[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fL8K3IdvQxpOvYcDdU_zgfKUQYxa4EAdDun6B0recJxI":3},{"code":4,"msg":5,"data":6},200,"操作成功",{"id":7,"title":8,"content":9,"digest":10,"source":10,"coverPath":11,"thumbsCoverPath":12,"isTop":13,"isShow":14,"baseClick":13,"clickCount":15,"createTime":16,"typeId":17,"isNewest":18,"newsInfoTypeRespVo":19,"voiceUrl":22,"voiceSize":23,"taskId":24,"releaseTime":25,"titleEn":26,"contentEn":27,"voiceUrlEn":28,"taskIdEn":29,"voiceSizeEn":30},1540,"“模型祛魅”的AI拐点时刻：从“追逐AGI幻想”转向“理性落地应用”，亚马逊云科技4万个Agent能否跑通落地逻辑?","\u003Cimg alt=\"\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2026\u002F03\u002Fhistory\u002Fc75ae2c49918481ea0db3e69ad6da29f.png\" width=\"710\" height=\"null\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cspan style=\"color: rgb(187, 187, 187); background-color: rgb(56, 56, 56);\">代闻 图片来源：企业供图\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">当MiniMax（稀宇科技）等中国通用人工智能企业加速冲刺上市、国内互联网大厂在AI Agent（人工智能智能体）领域密集落子，全球AI产业正从“模型竞赛”迈入“落地深水区”。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">“AI Agent落地已进入产业拐点，编码开发提效与生产力升级成为两大核心场景。”亚马逊云科技大中华区解决方案架构总经理代闻近日在接受《每日经济新闻》记者采访时表示，当前企业对AI的需求已从“用不用”转向“怎么用”，组织流程重构与工具赋能协同成为落地关键。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">亚马逊云科技正试图用内部超4万个Agent应用的实践验证这一逻辑。但面对中国市场的独特生态，其“模型出海+本地方案”的双线策略，能否与国内玩家共同推动产业进入规模化落地新阶段，仍需时间检验。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Ch2>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">编码开发提效与生产力升级，Agent双线落地\u003C\u002Fspan>\u003C\u002Fh2>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">三年前，行业热议AGI（通用人工智能）何时到来；如今，企业已清晰认识到模型的局限性与差异化价值。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">“没有万能模型，客户更倾向于将自身知识和流程作为核心资产，通过Agent让模型在特定上下文发挥作用。”代闻指出，大数据时代积累的海量数据尚未转化为“知识”，流程梳理也存在诸多痛点，而Agent正是打通这两大环节的关键载体。在企业级场景中，安全控制、合规要求、长短期记忆支撑等工程化问题，已取代模型参数比拼，成为落地核心关注点。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">“当前Agent落地已形成两大高共识场景——编码开发提效与生产力升级。”代闻表示，这一判断背后，是明确的市场需求。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">AI Agent的产业价值已得到市场阶段性验证。Lang Chain发布的《AI Agent工程状态报告》显示，57.3%的受访者已在生产环境中运行AI Agent，其中员工规模超1万人的大型组织采用率高达67%。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">这一趋势在中国市场尤为显著：一方面，MiniMax等专注于大模型与Agent技术的企业启动上市进程，标志着商业化闭环的成熟与资本对赛道的认可；另一方面，国内互联网大厂也在加速布局。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">中国市场因其旺盛需求与独特生态，成为全球巨头的必争之地。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">“把工具直接交到业务部门手里，才能最短路径响应提效需求。”代闻强调，这种“去中间化”的工具交付逻辑，正是应对企业核心痛点的关键。而在开发提效赛道，相关工具的持续升级则聚焦于“从原型到生产级代码”的转化难题——这也是企业级客户落地AI的核心诉求。亚马逊云科技内部超4万个Agent应用的实践，也在试图验证工具与流程协同的核心价值。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">“流程重构与组织变革，才是效能提升的根本。”代闻强调，工具到位而流程不变，终将陷入“开发快、落地慢”的困境。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Ch2>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">拐点已至？从“用不用”到“怎么用”的产业跃迁\u003C\u002Fspan>\u003C\u002Fh2>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">从去年强调“实用性AI”到今年提出“行业拐点”，行业巨头纷纷转向的战略调整背后，是对客户需求与行业趋势的深刻洞察。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">“我们始终坚持Working Backward（逆向工作法），客户认知的成熟正是拐点到来的核心信号。”代闻表示，如今企业对AI的态度已从“追逐AGI幻想”转向“理性落地应用”，模型祛魅之后，如何将技术融入业务场景、激活数据与流程价值，成为核心诉求。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">而Agent调度的核心突破，在于打破了传统ERP（一种管理软件）系统的固定流程限制——无需预设流程即可动态组织工作，人机交互从“人适应软件”转向“软件围绕人设计”，这种灵活性正是企业应对复杂业务场景的关键。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">面对Agent数量激增可能引发的“孤岛问题”，代闻提出了灵活适配的解决方案。“IT组织形式是企业组织的映射，不必强求统一模式。”借鉴DataMesh理念，通过API（应用程序编程接口）实现不同Agent的能力互通，既保留分布式优势，又避免数据与能力割裂。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在中国市场，亚马逊云科技采取“双线并行”策略：一方面通过Amazon Bedrock平台将MiniMaxM2、KimiK2、DeepSeek等中国模型推向全球，满足开发者多元选择需求；另一方面基于自有模型与第三方模型，为本地客户提供深度定制的解决方案。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">代闻强调，无论是模型引入还是方案落地，核心都是帮助客户实现AI的实用价值。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">对于AI可能产生的影响，代闻给出了理性判断：“不同时代有不同的工具与分工，重复性工作将逐步由AI承担，但人的核心价值从未被替代。”\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">他指出，沟通能力、思考能力与明确目标感，将成为AI时代的核心竞争力。“把事情说清楚、提出好问题，背后是强大的思考力量，这正是人的不可替代性所在。”