[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f-tzt7VDVzz7fmbw8gOfxU9BggoD9b5LhdbpcWBinqWY":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":13},1283,"前程无忧发布《2025企业AI应用概况调查报告》：7大核心结论与避坑指南","\u003Cp class=\"ql-align-justify\">\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">7月28日，2025世界人工智能大会暨人工智能全球治理高级别会议在上海落幕。本次大会再次凸显了人工智能作为驱动产业变革核心引擎的重要地位，其与实体经济的融合正持续深化，深刻赋能包括人力资源在内的各个领域。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">为深入了解AI技术在企业，特别是在人力资源管理领域的实际应用现状、发展趋势及核心需求，前程无忧近期面向数百家企业发起专项调查，并正式发布《2025企业AI应用概况调查报告》（以下简称《报告》），旨在从专业HR视角，揭示当前企业应用AI的真实图景与未来方向。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">01 企业AI普及率低但前景乐观 规模企业仍有较大提升空间 \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">《报告》显示，受访企业AI应用比例仅约40.0%。74.6%的受访企业员工规模超200人，意味着规模较大企业中AI普及仍有空间。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002Fa2055a7c382b45688fc7ee63b9c9ef45\u002Fd460e7683726bc93bf0c554b9f0e4d64.png\" width=\"750\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">行业间AI技术渗透率差异明显。制造业与零售业的AI应用率超半数，得益于生产流程智能化改造和客户服务自动化等场景中，AI技术具备高适配性与落地可行性；而金融业作为信息高度密集型行业，AI 应用率仅16.7%，远低于本次调查均值。其\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">高技术门槛、场景适配复杂性及严苛安全性要求，构成AI大规模应用的多重壁垒\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">，尤其是AI加剧的网络安全风险，对金融行业形成严峻挑战。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">人员接受度上，此前前程无忧面向C端的AI使用调查中也发现，年轻从业者推动AI工具高频使用，管理层因业绩压力及技术不确定性，对AI投资持审慎态度。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">新兴技术规模化应用周期漫长，企业引入AI需构建技术能力、开发适配程序。\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">尽管当前AI普及率待提升，但基于其创新潜力与企业发展需求，未来在企业领域的广泛部署趋势仍被看好。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">02 提升效益是企业引入AI主因 但面临诸多挑战 \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">企业选择AI时最关注“提升企业效益”“AI技术成熟度与可靠性”“智能化趋势” 三大要点。增效是首要诉求，渗透于全业务链，但面临技术应用深水区挑战，即AI与核心业务流程衔接松散，系统化整合不足。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">值得注意的是，81.8%的受访企业忽略人机协同，仅42.9%的跨国公司关注 “友好合作”，而AI融入业务需复杂的封闭数据训练及专业协同人才。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">50%的受访企业因“不安全感”引入AI，超七成国企与跨国企业认可智能化趋势。\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">面对AI冲击，尽管许多企业并没有清晰规划如何将其深度融合业务，但已有“不发展即风险”的共识。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002Fb303e4a611734910bf5b6537accd8a12\u002Fbbc5a3ec98b4ffc8adc63349f104f461.png\" width=\"776\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">68.2%的受访企业认为AI能大幅降低一线人力成本，通过大模型基座与领域数据训练实现业务初级融合，但尚未改变底层商业逻辑。79.1%的企业认为AI比人更易管理，却面临技术可行性、系统稳定性、合规性等风险，生成式AI的模型偏差、“AI幻觉”等问题凸显技术成熟度的重要性。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在效能表现上，\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">49.1%的受访企业通过AI工具实现局部提效，以“优化现有流程”为主，而非颠覆式创新。\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">调查显示，15.3%的受访民营企业认为AI提效效果不明确，高于13.9% 感知到颠覆性提升的比例，且显著高于跨国企业（2.7%）和国有企业（1.1%）的同类占比。多数民营企业仍困于AI应用瓶颈，组织架构、人才储备等能力建设滞后，数据治理体系薄弱制约算法效能发挥。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">03 AI应用行业分化显著 重构部分企业管理决策模式 \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">AI技术在企业端的应用已突破早期试验阶段，\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">52.7%的受访企业能借助AI开展业务，但行业之间技术落地深度存在结构性分化。\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">机械制造（66.7%）、教育文娱（75%）、快消零售（68.8%）应用较广，而制药医疗（66.7%）、金融业（83.3%）、计算机电气通信（60%）面临阻碍，主因在于“企业级AI战略模棱两可、短视或不存在”“松散定义的运营模式和治理”“对风险的理解不足:AI引入了独特的风险，从AI幻觉到偏见和知识产权保护”等因素。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002F7e7e7fa4deae4ec2b3fc397a202905e0\u002F47d41962727f34443f8a56598591e90f.png\" width=\"797\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">从职能看，\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">综合管理类（31.8%）、客户服务与销售类（21.8%）、技术研发类（20.9%）受AI影响最大。\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">行业应用侧重不同：智能制造聚焦生产环节，制药医疗与金融业集中于综合管理，快消零售侧重技术研发与支持。企业正在将AI技术应用于可以产生最大综合价值的地方。这推动管理岗位从“经验型权威”向“数据型领导力”转型，AI正重构决策底层逻辑，缓解 VUCA(易变、不确定、复杂、模糊)时代的认知偏差与信息滞后问题。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">人才层面，\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">64.5%的受访企业将AI素养视为招聘辅助因素，非技术岗位（如销售、行政）仍以行业知识、沟通技能等为核心能力\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">，反映企业更关注员工核心技能与适应性，而非单一AI素养。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">04 AI改写HR生态与人才战略 企业应重视协同发展 \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">AI 对人力资源管理的影响正从“工具辅助”迈向“能力重构”，具备“AI技术敏感度、业务场景理解力、战略价值创造力”的HR人才，将成为企业数字化转型的关键力量。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">72.7%的HR从业者认可AI大幅降低事务性工作负担\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">，\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">但也面临技能升级、AI专项培训和人员优化等挑战。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">不同行业受AI影响呈现显著差异。计算机\u002F通信、半导体等AI高敏行业率先突破，设立“技术洞察官”岗位，聚焦AI人才画像建模与智能组织诊断。金融、快消零售等服务业差异化适配：金融业因合规风险优先，AI应用聚焦“可解释性、可控性、可追溯性”；零售业以效率提升为先，侧重“动态响应、成本优化、体验平衡”，实现技术与行业特性深度融合。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002F70f099d943104a638aa5c4fa07b4befd\u002Fa58a1217eadebf12cb6a26a4e4f8b064.png\" width=\"795\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">企业性质也决定了AI 转型策略。