用自然语言自动生成业务流程，让非专业人士也能轻松实现自动化
From Words to Workflows: Automating Business Processes
- 通过大语言模型将用户描述转化为可执行的JSON流程
- 支持任意业务场景的自动化，无需专家编程知识
- 适合希望快速部署自动化但缺乏技术团队的企业
随着企业越来越多依赖自动化优化运营，传统机器人流程自动化（RPA）的局限性日益凸显，尤其体现在对专家知识的依赖以及处理复杂决策任务的能力不足。人工智能（AI），特别是生成式AI（GenAI）和大语言模型（LLMs）的发展，为智能自动化（IA）提供了可能，使其具备认知能力以弥补RPA的缺陷。本文提出Text2Workflow，一种从自然语言用户请求自动构建工作流的新方法。与传统自动化方式不同，Text2Workflow提供了一种通用解决方案，能将用户输入转换为以JavaScript对象表示法（JSON）格式呈现的可执行步骤序列。该方法利用大语言模型的决策能力和指令遵循能力，构建了一个可扩展、可适应的框架，使用户能够以最少的人工干预可视化并执行工作流。本研究详细阐述了Text2Workflow的方法论及其在自动化复杂业务流程方面的广泛影响。
原文摘要 · Abstract (English)
As businesses increasingly rely on automation to streamline operations, the limitations of Robotic Process Automation (RPA) have become apparent, particularly its dependence on expert knowledge and inability to handle complex decision-making tasks. Recent advancements in Artificial Intelligence (AI), particularly Generative AI (GenAI) and Large Language Models (LLMs), have paved the way for Intelligent Automation (IA), which integrates cognitive capabilities to overcome the shortcomings of RPA. This paper introduces Text2Workflow, a novel method that automatically generates workflows from natural language user requests. Unlike traditional automation approaches, Text2Workflow offers a generalized solution for automating any business process, translating user inputs into a sequence of executable steps represented in JavaScript Object Notation (JSON) format. Leveraging the decision-making and instruction-following capabilities of LLMs, this method provides a scalable, adaptable framework that enables users to visualize and execute workflows with minimal manual intervention. This research outlines the Text2Workflow methodology and its broader implications for automating complex business processes.
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