\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">亚马逊云科技与ISV（独立软件开发商）的\u003C\u002Fspan>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">关系也从单纯的技术提供转向共生共赢。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">正如代闻所言，AI拐点的核心不是技术的突变，而是产业认知的成熟与落地能力的提升。在这场从“用不用”到“怎么用”的产业跃迁中，工具、方法论与组织变革的协同，终将让AI成为激活企业核心价值的关键引擎。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(136, 136, 136);\">【新闻来源】每日经济新闻 \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.msn.cn\u002Fzh-cn\u002Fnews\u002Fother\u002Far-AA1STVIn?ocid=msedgntphdr&cvid=694b391ce8d841fab1d1cc9ae54499ac&ei=24\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(136, 136, 136);\"> https:\u002F\u002Fwww.msn.cn\u002Fzh-cn\u002Fnews\u002Fother\u002Far-AA1RTDQy?ocid=BingHp01&cvid=6936317f054647a2afcd53fafcde084a&ei\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(136, 136, 136);\">（本网转发此文章，旨在为读者提供更多的信息资讯，所涉内容不构成投资、消费建议。文章事实如有疑问，请与有关方核实，文章观点非本网观点，仅供读者参考。）\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>","","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F12\u002Fdc4cd205c0a94568a5e7f001ed8e1dc7\u002FAI领域.jpg","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F12\u002Fthumbs\u002Fdc4cd205c0a94568a5e7f001ed8e1dc7\u002FAI领域.jpg",0,1,92,"2025-12-25 09:43",2,false,{"id":17,"name":20,"enName":21},"芯位视野","Xinwei Vision","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3A2e04e80c-c8bb-4377-9c96-4045f5d8fe17%3A0.wav?Expires=1766641673&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=WEKpX7P4NnwzdkxOU9xGaQw2%2Bx0%3D",9950124,"2e04e80c-c8bb-4377-9c96-4045f5d8fe17","2025-12-25 09:39","\"The AI Inflection Point of 'De-mystifying Models': From 'Pursuing AGI Fantasies' to 'Rational Practical Applications', Can Amazon Web Services' 40,000 Agents Prove the Logic of Practical Implementation?","\u003Cimg alt=\"\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2026\u002F03\u002Fhistory\u002Fc75ae2c49918481ea0db3e69ad6da29f.png\" width=\"710\" height=\"null\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cspan style=\"color: rgb(187, 187, 187); background-color: rgb(56, 56, 56);\">Dai Wen, Image Source: Provided by the Company\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">When companies like MiniMax (Xiyu Technology) accelerate their IPOs and major internet companies in China make dense investments in AI Agent (Artificial Intelligence Agent), the global AI industry is moving from \"model competition\" into the \"deep waters of practical implementation\".\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">\"AI Agent implementation has entered an industrial turning point, with code development efficiency improvement and productivity upgrading becoming two core scenarios,\" said Dai Wen, General Manager of Solutions Architecture for Greater China at Amazon Web Services, when recently interviewed by the \"Everyday Financial News\" newspaper. Currently, enterprises' demand for AI has shifted from \"whether to use\" to \"how to use\", with organizational process restructuring and tool empowerment collaboration becoming key factors for successful implementation.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Amazon Web Services is trying to validate this logic through the practice of more than 40,000 internal agent applications. However, with the unique ecosystem of the Chinese market, its dual strategy of \"model export plus local solutions\" can it work together with domestic players to drive the industry into a new phase of large-scale implementation, which still needs time to verify.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Ch2>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Efficiency Improvement in Code Development and Productivity Upgrade, Dual Scenarios for Agent Implementation\u003C\u002Fspan>\u003C\u002Fh2>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Three years ago, the industry was discussing when AGI (General Artificial Intelligence) would arrive; now, enterprises have clearly recognized the limitations and differentiated value of models.