VeChain CEO Says Blockchain Is Key to Trust for AI Agents

VeChain co-founder and CEO Sunny Lu believes AI agents—software that can act autonomously and continuously—could become the next major driver of blockchain adoption, but only if the ecosystem develops stronger ways to verify identity and establish accountability.

Speaking during Cointelegraph’s Chain Reaction show on Wednesday, Lu argued that widespread trust in always-on autonomous systems will require “a new accountability system,” adding that “the perfect solution is a blockchain.” His comments centered on VeWorld.ai, an agent-building platform built on VeChain, and a broader vision of how agents could earn credibility over time.

Key takeaways

• Sunny Lu says AI agents operating around the clock need a dedicated accountability layer to earn public trust.
• Lu’s model relies on blockchain-based identity and reputation “passports” to track agents and their creators.
• Smart contracts are positioned as a mechanism for settling transactions between agents—or between agents and people.
• Lu frames agent-building as a new way for non-developers to monetize domain expertise, similar to how app stores expanded software distribution.
• Industry warnings persist: other leaders have cautioned that users may become dependent on agent providers they do not control.

Why Lu thinks blockchain is essential for autonomous agents

Lu’s argument begins with a practical problem: AI agents are not intermittent tools. If autonomous agents run continuously, the trust model changes. Instead of trusting a human operator, users and institutions would need reliable ways to confirm who is behind an agent and whether that agent behaves predictably over time.

In Lu’s view, blockchain can serve as the foundation for that trust. He described the concept of agents carrying digital “passports,” paired with a “decentralized credibility system” designed to track reputations—not only of the agents themselves, but also of their creators. The implication is that accountability should be auditable and transferable, rather than dependent on centralized intermediaries.

He also pointed to smart contracts as a settlement layer for interactions. If agents are interacting with one another, or with individuals, their transactions could be handled under programmable rules, potentially reducing disputes about what happened and why.

VeWorld.ai and the push toward reputation-based agent ecosystems

Lu tied his broader thesis to VeWorld.ai, describing it as an agent-building platform that uses VeChain’s blockchain. The emphasis on reputation and identity is central to his pitch: an agent that can demonstrate reliable behavior over time could become more usable, while weak accountability could undermine adoption.

This matters for investors and developers because reputation systems are only useful when they are consistent and hard to game. While the article does not outline specific technical details of how “passports” and credibility scores would be computed, Lu’s framing suggests VeChain is positioning itself not just as infrastructure for payments or assets, but as a trust layer for autonomous software.

Lu also pointed to existing blockchain adoption efforts in supply-chain tracking. VeChain has previously pursued use cases such as food traceability, including a project involving a Walmart China subsidiary for tracing food products, according to earlier coverage on Cointelegraph. That track record provides context for why identity and verification themes resonate within VeChain’s broader narrative: the company has repeatedly focused on “proof” systems that can be checked independently.

Monetizing expertise beyond software development

Beyond trust and accountability, Lu’s comments highlighted a second adoption pathway: turning agent-building into a broader economic opportunity. He argued that AI agents could help individuals monetize their expertise and deliver services or businesses without requiring them to be software developers.

His comparison to mobile app stores is instructive. App stores enabled developers to distribute and monetize software to global users, while also lowering barriers for new entrants. Lu’s view is that agent-building tools could similarly expand who can participate—opening the market to people with specialist experience, local knowledge, or hobbies, not only programmers.

Lu described examples from his own experiments, including educational support for his daughter, an agent intended to assist his mother’s daily routine and recovery, and a virtual employee that handled purchasing, inventory, sales, and operations for an acquaintance’s shop in Milan. While these anecdotes do not prove commercial viability at scale, they reinforce his core point: agents can be packaged as practical services rather than purely technical products.

Real concerns: dependence on agent providers

Lu’s optimism comes alongside warnings from other industry voices about the risks of relying on agent platforms. In an October interview, Animoca Brands chairman Yat Siu told Cointelegraph that crypto traders could use AI agents to work around the clock, but warned that users may end up building trading strategies around services they do not control.

The concern is structural. If an agent’s behavior, model updates, or execution pathway depend on a third-party provider, users may face hidden constraints—ranging from changes to the agent’s tooling to differences in how instructions are carried out. That can be especially problematic in high-stakes environments such as automated trading, where small shifts can affect outcomes.

For Lu’s vision of blockchain-based credibility to work in practice, the accountability system would need to reduce—not obscure—this kind of dependency. If agents can demonstrate provenance, reputation, and enforceable rules through verifiable on-chain records, users may be better positioned to assess risk before trusting automation.

What to watch next

As agent platforms mature, the key question will be whether identity, reputation, and transaction settlement can be made reliable enough for everyday users and institutions—without forcing them to trust opaque intermediaries. Lu’s blockchain-based accountability concept offers one path forward, but adoption will likely depend on how effectively these systems address real-world operational risks highlighted by industry critics.