**Hong Kong Consensus Conference Observation: The Intersection of AI and Crypto Is Reshaping Web3** At the 2026 Consensus Conference currently underway in Hong Kong, a subtle yet profound shift is emerging. Three years ago, industry discussions still revolved around infrastructure topics such as L2 scaling and stablecoin compliance. Today, as Hong Kong Financial Secretary Paul Chan emphasized in his speech the integration of artificial intelligence and digital assets, the focus has quietly shifted: with AI algorithms capable of autonomously interacting with tokens and smart contracts, are we laying the foundational order for a new kind of economic participant? The driving force behind this transformation is efficiency. For autonomous agents that require real-time procurement of computing power, access to data services, or cross-border payments, the account verification and clearing cycles of traditional banking systems are clearly mismatched with machine-speed decision-making. As a result, "agent finance" is moving from concept to practice. Developers are now experimenting with AI agents holding private keys, executing on-chain strategies, and automating asset allocation. Stablecoins are thus being redefined—no longer just a safe-haven tool for humans, but a neutral medium of exchange for value transfer between machines. **From "Peer-to-Peer" to "Code-to-Code"** If blockchain over the past decade has addressed the problem of trust between humans, then as AI agents become active on-chain participants, the trust structure is evolving into "code-to-code." Justin Sun revealed at the conference that TRON plans to launch a perpetual contract feature and is committed to enhancing yields through AI technology. He noted that given the current popularity and application prospects of AI agents, TRON had previously launched an AINFT product and will further deepen AI's financial applications within its ecosystem. Legal agents call upon data agents, trading agents coordinate with liquidity protocols, and intelligent entities complete high-frequency, micro-settlement transactions through standardized interfaces and cross-chain protocols. The growth in on-chain activity increasingly originates from automated wallets and strategic programs, rather than purely human clicks. AI wallets have also evolved from experimental products into tools capable of managing multiple assets and executing complex logic, now entering real-world pilot scenarios. **Machine Transaction Flows and the Reshaping of the Public Chain Narrative** Against this backdrop, high-performance public chains are assuming a new narrative role. Low latency, low fees, and predictable execution environments make certain networks better suited to host machine-grade transaction flows. Valuation discussions surrounding these networks are beginning to factor in the potential demands of the "agent economy." While prices remain influenced by macro liquidity and sentiment, if future on-chain activity is predominantly driven by algorithm-based entities, the demand structure for underlying tokens may shift. Some researchers refer to this as the "invisible payment economy"—where settlement, identity verification, and compliance logic are embedded at the protocol level, allowing users to transact without even perceiving the process. **Computing Power as an Asset and the Agent Economy** Supporting this trend is the restructuring of computing power infrastructure. Global AI investment is growing rapidly, with data center expansion and high-end GPU procurement becoming focal points for capital. However, a highly concentrated supply structure has placed developers under cost pressure. Against this backdrop, DePIN networks are regaining attention. By incentivizing distributed hardware resources through token rewards, these networks aim to shorten the supply cycle of computing power and offer developers more options. While cost advantages remain to be validated, the concept of "democratizing computing power" is shifting the direction of industry discourse. At the conference, multiple institutions have shifted their focus from singular infrastructure narratives to agent finance. Haseeb Qureshi, Managing Partner at Dragonfly, stated that while his firm's investments remain focused on stablecoins, DEXs, and asset tokenization, the next phase will pay greater attention to the integration of AI agents and crypto networks. He believes that the ability of agents to hold assets and invoke protocols on-chain is opening new application spaces. As for recently discussed projects like OpenClaw, they remain in early stages and may take years to mature. This is not a chase after hype, but a forward-looking assessment of structural trends. Projects like Bittensor are further attempting to integrate model capabilities and computing power into on-chain incentive systems. Through reward distribution and subnet competition mechanisms, algorithmic performance is mapped into tradeable assets, creating a feedback loop between technological evolution and market signals. Computing power is no longer just a resource—it has become a liquid, tradable digital commodity. **Verifiability, Identity, and Risk Structures** However, agent-led networks also introduce new risks. As the proportion of AI-generated content rises rapidly, verifying model integrity and data provenance has become a real-world challenge. Zero-knowledge proofs are being introduced into scenarios such as "inference proofs" to confirm that outputs indeed originate from specific, untampered models. For agents executing financial decisions, such verifiability is particularly critical. Web3 protocols are assuming the role of an "audit layer," providing traceable credentials for algorithmic behavior. Identity systems are also evolving. When users may possess multiple on-chain agents, the definition of "subject" is being reexamined. The industry is extending from "Know Your Customer" to "Know Your Agent," emphasizing agent ownership, permission boundaries, and accountability. Legal issues surrounding digital and asset management are also beginning to enter policy discussions. As automated nodes become stable participants, incentive mechanisms are increasingly designed around "effective utilization" and "sustained productivity," rather than short-term user growth. Token models are shifting from a traffic logic to a productivity logic. At the regional level, Hong Kong is positioning itself at this intersection. The regulatory framework is gradually being clarified, with virtual asset policies and fintech strategies advancing in parallel, providing institutional space for innovation. Meanwhile, the rapid of AI at the enterprise level has laid a practical foundation for this convergence. Joe Ngai, Senior Partner and Chairman of McKinsey Greater China, revealed at the conference that approximately 98% of enterprises are already utilizing AI technology to varying degrees. The real bottleneck lies not in model capability, but in organizational structure and talent. He also noted that Chinese enterprises rank among the global leaders in digital adaptability and AI adoption. **Hong Kong's Institutional Window** As AI becomes enterprise-grade infrastructure, blockchain's significance as a tool for value and data rights verification is being amplified. What Hong Kong offers is not merely regulatory transparency, but an institutional environment that connects enterprise-level AI applications with on-chain financial tools. This synergy is attracting capital and developers to reassess the strategic position of Eastern markets. Looking back at this phase, it is evident that blockchain has not replaced existing internet structures, but rather, amid AI's expansion, it provides a verifiable and clearable underlying logic. An AI system lacking transparency risks descending into a black box, while a blockchain network without productivity support struggles to sustain itself. The convergence of the two fosters a new symbiotic relationship between trust mechanisms and computing resources. If future smart terminals are embedded with agent programs, users may no longer need to directly operate wallets and cross-chain tools; value exchange will occur automatically in the background. At that point, Web3 will no longer exist in form, but will become an invisible settlement and trust layer. The true inflection point of the technological narrative lies not in price fluctuations, but in how humanity, through cryptography and institutional design, preserves agency and control in an algorithm-driven era. This transformation is still unfolding. But one thing is certain: when algorithms become economic agents, blockchain is no longer merely a technological option—it becomes the foundation of order.