakers from Cronos, Kgen, Aethir, and Aleph Cloud.
The conversation began by addressing the fast rise of AI in recent years and the panelists’ perspectives on the intersection of AI with blockchain and the broader cryptocurrency space. They also discussed the challenges that need to be addressed.
One of the panelists pointed out that the combination of blockchain and AI is a natural one, explaining that AI works with data, and blockchains are inherently open, with transparent smart contracts and data—making it a perfect environment for AI to learn and self-train. However, the challenge lies in the many grand visions for AI agents that are supposed to automatically grow the wealth of users while they focus on other tasks. Despite this, concrete examples of how AI can effectively manage wealth have been scarce. The key challenge, therefore, is to create incremental, actionable use cases where AI can gain public trust. Many people remain hesitant to entrust their money to AI, especially with the current high rate of AI “hallucinations” or inaccuracies.
Other speakers supported this view, highlighting the critical role blockchain can play in building verification systems—not just for AI agents but also for humans involved in training those models or agents. Each AI agent requires human evaluation to ensure that they are progressing in the right direction. Additionally, AI agents require a vast network of developers to ensure proper functionality.
The panel also discussed three layers at which blockchain and Web3 enable AI. The first layer is the verification layer, which ensures the output generated by AI agents is trustworthy. Key components within this layer include assessing whether the output is AI-generated, identifying which model was used, and verifying that the models themselves have been trained properly. Zero-knowledge technologies (ZK) have made significant progress in this area, and ZK-verification is expected to become a standard in the future, including in regulatory frameworks.
The second layer focuses on the economic aspects of blockchain. Web3 and cryptocurrency introduce economic dynamism to AI, enabling AI agents to process payments, for example. The third layer addresses infrastructure—AI cannot be reliant on a few large companies that control GPUs, as these companies essentially control AI development due to their monopoly on GPU resources. Cryptocurrency enables a more distributed approach to infrastructure by spreading the supply of GPUs across the world, thus fostering innovation.
A recurring theme throughout the discussion was the importance of Web3 in safeguarding the future of AI. As AI becomes integrated into everyday devices, there are growing concerns about privacy. If AI has access to all data and that data is not secure, it could pose significant risks to individuals’ privacy. With centralized corporations controlling much of the data and influencing people’s day-to-day decisions, Web3 offers a solution by enabling decentralized, private AI. In a Web3 framework, AI can run in fully confidential instances, with verifiable models that ensure transparency. Users can deploy their own AI without relying on centralized providers, ensuring greater privacy and autonomy.
Furthermore, the panelists discussed the road to Artificial General Intelligence (AGI) and the role of Web3 in that journey. Currently, centralized corporations control the development of AGI by amassing data centers and training models, either through open-source or proprietary approaches. However, achieving AGI requires a completely autonomous system. In a decentralized environment, Web3 can facilitate this by enabling AI agents to manage their own computing resources, train their own models, and function independently—without the need for credit cards or centralized control. This autonomy could pave the way for AGI and even Artificial Superintelligence (ASI), with the added benefit of being open-source and decentralized. This, according to the panelists, is a critical area for future development and exploration.
Key Trends Shaping The Future Of Crypto And AI
Further insights were shared regarding the biggest trends expected in the next 12 months at the intersection of cryptocurrency and AI. The speakers discussed the macro-level opportunity, noting that large corporations are increasingly looking to enter the cryptocurrency space by launching their own stablecoins as a way to generate additional revenue. These companies are also seeking reliable on-ramps and off-ramps for stablecoin transactions. The possibility of a world with hundreds of stablecoins was raised, suggesting that this could resemble the current use of credit cards, with people holding multiple stablecoins for various purposes.
The question was posed as to how these hundreds of stablecoins could be aggregated—would it be AI or other builders taking on this challenge? This presents a large opportunity, as traditional corporations enter the blockchain space via stablecoins, creating the potential to build more accessible and efficient infrastructure. This could lead to the development of a seamless ecosystem for commerce, where AI agents play an integral role.
Another prediction highlighted by the speakers focused on the emerging trend of VeriFI, which builds upon the idea that the market will soon be flooded with AI agents. In the coming months, it may become difficult to differentiate between products generated by humans and those created by AI agents, or to discern whether actions are performed by AI agents or real users. To address this, there will be a growing need for a verification layer that distinguishes AI-driven actions from human activities, while also ensuring transparency around the underlying models and technologies used.
The speakers also agreed with the earlier point about stablecoins and introduced another evolving trend: prediction markets. This use case is expected to onboard hundreds of millions of users rapidly. In the long term, Real-World Asset (RWA) tokenization is seen as a fundamental transformation in finance. Another trend discussed was the continued growth of Decentralized Physical Infrastructure Networks (DePIN).
In the AI space, speakers noted that there would be a greater focus on open-source models, as enterprises are becoming increasingly serious about their AI strategies.
The conversation then turned to the evolution of Decentralized Autonomous Organizations (DAOs), which are expected to change how governance is approached. One emerging concept discussed was fully autonomous agent organizations, where the DAO itself functions as an agent—managing funds and executing actions independently. In this model, users would have the opportunity to own shares in the DAO. Additionally, user interfaces (UI) are expected to undergo significant transformations, with AI playing a crucial role in this shift.
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About The Author
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
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Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