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">\"There is no universal model; customers are more inclined to treat their own knowledge and processes as core assets, using agents to enable models to perform in specific contexts,\" Dai Wen pointed out. The massive data accumulated in the big data era has yet to be transformed into \"knowledge\", and process optimization still faces many pain points, while agents are the key carriers to bridge these two aspects. In enterprise-level scenarios, engineering issues such as security control, compliance requirements, and long-term and short-term memory support have replaced the parameter comparison of models, becoming the core focus of implementation.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">\"Currently, the implementation of AI agents has formed two high-consensus scenarios - efficiency improvement in code development and productivity upgrade,\" said Dai Wen. This judgment is based on clear market demand.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The industrial value of AI agents has been verified by the market. According to the \"AI Agent Engineering Status Report\" released by Lang Chain, 57.3% of respondents have already run AI agents in production environments, with the adoption rate among large organizations with over 10,000 employees reaching as high as 67%.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">This trend is particularly significant in the Chinese market: on one hand, companies focusing on large models and agent technologies such as MiniMax have started the IPO process, marking the maturity of commercial closed loops and capital's recognition of the sector; on the other hand, major internet companies in China are also accelerating their layout.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Due to its strong demand and unique ecosystem, the Chinese market has become a battleground for global giants.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">\"To directly deliver tools to business departments is the shortest path to respond to efficiency improvement needs,\" emphasized Dai Wen. This \"de-intermediation\" delivery logic is the key to addressing core enterprise pain points. In the field of development efficiency, the continuous upgrades of related tools focus on the conversion challenge from prototypes to production-grade code - which is also the core demand of enterprise clients for implementing AI. The practical experience of more than 40,000 agent applications within Amazon Web Services also aims to verify the core value of tool and process collaboration.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">\"Process reengineering and organizational change are the fundamental keys to efficiency improvement,\" emphasized Dai Wen. If tools are in place but processes remain unchanged, it will eventually lead to the dilemma of \"fast development, slow implementation\".\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Ch2>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Is the Inflection Point Here? Industrial Transformation from \"Whether to Use\" to \"How to Use\"\u003C\u002Fspan>\u003C\u002Fh2>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">From emphasizing \"practical AI\" last year to proposing \"industry inflection point\" this year, the strategic adjustments made by industry giants reflect a deep understanding of customer needs and industry trends.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">\"We have always adhered to Working Backward (Reverse Work Method), and the maturity of customer cognition is the core signal indicating the arrival of the inflection point,\" said Dai Wen. Now, enterprises' attitude toward AI has shifted from \"pursuing AGI fantasies\" to \"rational practical applications.\" After de-mystifying models, how to integrate technology into business scenarios, activate data and process values, has become the core demand.