转载一下Forbes的文章

https://www.forbes.com/councils/forbestechcouncil/2025/02/07/ai-agent-harmony-composing-the-future-of-ai-collaboration/

Daniel Knauf is the Chief Technology Officer, Americas at Merkle.

We are at a turning point in artificial intelligence. While single-function chatbots once sufficed, today’s landscape is dominated by specialized AI agents that can manage travel, process payments or even draft proposals. However, as more brands launch their own AI agents, customers face an overwhelming maze of interfaces and interactions, threatening the very purpose of AI: to simplify lives.

The solution lies in agent-to-agent orchestration, a paradigm where AI agents communicate and collaborate to address complex needs. This approach offers a unified, streamlined experience, eliminating the need for users to manage multiple systems.

The Next Step: Agent-To-Agent Orchestration

Agent orchestration allows personal agents to collaborate with others, even across brands and ecosystems. Instead of managing multiple tools, users interact with a single “conductor” agent, which delegates tasks to specialized agents in the background. This creates a seamless, integrated experience that transforms complex ecosystems into unified workflows.

By enabling agents to interact and share capabilities, organizations can offer efficient and consistent experiences, restoring simplicity and enhancing customer satisfaction.

Scaling Human-Like Intelligence

AI agents must replicate the nuanced decision making of human representatives who blend intuition, domain expertise and guided procedures. Agent orchestration achieves this by dynamically coordinating tasks using a modular architecture. Each specialized service, such as payment processing or troubleshooting, operates as a microservice, while the orchestration layer connects these services logically to resolve complex issues.

This orchestration layer mimics human adaptability, ensuring that AI systems not only automate repetitive tasks but also navigate intricate workflows, addressing user demands without frequent human intervention.

Broadcasting Capabilities: Agent Directories

For agents to collaborate effectively, they must understand each other’s capabilities. Future ecosystems will feature standardized directories that list agent functionalities, required inputs and outputs. These directories allow agents to identify the best collaborators for specific tasks.

By exposing capabilities in machine-readable formats, organizations maintain control while enabling authorized agents to negotiate and delegate. This turns isolated services into interconnected networks of expertise, reducing complexity and enhancing flexibility.

Transforming Customer Experience

Agent orchestration revolutionizes the customer experience. Instead of juggling multiple chatbots or apps, users issue a single, natural language request (a prompt). Their personal agent consults capability directories, identifies appropriate agents and oversees task completion. This unified approach simplifies interactions, saving time and effort.

Brands adopting this model gain a competitive edge by becoming synonymous with efficiency and reliability. Over time, public directories could lead to “Agent Stores,” where brands list agent capabilities for broader collaboration. For instance, an airline’s agent might coordinate with hotel and rideshare agents to deliver a seamless travel experience.

Orchestration also redefines personalization. Beyond remembering purchase histories, advanced systems tailor entire processes to individual needs, proactively assembling agents to meet evolving demands. This creates a level of support that feels intuitive and proactive, driving loyalty and trust.

Proposed Architecture For Orchestration

• User Interaction Layer: A single interface where users submit requests, leaving the complexity to the orchestration system.

• Orchestration Layer: Interprets user intent, consults directories, applies rules and coordinates agents.

• Capability Directory: A registry of agent functionalities, ensuring seamless collaboration.

• Context/Policy Engine: Stores user data, enforces privacy and shapes outcomes based on policies.

• Interoperability Layer: Ensures agents adhere to consistent protocols for compatibility.

• Specialized Agents: Execute domain-specific tasks assigned by the orchestrator.

• Response Aggregation: Combines results into a unified response for the user.

This architecture transforms today’s fragmented systems into integrated solutions, offering simplicity and efficiency.

Preparing For Agent Orchestration

To prepare for agent orchestration, organizations must focus on laying a strong foundation for modularity, integration and interoperability. The first step is to ensure that existing systems and services are modular, with clearly defined inputs, outputs and dependencies. This modular architecture is essential for creating an ecosystem where agents can seamlessly collaborate. Organizations should also begin cataloging the capabilities of their AI agents and microservices in structured directories. These directories should include metadata and access policies, enabling agents to quickly identify and collaborate with the appropriate partners.

In addition to building modular systems and directories, organizations must address interoperability by adopting standardized communication protocols. This ensures that agents across different brands or ecosystems can integrate easily without requiring custom configurations. By focusing on these foundational elements, businesses can position themselves to fully embrace agent-to-agent orchestration and deliver a better customer experience.

Roadblocks To Watch For

While the benefits of agent orchestration are compelling, organizations must address several challenges to unlock its potential. One significant hurdle is ensuring data privacy and compliance. As agents collaborate, they must operate within strict boundaries, accessing only authorized information. Strong governance frameworks and policy enforcement are critical to mitigate risks and maintain trust.

Another challenge is overcoming interoperability gaps. Many organizations operate in siloed environments where systems are not designed to work together. This lack of compatibility can hinder the seamless integration needed for orchestration. Finally, businesses should prepare for the upfront investment required to build orchestration frameworks, including infrastructure upgrades, capability directories and standardized APIs. These efforts, while resource-intensive, will be instrumental in driving long-term success.

The Path Forward

Agent orchestration is the next evolution in AI. By turning complexity into a competitive advantage, it allows organizations to meet customer demands with precision and agility. Users no longer need to navigate tools or interfaces—they can focus on goals, trusting the AI ecosystem to handle the details.

This vision ultimately leads us to “agent harmony,” representing a future where AI agents collaborate dynamically to deliver intuitive and effective results. It is a shift from managing tools to managing outcomes, with technology acting as an invisible helper. As organizations embrace this model, they pave the way for AI systems that are not only efficient but also deeply fulfilling for users.

