当人工智能翻译不再仅依靠提示

When most people think of AI aiding in everyday translation and localization tasks, they still think of large language models and the language technology platforms that use them. Many also have grown used to the idea of writing instructions, or prompts, for a model to execute: type a prompt, and the AI model generates a translation, a summary, or a piece of code. It’s a powerful but passive relationship with AI as another tool, waiting for us to tell it what to do.

Now, new paradigms are emerging: agentic AI and model context protocol (MCP). The combination is a shift from reactive tools and disparate tasks to a more autonomous AI localization process, where the AI acts as a collaborator that, unlike traditional AI, can make decisions.

提到帮助自己完成日常翻译和本地化任务的人工智能（AI）时，多数人脑海里浮现的仍是大型语言模型，以及基于这些模型搭建的语言技术平台。不少人也早已习惯了为模型编写指令或提示词，让其执行任务的模式：输入提示词，AI模型就会生成译文、摘要或一段代码。这种跟AI的互动虽高效但被动，毕竟AI只是一件工具，只会等着我们发号施令。如今，新的范式正在出现：代理人工智能和模型上下文协议(MCP，一个开放协议，为 AI 模型连接各种数据源和工具提供了标准化的接口) 。这种结合意味着转变——从被动工具和不同任务转为更加自主的人工智能本地化过程——与传统AI不同，AI扮演着协作者的角色，能够自行做出决策。

While AI agents reason, plan, and take the initiative to execute complex, multi-step mandates with minimal supervision, MCP is the cherry on top ensuring that context, that elusive yet essential language AI element, is done right in translation.

人工智能体（AI agents）能够推理、规划，并在极少人工监督的情况下主动执行复杂的多步骤任务；而MCP则起到了 “锦上添花” 的关键作用——确保 “上下文（context）” 这一人工智能领域中难以把控却又至关重要的要素，进行准确的翻译工作。

For the localization industry, this combination is more than just another set of AI upgrades: it’s a fundamental, transformative innovation. Agentic AI doesn’t just translate text; it understands the entire localization workflow. It can navigate code repositories, check design mockups, and apply nuanced brand guidelines and context, aided by MCP —all to ensure that a translation isn’t just accurate but contextually precise.

对本地化产业而言，这绝非又一套AI升级方案，而是一项根本上的变革性创新。代理人工智能不仅能翻译文本，更通晓整个本地化工作流程。在MCP的帮助下，它能浏览代码库，检查设计原型图，落实精细化的品牌规范，并结合上下文展开工作——所有这些都是为了确保翻译不仅准确，而且符合语境。

Crowdin (a leading AI-powered localization platform designed to accelerate the management of multilingual content) has implemented Agentic AI to give localization managers and linguists an intelligent partner that can automate repetitive tasks while enhancing the overall quality and consistency of their work.

Crowdin (一个行业领先的人工智能驱动型本地化平台，致力于提升多语言内容管理效率)已落地代理人工智能技术，为本地化经理和语言学家提供了一个智能合作伙伴。代理人工智能可以自动化处理重复性任务，又能同步提升工作的整体质量和一致性。

Here’s how this next-gen approach is changing the game:

以下是这种下一代代理人工智能改变未来的方式：

• Agentic AI boosts efficiency by automating several steps, from      initial translation to final quality assurance (QA) checks, freeing up      valuable time.

• 代理人工智能可以自动化处理从初始翻译到最终质量保证 (QA) 检查的多个环节，提高效率，从而节省出宝贵的时间。

• By actively seeking the right context, the AI agent provides      translations that are more consistent and accurate, helping to maintain a      brand’s unique voice across all languages.

• 人工智能体会主动获取合适语境，输出更一致、更准确的译文，帮助品牌在所有语言中保持独特调性。

• Managers can now tackle new languages and high-volume projects,      scaling localization operations without needing a proportional increase in      human resources

• 经理们如今可以承接新语言项目和高体量任务，无需按比例增加人力即可实现本地化业务的扩容。

• Agentic AI continuously learns from human feedback and market      data, helping localization teams adapt and refine translations to create      content with a stronger local relevance.

• 代理人工智能不断从人类反馈和市场数据中学习，从而帮助本地化团队调整和完善翻译，进而创造出更与本地适配的内容。

Agentic AI effectively allows localization managers to transition from task-oriented work to strategic leadership and oversight throughout the entire localization workflow, doing a lot more in a lot less time.

借助代理人工智能，本地化经理能有效从任务导向型工作，转型为贯穿整个本地化工作流程的战略性领导和监督，进而用更少时间完成更多工作。

While the potential of agentic AI is immense, it’s not a “plug-and-play” solution, especially in its experimental phase. Crowdin emphasizes the need for careful configuration to get the best results. Users must provide precise, customized rules to guide the AI. Lack of proper guidance can lead to slow responses and unusable output.

尽管代理人工智能的潜力巨大，但它不是一个“即插即用”的解决方案，特别是在其实验阶段。Crowdin强调，要想发挥其最大价值，必须进行细致配置。用户必须提供精准、定制化的规则来引导人工智能。若缺乏适当的指导，AI反应会变得缓慢，其产出内容也无法使用。

For enterprises, the security of sensitive content is paramount. Crowdin addresses this by prioritizing data ownership and privacy. Users can rely on their own API keys for leading AI providers, and Crowdin has secured contracts with its AI partners to ensure that your data is not used to train or improve their models. This guarantees that your information remains confidential.

对于企业来说，敏感内容的安全性是最重要的。Crowdin通过优先考虑数据所有权和隐私来解决这个问题。用户可以依靠自己的API密钥（用于身份验证和授权的安全凭证）享受领先人工智能提供商的服务，Crowdin已经与人工智能合作伙伴签订了保密协议，以确保用户数据不会被用来训练或优化其模型。这保证了用户信息的保密性。

The ideal outcome is not to replace human experts but to empower them with AI collaborators. Agentic AI can handle tedious tasks that consume much of a localization professional’s time, allowing them to productively focus on the creative, strategic, and culturally nuanced aspects of their work.

代理人工智能的理想价值不是取代人类专家，而是借助人工智能这一协作者为人类赋能。它可以处理耗费本地化专业人员大量时间的繁琐任务，使他们能够把精力聚焦在工作中的创意输出、战略规划以及文化层面的细微差异把控上。

The era of agentic AI is here, and it should be understood as a partnership —a collaboration between human expertise and a truly intelligent system.

代理人工智能时代已经来临，而我们应将其视为一种伙伴关系——一种人类专业能力与真正智能系统之间的深度协作。

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