以下是内容的中文翻译： 在万事达卡首席执行官Michael Meebock主持的一次讨论中，该公司将自身定位为在不断演进的数字支付领域，尤其是稳定币和AI驱动的商业中，实现互操作性的关键中介。万事达卡旨在防止这个碎片化的生态系统演变成“意大利面条”式的混乱局面，其收购领先的稳定币平台EVNPay以连接全球稳定币交易便是例证。 Meebock深入探讨了“代理式商务”，其中AI充当客户的私人购物代理。想象一个大型语言模型（LLM）帮助规划露营旅行，它了解你过去的购买记录，并只推荐你所需物品。当这个AI代理需要跨不同商家执行购买时，挑战就出现了。这种无摩擦的体验虽然方便，但也带来了新的网络安全和欺诈风险。如何确定代理是合法的？错误或欺诈性交易又将如何处理？ 万事达卡的解决方案是**AgentPay**，一个旨在解决这些问题的协议。AgentPay确保AI代理在支付生态系统中被认可并获得信任方认证。通过AgentPay促成的交易是完全代币化的，这意味着每一条数据都被捕获，为消费者的意图提供无可辩驳的证据。该系统利用万事达卡现有的争议处理基础设施，如退单，为消费者提供与目前相同的保护。对万事达卡而言，AgentPay通过代币化和增强型网络安全解决方案等服务，代表着巨大的增长机遇。尽管它可能不会大幅增加整体消费（人们仍只需要一个帐篷，而不是五个），但由于无摩擦体验的增加和更优质的推荐，它可能会带来更多的交易，起到“交易增长倍增器”的作用。 讨论随后扩展到**AP4M（AgentPay for Machines，面向机器的AgentPay）**，重点关注B2B商业。Meebock描述了这样一个未来：企业可以按需购买数字内容、API、数据或计算能力。这需要目前尚不存在的高速、微小额（不足一美元的零头）支付。AP4M是一个基于AgentPay构建的协议，旨在以机器的速度和规模促进这些机器到机器的交易，确保信任和保护，即使底层支付轨道不同（如稳定币或账户到账户系统）。万事达卡将自身定位为这一关键互操作层的中立提供商，无论不同企业使用何种特定的数字货币或区块链。 关于战略增长，万事达卡采取“购买或自建”的方式。尽管它已从传统的消费者卡片业务显著扩展到企业、政府和多元化的支付形式，但并购决策纯粹是战略驱动的。当公司缺乏特定能力（例如，一家个性化公司），但能够利用其庞大的数据集、全球覆盖和网络来扩展所收购的解决方案时，它会选择收购。对于与其核心业务更接近的领域，它更倾向于内部自建，平衡这两种方法以成为股东资本的良好管理者。 关于资本配置，Meebock重申，对业务进行再投资（有机增长和非有机增长）是首要任务，其次是保持强大的资产负债表，这对其支付担保至关重要。股票回购是机会主义的，而非核心战略，仅在股价被低估时使用，例如在“AI交易热潮”中股价出现波动时。 谈及AI的更广泛影响，特别是对就业的影响，Meebock强调应将AI视为一种若部署得当，便能推动繁荣发展的技术。万事达卡专注于“以人为本的AI”，提升员工技能，利用AI工具进行更优质、更具战略性的工作，同时卸载重复性任务。他强调万事达卡独特且专有的交易数据是一大优势，提供了“入场券”，并在AI时代推动其长久发展。 最后，Meebock分享了他个人在这一要求严苛的职位上保持领导力的秘诀。他强调了拥有一个全球化、分布式领导团队的重要性，重视休假（甚至鼓励团队成员休更长的假），参与非营利工作以放松身心，以及从事摩托车和滑雪等需要全神贯注的爱好。他还表达了重新致力于多读书的决心，承认这对于个人成长的重要性。

In a discussion led by Michael Meebock, CEO of MasterCard, the company positioned itself as the crucial intermediary for interoperability in the evolving landscape of digital payments, particularly stablecoins and AI-driven commerce. MasterCard aims to prevent a "spaghetti" like mess in this fragmented ecosystem, exemplified by its acquisition of EVNPay, a leading stablecoin platform, to connect global stablecoin transactions. Meebock delved into "agentic commerce," where AI acts as a customer's personal shopping agent. Imagine an LLM (Large Language Model) helping plan a camping trip, knowing your past purchases, and recommending only what you need. The challenge arises when this AI agent then needs to execute purchases across various merchants. This frictionless experience, while convenient, introduces new cybersecurity and fraud risks. How do you know the agent is legitimate? How are errors or fraudulent transactions handled? MasterCard's solution is **AgentPay**, a protocol designed to address these concerns. AgentPay ensures that an AI agent is recognized and accredited as a trusted party in the payment ecosystem. Transactions facilitated by AgentPay are fully tokenized, meaning every piece of data is captured, providing irrefutable proof of the consumer's intent. This system leverages MasterCard's existing infrastructure for handling disputes, such as chargebacks, offering the same protections consumers currently enjoy. For MasterCard, AgentPay represents a significant growth opportunity through services like tokenization and enhanced cybersecurity solutions. While it might not dramatically increase overall consumption (people still need one tent, not five), it could lead to more transactions due to increased frictionlessness and better recommendations, acting as a "transaction growth multiplier." The conversation then extended to **AP4M (AgentPay for Machines)**, focusing on B2B commerce. Meebock described a future where companies purchase digital content, APIs, data, or compute power on a "pay-as-you-need" basis. This requires high-velocity, micro-fraction-of-a-dollar payments that don't exist efficiently today. AP4M is a protocol building on AgentPay to facilitate these machine-to-machine transactions at machine speed and scale, ensuring trust and protection, even if the underlying rails are different (like stablecoins or account-to-account systems). MasterCard sees itself as the agnostic provider of this critical interoperable layer, regardless of the specific digital currency or blockchain used by different businesses. Regarding strategic growth, MasterCard adopts a "buy or build" approach. While it has expanded significantly from its traditional consumer card focus to include businesses, governments, and diverse payment forms, M&A decisions are purely strategy-driven. The company acquires when it lacks specific capabilities (e.g., a personalization company) but can leverage its vast data set, global reach, and network to scale the acquired solution. For areas closer to its core, it prefers to build in-house, balancing both approaches to be good stewards of shareholder capital. On capital allocation, Meebock reiterated that reinvesting in the business (organically and inorganically) is the top priority, followed by maintaining a strong balance sheet crucial for its payment guarantee. Share buybacks are opportunistic, not a core strategy, used during times of perceived undervaluation, as seen when the stock experienced volatility during the "AI trade." Addressing the broader implications of AI, particularly for employment, Meebock emphasized viewing AI as a technology that, if deployed correctly, can drive prosperity. MasterCard focuses on "human-centered AI," upskilling its workforce to leverage AI tools for better, more strategic work, offloading redundant tasks. He highlighted MasterCard's unique and proprietary transactional data as a significant advantage, providing a "license to play" and driving longevity in the AI era. Finally, Meebock shared his personal approach to sustaining leadership in a demanding role. He emphasized the importance of a global, distributed leadership team, valuing vacation (even pushing team members to take longer breaks), engaging in non-profit work for mental breaks, and pursuing hobbies like motorcycling and skiing that demand complete focus. He also expressed a renewed commitment to reading more, acknowledging its importance for personal growth.