国有企业依托体制优势，55.6%开展全员数字素养培训；\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">民营企业追求效能，借助AI面试官降本并重塑岗位技能；\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">跨国企业更倾向渐进式变革，构建AI能力共享平台。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在行业层面，制造业、地产\u002F建筑等劳动密集型领域因数字化转型尚处早期，采取“技术嵌入 +人力补充”策略；计算机、能源化工原材料等技术驱动型行业则加速结构性调整，计算机\u002F通信行业40%的受访企业计划启动专项优化。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">《报告》显示，\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">78.2%的受访企业认为 AI 给员工带来的机遇大于挑战，未来企业竞争力取决于“人力-技术”协同能力。\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">尽管 AI 对员工留存率影响有限，62.7%的受访企业表示短期内员工数量不会改变，但技能断层引发的隐性淘汰风险仍需警惕。\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 class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">【新闻来源】前程无忧51job \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.hrloo.com\u002Fnews\u002F347084.html\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">https:\u002F\u002Fwww.hrloo.com\u002Fnews\u002F347084.html\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（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\u002F08\u002F1d25c5991a4d4ba1a7ebb3551a350800\u002FAI领域.jpg","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002Fthumbs\u002F1d25c5991a4d4ba1a7ebb3551a350800\u002FAI领域.jpg",0,1,220,"2025-08-27 09:18",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%3Aec42f875-6490-4cb1-9d2b-ecf2012191a1%3A0.wav?Expires=1756263076&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=%2BMrf5%2Bl8J4QhsiONDyJOb%2Ftx%2BO8%3D",13300266,"ec42f875-6490-4cb1-9d2b-ecf2012191a1","2025-08-27 09:12","Qiancheng Wuyou released the \"2025 Enterprise AI Application Overview Survey Report\": 7 Core Conclusions and Pitfall Guide","\u003Cp class=\"ql-align-justify\">\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">On July 28, the 2025 World Artificial Intelligence Conference and the High-level Meeting on Global Governance of Artificial Intelligence concluded in Shanghai. This conference once again highlighted the important position of artificial intelligence as a core engine driving industrial transformation. Its integration with the real economy is continuously deepening, profoundly empowering various fields including human resources.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In order to gain a deeper understanding of the actual application status, development trends, and core needs of AI technology in enterprises, especially in the field of human resources management, Qiancheng Wuyou recently launched a special survey targeting hundreds of enterprises, and officially released the \"2025 Enterprise AI Application Overview Survey Report\" (hereinafter referred to as the \"Report\"), aiming to reveal the true picture and future direction of enterprise AI applications from the professional HR perspective.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">01 Low AI Penetration Rate in Enterprises but Optimistic Prospects Large Enterprises Still Have Room for Improvement \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The report shows that the proportion of enterprises applying AI is only about 40.0%. 74.6% of the surveyed enterprises have more than 200 employees, meaning that there is still room for AI penetration among large enterprises.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002Fa2055a7c382b45688fc7ee63b9c9ef45\u002Fd460e7683726bc93bf0c554b9f0e4d64.png\" width=\"750\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">There are significant differences in AI technology penetration rates across industries. The AI application rate in manufacturing and retail exceeds half, thanks to the high adaptability and feasibility of AI technology in scenarios such as intelligent production process upgrades and automated customer service; while the financial industry, as an information-intensive industry, has an AI application rate of only 16.7%, far below the average of this survey. Its\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">high technical barriers, complex scenario adaptation, and strict security requirements form multiple barriers to large-scale AI application\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">, especially the cybersecurity risks intensified by AI, which pose serious challenges to the financial industry.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In terms of personnel acceptance, previous surveys by Qiancheng Wuyou on AI usage for C-end users also found that young professionals drive the frequent use of AI tools, while management teams maintain a cautious attitude towards AI investment due to performance pressure and technological uncertainty.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The large-scale application of emerging technologies takes a long time, and enterprises need to build technical capabilities and develop suitable programs when introducing AI.\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Although the current AI penetration rate needs improvement, based on its innovative potential and enterprise development needs, the widespread deployment trend in the enterprise sector is still optimistic.