Venture Capitalists Discuss the Future of AI Agents in Blockchain: Efficiency and Coordination Key to Success

Blockchain and AI Agents: The Key to Unlocking Future Innovation, Say VCs

As artificial intelligence (AI) continues to make inroads into business processes, its integration with blockchain technology offers significant potential, particularly through AI agents that automate tasks on-chain. Yet, according to a recent discussion among venture capitalists at Cointelegraph Accelerator’s X Spaces session, the full potential of AI agents in blockchain is still in the early stages, with improvements needed for more efficient and practical use cases.

Zoie Zhang, co-founder of Stealth Project, Fiona Ma, investment and research leader at DWF Ventures, and Samiz Bayan, an investor at Draper Dragon, gathered to discuss how AI agents can be better integrated with blockchain technology. The group emphasized that while the industry is seeing promising advancements, the real leap in AI adoption will require clearer frameworks for agent coordination and more advanced use cases.

The Need for More Advanced AI Agents

Ma kicked off the conversation by underscoring the need for more sophisticated AI agents that can perform complex tasks and interact across various platforms. “We need AI agents that can make complex decisions and interact with a bunch of different platforms. Right now, the market is mostly filled with basic and intermediate agents,” Ma said. She further emphasized that investors often view AI as a buzzword when projects fail to present concrete use cases for its application.

Zhang pointed out that AI agents could offer valuable solutions in monetizing user-generated content (UGC), particularly in community-driven projects. For example, frameworks such as Griffin AI and OpenAI Swarm can streamline workflows and facilitate meaningful interaction between users and AI. These platforms make AI more practical by automating complex tasks within a user-friendly framework.

AI and DeFi: A Powerful Pairing

One area where AI agents are expected to shine is in decentralized finance (DeFi). Bayan explained how AI could be used not only for executing trades but also for more complex tasks like monitoring positions and executing automated actions. “DeFi and AI make a strong pair,” he noted, adding that AI agents could play a pivotal role in enhancing the efficiency of DeFi operations.

Ma shared insights into two DeFi projects currently under development at DWF Labs. One of them, HeyAnon, combines conversational AI with real-time data aggregation, allowing users to manage various DeFi operations such as bridging, swapping, staking, and borrowing, while pulling insights from platforms like Twitter, Telegram, and Discord. Another project, AI16Z, reimagines fund management by using AI to analyze market sentiment, on-chain data, and trends to make decisions, much like a virtual hedge fund manager.

Coordination Layers: Unlocking the Full Potential of AI Agents

A major theme that emerged from the discussion was the importance of agent coordination. To fully realize the potential of AI agents, developers need to focus on creating systems where agents can work together effectively. Zhang pointed out that as AI agents become more capable, coordinating their actions in a meaningful way will become a critical part of their functionality. “We need frameworks where multiple agents can organize tasks together to produce a meaningful result,” she said.

The speakers also cited examples of emerging platforms that are already exploring agent orchestration. Nethermind, for instance, is an L2 network run entirely by autonomous agents. These agents work together in a consensus-driven environment, allowing for customized, agent-run chains tailored to specific use cases. Such frameworks hold significant promise for building fully autonomous systems across various sectors, from finance to healthcare.

Bridging the Gap to Institutional Adoption

Despite the excitement surrounding blockchain and AI integration, institutional adoption remains a challenge, primarily due to regulatory uncertainty and entrenched legacy systems. Bayan suggested a hybrid approach to overcome these barriers, where institutions continue to rely on traditional systems while gradually integrating blockchain technologies in specific areas. This incremental adoption could help large institutions become more comfortable with decentralized technologies.

Bayan also pointed to CARV, a project that uses blockchain for benefits and credentials while relying on off-chain machine learning for computation. This hybrid model offers a way for traditional institutions to adopt blockchain technology in a way that aligns with their existing infrastructure.

The Role of Tokens and Sustainability in AI Agents

Not all AI agent projects need to launch with a token, according to Zhang. She argued that the primary focus should be on proving the use case and obtaining client feedback before introducing tokenomics. “A token should improve the ecosystem and governance once the business model is established,” she said.

Ma echoed this sentiment, emphasizing that from a venture perspective, AI projects must demonstrate long-term value. “We need products with staying power—not just something that peaks at TGE and then disappears,” Ma pointed out, stressing the importance of building sustainable demand rather than simply relying on initial hype.

Bayan also highlighted the need for simplicity in both user experience and developer tools. “Users shouldn’t even realize they’re using blockchain or Web3. The next breakthrough moment will be when large Web2 companies start using blockchain-based compute. It needs to feel effortless,” he said.

The Future of AI Agents in Blockchain

As AI agents continue to evolve, Zhang envisions a future where platforms integrate more powerful AI-driven bots into everyday workflows, simplifying tasks for users. Whether it’s social betting, health information sharing, or managing digital assets, AI-powered bots will soon become more embedded in platforms that users already interact with, such as social media.

“I think very soon we’ll see very powerful products supported by AI-driven bots and streamlined AI agents,” Zhang concluded, highlighting the massive potential that lies in the convergence of blockchain and AI technologies.

For further exploration of AI and blockchain integration, check out these related resources and recent developments in decentralized finance.