[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fjHSmfyGJnP7OrTJ2VS_7sTRZf-tBVLoESomjfEF8gdo":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},1495,"2025年人工智能的现状：智能体、创新和转型","\u003Cp>\u003Cstrong style=\"color: rgb(255, 153, 0); font-size: 18px;\">距离生成式AI掀起技术浪潮已过去三年，2025年的人工智能行业正呈现出“高普及、浅渗透、新突破”的鲜明格局。调研显示，AI已从企业“可选工具”变为“标配能力”，而以AI智能体为代表的新技术、以业务重构为核心的新模式，正推动行业从工具应用向价值创造的深层转型。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">2025年的AI应用版图，首先被高普及率的数字刷新。数据显示，88%的组织已在至少一个业务职能中常态化使用AI，较2024年的78%提升10个百分点。超七成组织将AI扩展至两个及以上职能，半数组织覆盖三个或更多业务模块，这一进展相较2021年实现了跃升式突破。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">从行业分布看，技术、媒体与电信、保险行业的AI使用率率先突破90%，成为应用第一梯队。知识管理、市场营销与销售、IT服务是AI落地最成熟的三大领域，覆盖了企业日常运营的核心链路。比如在市场营销场景，67%的受访者反馈实现了可量化的收入增长；而在软件工程领域，56%的企业收获了显著的成本下降。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">但高普及率的背后，是“广度有余、深度不足”的现实。近三分之二的组织仍停留在AI实验与试点阶段，仅31%迈入企业级规模化应用，真正实现AI与核心业务深度集成的比例不足5%。企业规模的差距进一步拉大这一鸿沟：年收入50亿美元以上的大型企业中，49%已完成AI规模化部署；而收入低于1亿美元的中小企业，这一比例仅为29%。大企业的基础设施、人才储备优势，让其在AI落地中占据了绝对主导地位。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">2025年AI领域的最大创新亮点，当属AI智能体的崛起。作为依托基础模型、能自主规划并执行多步骤任务的新一代系统，AI智能体正成为企业数字化转型的新抓手。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">数据显示，62%的受访者所在组织已启动AI智能体的相关探索，其中23%已在至少一个业务职能中实现规模化应用，39%仍处于试验阶段。从落地场景看，IT与知识管理是智能体的主战场：IT服务台的自动化工单处理、知识管理中的深度内容生成与检索，已成为相对成熟的实践案例。技术、媒体与电信、医疗健康行业则领跑智能体的行业应用，展现出替代重复性流程、提升复杂任务效率的潜力。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">不过智能体的普及仍受限于应用范围。即便是已规模化落地的企业，其智能体部署也大多集中在一到两个职能，全企业范围的智能体协同尚未形成气候。智能体的行业热度与实际落地成效之间，仍存在显著差距。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">AI对企业的价值贡献，正从单一的降本增效转向创新与增长的多元维度。64%的受访者认为AI提升了组织创新能力，具体表现为产品研发周期缩短、营销创意产出提速；45%的企业反馈AI改善了员工与客户双端体验，重复性工作占比下降、智能客服响应时间大幅缩减。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">从财务价值看，AI的成效仍呈现“点状突破”特征。仅39%的组织表示AI对EBIT（息税前利润）产生影响，且超80%的组织中，AI贡献的EBIT占比不足5%。但这一局面在6%的AI高绩效企业中被打破，这类企业不仅实现AI贡献EBIT超5%，更构建了差异化的AI落地路径。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">高绩效企业的成功逻辑，与普通企业形成鲜明对比。普通企业中80%将降本与流程自动化作为AI核心目标；而高绩效组织中，84%仍强调效率优化，同时82%将营收增长、79%将业务创新纳入AI战略体系。55%的高绩效企业会基于AI重构核心业务流程，这一比例是普通组织的2.8倍；35%的高绩效企业将超20%的数字预算投入AI，是普通企业的近5倍。高层的深度参与更是关键：39%的高绩效企业有高管“强烈认可”AI项目所有权，这一比例是普通企业的3倍。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">AI对企业劳动力的影响呈现分化态势。32%的受访者预计企业总员工数将因AI减少，43%认为无明显变化，13%则预期员工规模会因AI新业务拓展而增加。大型企业因自动化空间大更倾向于人员精简，中小企业则因AI应用范围有限，对人员规模影响较小。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">AI相关人才需求持续旺盛。软件工程师、数据工程师、机器学习工程师成为最紧缺岗位，大型企业还在积极招聘AI数据科学家、AI产品经理等高端角色。更重要的是，AI正推动现有岗位的技能重构：传统客服需要掌握AI工具的信息检索能力，传统财务岗需具备AI数据分析素养。调研强调，未来的工作核心是“人机协作”，而非“人机对抗”。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">2025年的AI行业，正站在从工具普及到价值深耕的关键节点。高普及率搭建了行业基本盘，AI智能体打开了技术新空间，而少数高绩效企业的实践，则为行业的深度转型提供了可复制的参考范式。\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>\u003Cspan style=\"color: rgb(136, 136, 136);\">【新闻来源】商业新知 \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.msn.cn\u002Fzh-cn\u002Fnews\u002Fother\u002Far-AA1RRDMT?ocid=BingHp01&cvid=6936317f054647a2afcd53fafcde084a&ei\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(136, 136, 136);\">https:\u002F\u002Fwww.msn.cn\u002Fzh-cn\u002Fnews\u002Fother\u002Far-AA1RRDMT?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>","","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F12\u002F73337e4549d54c08a7e6f600b1075ad7\u002Fd3ceb214-e320-4d27-b9ff-62bd5ab11fa0.jpg","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F12\u002Fthumbs\u002F73337e4549d54c08a7e6f600b1075ad7\u002Fd3ceb214-e320-4d27-b9ff-62bd5ab11fa0.jpg",0,1,52,"2025-12-09 15:21",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%3A11584184-2d53-44dd-8ba7-011422c88db4%3A0.wav?Expires=1765300062&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=RFhj0EV%2B1jtZorXs9f1qhoVAz3s%3D",10151488,"11584184-2d53-44dd-8ba7-011422c88db4","2025-12-09 15:02","2025 Status of Artificial Intelligence: Agents, Innovation and Transformation","\u003Cp>\u003Cstrong style=\"color: rgb(255, 153, 0); font-size: 18px;\">Three years have passed since generative AI triggered a technological wave, and the artificial intelligence industry in 2025 is showing a distinct pattern of \"high penetration, shallow integration, and new breakthroughs.