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">02 Improving Efficiency is the Main Reason for Enterprises to Introduce AI but Facing Many Challenges \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">When enterprises choose AI, they focus most on \"improving enterprise efficiency,\" \"maturity and reliability of AI technology,\" and \"intelligent trend.\" Efficiency enhancement is the primary demand, permeating the entire business chain, but facing challenges in the deep water zone of technology application, that is, the loose connection between AI and core business processes, and insufficient systematic integration.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">It is worth noting that 81.8% of the surveyed enterprises ignore human-machine collaboration, and only 42.9% of multinational companies pay attention to \"friendly cooperation,\" while AI integration into business requires complex closed data training and professional collaborative talents.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">50% of the surveyed enterprises introduced AI due to a sense of insecurity, and more than 70% of state-owned enterprises and multinational corporations recognized the intelligent trend.\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Faced with AI impact, although many enterprises do not have a clear plan for how to deeply integrate it into their business, there is a consensus that \"not developing is a risk.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002Fb303e4a611734910bf5b6537accd8a12\u002Fbbc5a3ec98b4ffc8adc63349f104f461.png\" width=\"776\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">68.2% of the surveyed enterprises believe that AI can significantly reduce frontline labor costs, achieving initial business integration through large model bases and domain data training, but it has not changed the underlying business logic. 79.1% of enterprises believe that AI is easier to manage than humans, but face risks such as technological feasibility, system stability, and compliance. Issues such as model bias in generative AI and \"AI hallucinations\" highlight the importance of technological maturity.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In terms of performance, \u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">49.1% of the surveyed enterprises achieved partial efficiency improvements through AI tools, mainly optimizing existing processes, rather than disruptive innovation.\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The survey found that 15.3% of the surveyed private enterprises consider the effectiveness of AI unclear, higher than the proportion of those perceiving disruptive improvement (13.9%), and significantly higher than the similar proportions of multinational enterprises (2.7%) and state-owned enterprises (1.1%). Most private enterprises are still constrained by AI application bottlenecks, with lagging capacity building in organizational structure and talent reserves, and weak data governance systems limiting algorithm efficiency.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">03 Significant Industry Differentiation in AI Applications Reconstructing Certain Management Decision-Making Models \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The application of AI technology in enterprises has gone beyond the early experimental stage,\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">52.7% of the surveyed enterprises can use AI to conduct business, but there is structural differentiation in the depth of technological implementation between industries.\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Mechanical manufacturing (66.7%), education and entertainment (75%), and fast-moving consumer goods retail (68.8%) have broader applications, while pharmaceuticals and healthcare (66.7%), finance (83.3%), and computer, electrical communication (60%) face obstacles, mainly due to factors such as \"ambiguous or short-sighted enterprise-level AI strategies, or no strategy at all\", \"loosely defined operational models and governance\", and \"lack of understanding of risks: AI introduces unique risks, from AI hallucinations to bias and intellectual property protection\".\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002F7e7e7fa4deae4ec2b3fc397a202905e0\u002F47d41962727f34443f8a56598591e90f.png\" width=\"797\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">From the functional perspective,\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">comprehensive management (31.8%), customer service and sales (21.8%), and R&D (20.9%) are most affected by AI.\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Industry applications focus differently: smart manufacturing focuses on production links, while pharmaceuticals, healthcare, and finance focus on comprehensive management, and fast-moving consumer goods and retail focus on R&D and support. Enterprises are applying AI technology where it can generate the maximum overall value. This drives the transition of management positions from \"experience-based authority\" to \"data-driven leadership,\" reshaping the decision-making foundation and alleviating cognitive biases and information lags in the VUCA (volatile, uncertain, complex, ambiguous) era.