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The core breakthrough of agent scheduling lies in breaking the fixed process restrictions of traditional ERP (Enterprise Resource Planning) systems - organizing work dynamically without pre-set processes, human-computer interaction shifting from \"people adapting to software\" to \"software designed around people,\" this flexibility is key for enterprises to cope with complex business scenarios.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In response to potential \"island problems\" caused by the surge in agent numbers, Dai Wen proposed a flexible adaptation solution. \"The form of IT organization is a reflection of the enterprise organization; there is no need to force a uniform model.\" Drawing on the DataMesh concept, achieving interoperability between different agents through APIs (Application Programming Interfaces) retains the advantages of distribution while avoiding data and capability fragmentation.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In the Chinese market, Amazon Web Services adopts a \"dual-track approach\": on one hand, through the Amazon Bedrock platform, it pushes Chinese models such as MiniMaxM2, KimiK2, and DeepSeek to the global market to meet developers' diverse needs; on the other hand, based on its own models and third-party models, it provides in-depth customized solutions for local customers.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Dai Wen emphasized that whether it is model introduction or solution implementation, the core is helping customers realize the practical value of AI.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Regarding the possible impact of AI, Dai Wen gave a rational judgment: \"Different eras have different tools and divisions of labor; repetitive tasks will gradually be taken over by AI, but the core value of humans has never been replaced.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">He pointed out that communication ability, thinking ability, and clear goal sense will become the core competitiveness in the AI era. \"Being able to explain things clearly and raise good questions reflects powerful thinking ability, which is precisely where human irreplaceability lies.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The relationship between Amazon Web Services and ISVs (Independent Software Vendors) has also shifted from simple technical provision to mutual growth and win-win outcomes.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">As Dai Wen said, the core of the AI inflection point is not a sudden technological change, but the maturation of industry perception and the enhancement of implementation capabilities. In this industrial transformation from \"whether to use\" to \"how to use,\" the synergy of tools, methodologies, and organizational changes will ultimately make AI the key engine to activate the core value of enterprises.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(136, 136, 136);\">[News Source] Every Day Financial News \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.msn.cn\u002Fzh-cn\u002Fnews\u002Fother\u002Far-AA1STVIn?ocid=msedgntphdr&cvid=694b391ce8d841fab1d1cc9ae54499ac&ei=24\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(136, 136, 136);\"> https:\u002F\u002Fwww.msn.cn\u002Fzh-cn\u002Fnews\u002Fother\u002Far-AA1RTDQy?ocid=BingHp01&cvid=6936317f054647a2afcd53fafcde084a&ei\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(136, 136, 136);\">（This article is forwarded by this website to provide readers with more information and news. The content does not constitute investment or consumption advice. If there are any doubts about the facts of the article, please verify with the relevant parties. The views expressed in the article do not represent the views of this website and are for reference only.）\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3A354b1c48-e49f-4690-842f-55fbe03925a8%3A0.wav?Expires=1774838437&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=mo4p5py9EBy7tXc2KQHCWXWCI7k%3D","354b1c48-e49f-4690-842f-55fbe03925a8",14136504]