(번역) 2025년 가장 주목할 AI Agent 사례는?

𝗪𝗵𝗮𝘁 𝗮𝗿𝗲 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗰𝗼𝗺𝗺𝗼𝗻 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀 𝗶𝗻 2025? Given the pace of adoption, one thing is clear: In 12 months, every enterprise workflow will involve AI agents. Not might. Not could. Will. So it’s worth taking a closer look at how this is already playing out. Here are some of the most common and impactful AI agent use cases we’re seeing across industries in 2025. Let's break it down: ⬇️ 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚: Retrieval-Augmented Generation reimagined. These agents don’t just retrieve knowledge — they evaluate sources, reason over them, and produce contextually grounded answers. Used for internal knowledge assistants, intelligent documentation, and enterprise Q&A. Examples: IBM watsonx, Perplexity AI, Glean etc. 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗔𝗴𝗲𝗻𝘁𝘀: These agents orchestrate tasks across systems. Triggered by APIs, UI actions, or internal events, they can perform multi-step processes without human involvement. Think automated onboarding flows, approvals, or back-office operations. Very easy to build for everybody. Examples: Make.com, Flowise, n8n, Relevance AI etc. 𝗖𝗼𝗱𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁𝘀: AI-powered development assistants that go beyond code suggestions. These agents can plan, refactor, debug, and even reason across repositories. Ideal for accelerating software engineering teams or bootstrapping prototypes. Examples: Cursor, Roo Code, Windsurf etc. 𝗧𝗼𝗼𝗹-𝗕𝗮𝘀𝗲𝗱 𝗔𝗴𝗲𝗻𝘁𝘀: Niche, high-utility agents designed to perform well-defined tasks with specific tools — from sending emails to querying internal search engines. These agents are easy to deploy and integrate into targeted workflows. Examples: Breeze, Clay etc. 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗨𝘀𝗲 𝗔𝗴𝗲𝗻𝘁𝘀: The most ambitious — and most misunderstood. These agents don’t just call APIs. They use the UI. Navigating browsers. Typing into forms. Clicking buttons. Agents that act like humans, powered by models like Claude and GPT-4. 𝗩𝗼𝗶𝗰𝗲 𝗔𝗴𝗲𝗻𝘁𝘀: Where GenAI meets the phone line. These agents handle support calls, internal queries, and sales outreach... all with voice. Examples: ElevenLabs, Vapi, and others etc. This isn’t theoretical — it’s already happening. AI agent use cases are rapidly maturing, moving from prototypes to production across industries. And if your strategy still revolves around chatbots, you’re already behind. 𝗧𝗵𝗲 𝗻𝗲𝘅𝘁 12 𝗺𝗼𝗻𝘁𝗵𝘀 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗱𝗲𝗳𝗶𝗻𝗲𝗱 𝗯𝘆 𝘁𝗵𝗼𝘀𝗲 𝘄𝗵𝗼 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝗵𝗼𝘄 𝘁𝗼 𝗱𝗲𝘀𝗶𝗴𝗻, 𝗰𝗼𝗺𝗯𝗶𝗻𝗲, 𝗮𝗻𝗱 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝘁𝘆𝗽𝗲𝘀 𝗼𝗳 𝗮𝗴𝗲𝗻𝘁𝘀 𝗶𝗻𝘁𝗼 𝗿𝗲𝗮𝗹, 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀. 𝗧𝗵𝗶𝘀 𝗶𝘀 𝘄𝗵𝗲𝗿𝗲 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗯𝘂𝗶𝗹𝘁. Kudos to Rakesh Gohel for this excellent visualization! | 19 comments on LinkedIn