AI即未来：普通人用好人工智能的18大工作场景 内容简介
这是一本普通人的AI时代指南
编辑推荐
实用落地性强：聚焦文案撰写、客户服务、编程辅助、医疗诊断等 18 个高频工作场景，每个场景均搭配真实案例、具体操作技巧与工具推荐，提供可直接复用的实操方案。
语言通俗易懂：避免晦涩技术术语堆砌，用 “手脚麻利的实习生”等生动比喻解释 AI 特性，将复杂的 Transformer 架构、模型微调等知识转化为通俗表达，非技术背景读者也能轻松理解。
适配多元需求：既满足企业管理者的组织转型规划、创业者的效率提升需求，也适合普通职场人解决具体工作难题，无论是想理解技术本质、优化工作流程，还是探索创新应用，都能找到针对性答案。
案例数据支撑足：包含大量跨行业实证案例（如特斯拉 AI 设计、万事达卡欺诈检测），引用芝加哥大学、麦肯锡、斯坦福大学等机构的研究数据，观点更具说服力。
兼顾深度与通俗性：既有科学知识支撑，又有名人真实案例，不管是心理学爱好者、想提升人际质量的上班族，还是渴望自我成长的普通人，都能轻松读懂、持续受益。
AI即未来：普通人用好人工智能的18大工作场景 作者简介
安东尼奥・韦斯（Antonio Weiss）
拥有伦敦大学伯克贝克学院博士学位。
现任英国历史最悠久的公共服务专业咨询公司PSC高级合伙人；剑桥大学“数字国家”项目附属研究员；托马斯・克利珀公司的联合创始人。
深耕人工智能与数字化转型领域，曾为英国人工智能办公室、英国航天局、英国国家医疗服务体系人工智能实验室及政府数字服务局等核心机构提供战略咨询，并曾任英国首相办公室数字、数据与技术高级顾问。
AI即未来：普通人用好人工智能的18大工作场景 目录
◆目录◆第一部分理解人工智能和它的工作方式
第1章什么是生成式人工智能·········································3
第2章人工智能能为我提供哪些帮助·······························12
第3章数据科学与人工智能快速入门·······························22
第4章不同类型的人工智能模型有哪些····························33
第5章在组织中适配大语言模型·····································51
第6章人工智能：你那位才华横溢却并非完美的伙伴··········64
第7章人工智能实施指南··············································73
第8章评估人工智能模型··············································84
第9章从沙盒试点到企业级应用·····································98
第10章制定卓越的商业决策········································106
第11章人工智能的风险、伦理与可持续性······················113
第12章提升客户满意度的方法·····································126
第13章人工智能法律法规···········································135
第14章人工智能优先时代的职业发展····························143
第15章让组织具备未来适应性·····································151第二部分如何在工作中运用人工智能
第16章创意与构思····················································162
第17章文案撰写·······················································168
第18章图像创作·······················································174
第19章视频制作·······················································181
第20章客户服务与聊天机器人·····································185
第21章语音助手·······················································191
第22章原型设计与新产品开发·····································195
第23章社交媒体·······················································200
第24章市场营销·······················································204
第25章语言翻译·······················································208
第26章软件工程与编程··············································212
第27章欺诈检测·······················································218
第28章演示文稿与幻灯片···········································221
第29章研究内容总结·················································226
第30章会议助手·······················································229
第31章教育领域·······················································233
第32章数据分析·······················································240
第33章医疗健康·······················································245
结语生成式人工智能的未来应用场景······················249
致谢···································································253
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最后修改：2026 年 09 月 19 日
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