Daniel Knauf 是 Merkle 美洲区首席技术官。

我们正处于人工智能的转折点。虽然单一功能的聊天机器人曾经足够了，但如今的市场主要由专门的人工智能代理主导，它们可以管理旅行、处理付款甚至起草提案。然而，随着越来越多的品牌推出自己的人工智能代理，客户面临着令人眼花缭乱的界面和交互，威胁到人工智能的真正目的：简化生活。

解决方案在于代理到代理的编排，这是一种人工智能代理沟通和协作以满足复杂需求的范例。这种方法提供了统一、简化的体验，消除了用户管理多个系统的需要。

推广
下一步：代理到代理的编排
代理编排允许个人代理与其他人协作，甚至跨品牌和生态系统。用户无需管理多个工具，而是与单个“指挥”代理交互，该代理将任务委托给后台的专门代理。这创造了一种无缝、集成的体验，将复杂的生态系统转变为统一的工作流程。

通过使代理能够交互和共享功能，组织可以提供高效一致的体验，恢复简单性并提高客户满意度。

扩展类人智能
AI 代理必须复制人类代表的细致入微的决策，这些代表融合了直觉、领域专业知识和指导程序。代理编排通过使用模块化架构动态协调任务来实现这一点。每项专业服务（例如支付处理或故障排除）都作为微服务运行，而编排层将这些服务逻辑地连接起来以解决复杂问题。

该编排层模仿人类的适应性，确保 AI 系统不仅可以自动执行重复任务，还可以导航复杂的工作流程，无需频繁的人工干预即可满足用户需求。

广播功能：代理目录
为了使代理能够有效协作，他们必须了解彼此的能力。未来的生态系统将具有标准化目录，列出代理功能、所需的输入和输出。这些目录允许代理识别特定任务的最佳合作者。

通过以机器可读的格式公开功能，组织可以保持控制，同时使授权代理能够进行协商和委派。这将孤立的服务转变为相互关联的专业知识网络，从而降低复杂性并增强灵活性。

改变客户体验
代理编排彻底改变了客户体验。用户无需同时处理多个聊天机器人或应用程序，只需发出一个自然语言请求（提示）。他们的个人代理会查阅功能目录，确定合适的代理并监督任务完成情况。这种统一的方法简化了交互，节省了时间和精力。

采用这种模式的品牌通过成为效率和可靠性的代名词而获得竞争优势。随着时间的推移，公共目录可能会出现“代理商店”，品牌会在其中列出代理功能以进行更广泛的协作。例如，航空公司的代理可能会与酒店和拼车代理协调，以提供无缝的旅行体验。

编排还重新定义了个性化。除了记住购买历史之外，先进的系统还可以根据个人需求定制整个流程，主动组装代理以满足不断变化的需求。这创造了一种直观且主动的支持水平，从而推动了忠诚度和信任。

建议的编排架构

• 用户交互层：用户提交请求的单一界面，将复杂性留给编排系统。
• 编排层：解释用户意图、查阅目录、应用规则和协调代理。
• 功能目录：代理功能的注册表，确保无缝协作。
• 上下文/策略引擎：存储用户数据、实施隐私并根据策略塑造结果。
• 互操作性层：确保代理遵守一致的协议以实现兼容性。
• 专用代理：执行编排器分配的特定于域的任务。
• 响应聚合：将结果组合成对用户的统一响应。

这种架构将当今分散的系统转变为集成解决方案，提供简单性和效率。

为代理编排做准备
为了准备代理编排，组织必须专注于为模块化、集成和互操作性奠定坚实的基础。第一步是确保现有系统和服务是模块化的，具有明确定义的输入、输出和依赖关系。这种模块化架构对于创建代理可以无缝协作的生态系统至关重要。组织还应该开始对其 AI 代理和微控制器的功能进行分类服务在结构化目录中。这些目录应包括元数据和访问策略，使代理能够快速识别并与适当的合作伙伴协作。

除了构建模块化系统和目录之外，组织还必须通过采用标准化通信协议来解决互操作性问题。这可确保不同品牌或生态系统中的代理可以轻松集成，而无需自定义配置。通过关注这些基础要素，企业可以定位自己，以完全接受代理到代理的编排并提供更好的客户体验。

需要注意的障碍
虽然代理编排的好处引人注目，但组织必须解决几个挑战才能释放其潜力。一个重大障碍是确保数据隐私和合规性。当代理协作时，他们必须在严格的界限内运作，只能访问授权信息。强大的治理框架和政策执行对于降低风险和保持信任至关重要。

另一个挑战是克服互操作性差距。许多组织在孤立的环境中运营，系统不是为协同工作而设计的。这种缺乏兼容性可能会阻碍编排所需的无缝集成。最后，企业应为构建编排框架所需的前期投资做好准备，包括基础设施升级、功能目录和标准化 API。这些努力虽然耗费大量资源，但将有助于推动长期成功。

前进的道路
代理编排是人工智能的下一个发展方向。通过将复杂性转化为竞争优势，它使组织能够精准而灵活地满足客户需求。用户不再需要浏览工具或界面——他们可以专注于目标，相信人工智能生态系统会处理细节。

这一愿景最终将我们引向“代理和谐”，代表着人工智能代理动态协作以提供直观有效的结果的未来。这是从管理工具到管理结果的转变，技术充当了隐形助手。随着组织采用这种模式，它们为不仅高效而且对用户来说非常令人满意的人工智能系统铺平了道路。