\" Research shows that AI has evolved from an \"optional tool\" for enterprises to a \"standard capability,\" and new technologies represented by AI agents and new models centered on business restructuring are driving the industry's deep transformation from tool application to value creation.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">The landscape of AI applications in 2025 was first refreshed by high adoption rates. Data shows that 88% of organizations are using AI on a regular basis in at least one business function, up 10 percentage points from 78% in 2024. Over 70% of organizations have expanded AI to two or more functions, while half of the organizations cover three or more business modules, marking a leap-like breakthrough compared to 2021.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">Looking at industry distribution, AI usage rates in technology, media and telecommunications, and insurance industries have first exceeded 90%, becoming the first tier of applications. Knowledge management, marketing and sales, and IT services are the three most mature fields for AI implementation, covering core links of enterprise daily operations. For example, in marketing scenarios, 67% of respondents reported achieving quantifiable revenue growth; while in the software engineering field, 56% of companies achieved significant cost reductions.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">However, behind the high adoption rate lies the reality of \"wide breadth but limited depth.\" Nearly two-thirds of organizations remain in the stage of AI experiments and pilot projects, with only 31% entering enterprise-level large-scale application, and less than 5% truly achieving deep integration of AI with core businesses. The gap between enterprises of different sizes further widens this divide: 49% of large enterprises with annual revenues over $5 billion have completed AI scale deployment, while the proportion for small and medium-sized enterprises with revenues below $1 billion is only 29%. Large enterprises' infrastructure and talent reserves give them an absolute dominant position in AI implementation.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">The biggest innovation highlight in the AI field in 2025 is the rise of AI agents. As a new generation system based on foundational models that can independently plan and execute multi-step tasks, AI agents are becoming a new lever for enterprise digital transformation.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">Data shows that 62% of respondents' organizations have started exploring AI agents, with 23% already implementing large-scale applications in at least one business function, and 39% still in the testing phase. From the perspective of practical scenarios, IT and knowledge management are the main battlegrounds for agents: automated ticket processing in IT service desks and deep content generation and retrieval in knowledge management have become relatively mature practice cases. Technology, media and telecommunications, and healthcare industries lead in the industry application of agents, demonstrating the potential to replace repetitive processes and improve the efficiency of complex tasks.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">However, the popularity of agents is still limited by the scope of application. Even among enterprises that have implemented agents on a large scale, their agent deployments are mostly concentrated in one or two functions, and full-scale agent collaboration across the enterprise has not yet taken shape. There remains a significant gap between the industry enthusiasm for agents and their actual implementation effectiveness.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">The value contribution of AI to enterprises is shifting from single cost reduction and efficiency improvement to multiple dimensions of innovation and growth. 64% of respondents believe that AI enhances organizational innovation capabilities, specifically manifested in shortened product development cycles and accelerated marketing creativity output; 45% of enterprises report that AI improves the experience of both employees and customers, with a decreased proportion of repetitive work and significantly reduced response times for intelligent customer service.