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In terms of talent, \u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">64.5% of the surveyed enterprises regard AI literacy as an auxiliary factor in recruitment, and non-technical positions (such as sales and administration) still take industry knowledge and communication skills as core competencies\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">, reflecting that enterprises pay more attention to employees' core skills and adaptability, rather than single AI literacy.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">04 AI Reconfigures HR Ecology and Talent Strategy Enterprises Should Pay Attention to Synergistic Development \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The impact of AI on human resources management is moving from \"tool assistance\" to \"capability reconstruction.\" HR professionals who possess \"AI technology sensitivity, business scenario understanding, and strategic value creation ability\" will become key forces for enterprises' digital transformation.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">72.7% of HR professionals acknowledge that AI greatly reduces the burden of routine work\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">, \u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">but also face challenges such as skill upgrading, AI-specific training, and staff optimization.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Different industries show significant differences in AI impact. AI-sensitive industries such as computer\u002Fcommunication and semiconductors break through first, establishing \"technology insight officers\" positions, focusing on AI talent modeling and intelligent organizational diagnosis. Service industries such as finance and fast-moving consumer goods apply in a differentiated way: finance prioritizes compliance risks, focusing on \"explainability, controllability, and traceability\"; retail emphasizes efficiency improvement, focusing on \"dynamic response, cost optimization, and experience balance,\" achieving deep integration of technology and industry characteristics.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002F70f099d943104a638aa5c4fa07b4befd\u002Fa58a1217eadebf12cb6a26a4e4f8b064.png\" width=\"795\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Enterprise nature also determines AI transformation strategies. State-owned enterprises, relying on institutional advantages, have 55.6% conducting full-staff digital literacy training; \u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">private enterprises pursue efficiency, using AI interviewers to reduce costs and reshape job skills;\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">multinational enterprises tend to gradual change, building AI capability sharing platforms.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">At the industry level, labor-intensive sectors such as manufacturing, real estate\u002Fbuilding, due to the early stage of digital transformation, adopt a \"technology embedding + human supplementation\" strategy; technology-driven industries such as computer and energy chemical raw materials accelerate structural adjustments, with 40% of the surveyed enterprises in the computer\u002Fcommunication industry planning to launch specialized optimizations.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The report shows that \u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">78.2% of the surveyed enterprises believe that AI brings more opportunities than challenges to employees, and future corporate competitiveness depends on the \"human-technology\" synergistic capability.\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Although the impact of AI on employee retention is limited, 62.7% of the surveyed enterprises stated that the number of employees will not change in the short term, but the hidden elimination risks caused by skill gaps still need to be vigilant.\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 class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">[News Source] Qiancheng Wuyou 51job \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.hrloo.com\u002Fnews\u002F347084.html\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">https:\u002F\u002Fwww.hrloo.com\u002Fnews\u002F347084.html\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（This article is reprinted 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 of 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%3Ab95a7d32-d2ad-4672-8cf2-f93405ed1cde%3A0.wav?Expires=1774838485&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=qgh8cxn7v5lSGpcM0%2FCE%2F4Lktm0%3D","b95a7d32-d2ad-4672-8cf2-f93405ed1cde"]