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">From a financial value perspective, the effectiveness of AI still exhibits a \"point breakthrough\" characteristic. Only 39% of organizations indicate that AI has affected EBIT (earnings before interest and taxes), and in over 80% of organizations, the EBIT contribution from AI is less than 5%. However, this situation is broken by 6% of high-performing AI enterprises, which not only achieve EBIT contributions exceeding 5% from AI but also build differentiated AI implementation paths.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">The success logic of high-performing enterprises contrasts sharply with that of ordinary enterprises. In ordinary enterprises, 80% regard cost reduction and process automation as core goals for AI; while in high-performing organizations, 84% still emphasize efficiency optimization, and 82% include revenue growth, and 79% include business innovation in their AI strategy systems. 55% of high-performing enterprises restructure core business processes based on AI, a ratio 2.8 times higher than that of ordinary organizations; 35% of high-performing enterprises invest more than 20% of their digital budget in AI, nearly five times that of ordinary enterprises. The deep involvement of senior leadership is also key: 39% of high-performing enterprises have executives who strongly endorse AI project ownership, a proportion three times that of ordinary enterprises.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">The impact of AI on enterprise workforce is showing a divided trend. 32% of respondents expect the total number of employees in the company to decrease due to AI, 43% believe there will be no significant change, and 13% expect the employee size to increase due to AI-driven new business expansion. Large enterprises, due to greater automation potential, tend to reduce staff, while small and medium-sized enterprises, due to limited AI application scope, have less impact on staff size.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">Demand for AI-related talent continues to be strong. Software engineers, data engineers, and machine learning engineers have become the most scarce positions, and large enterprises are actively hiring high-level roles such as AI data scientists and AI product managers. More importantly, AI is driving the skill restructuring of existing positions: traditional customer service representatives need to master information retrieval capabilities using AI tools, and traditional finance positions require AI data analysis literacy. The survey emphasizes that the core of future work is \"human-machine collaboration,\" not \"human-machine confrontation.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">In 2025, the AI industry is standing at a critical juncture from tool proliferation to value deepening. High adoption rates have built the industry's basic foundation, AI agents have opened up new technical space, and the practices of a few high-performing enterprises provide replicable reference models for the industry's deep transformation.\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>\u003Cspan style=\"color: rgb(136, 136, 136);\">[News Source] Business Insight \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.msn.cn\u002Fzh-cn\u002Fnews\u002Fother\u002Far-AA1RRDMT?ocid=BingHp01&cvid=6936317f054647a2afcd53fafcde084a&ei\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(136, 136, 136);\">https:\u002F\u002Fwww.msn.cn\u002Fzh-cn\u002Fnews\u002Fother\u002Far-AA1RRDMT?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 questions about the facts of the article, please verify with relevant parties. The views expressed in the article are not the views of this website and are for reference only.）\u003C\u002Fspan>\u003C\u002Fp>","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3A82319818-cdbb-438c-a2f9-2d3d25193db0%3A0.wav?Expires=1774838445&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=yQZ%2BFEXKD32RMdroN9eZDXIo2Zo%3D","82319818-cdbb-438c-a2f9-2d3d25193db0",13967350]