欧洲在工作场所使用人工智能方面落后于美国，主要原因并非技术，一份新报告指出。由伦敦商学院赞助、Sifted发布的报告称，欧洲面临的是组织层面的差距，而非技术差距。企业在技能、管理、信任以及将人工智能融入工作流程的成本方面举步维艰。
Europe is falling behind the US on AI use at work, and the main reason is not technology, according to a new report. The report from Sifted, sponsored by London Business School, says Europe has an organisational gap rather than a tech gap. Firms struggle with skills, management, trust and the cost of fitting AI into how they work.
“做个好玩的ChatGPT小实验，和让整个业务跑在人工智能上，是两码事，”Celonis高管Rupal Karia对Sifted表示。
“Doing a fun thing with ChatGPT and running your whole business on AI are two very different things,” Celonis executive Rupal Karia told Sifted.
数据说话 圣路易斯联储的一项分析发现，2026年初，约43%的美国工人在工作中使用了人工智能，而欧洲这一比例为32%。美国工人用于人工智能的工作时长是德国、法国和意大利工人的三倍多。
The numbers About 43% of US workers used AI for their jobs in early 2026, against 32% across Europe, a St Louis Fed analysis found. US workers spent more than three times as many work hours using AI as those in Germany, France and Italy.
欧盟统计局数据显示，仅20%的欧盟企业使用人工智能，较一年前的13.5%有所上升。丹麦以42%领跑，罗马尼亚仅为5.2%。
Only 20% of EU firms use AI at all, up from 13.5% a year earlier, Eurostat data shows. Denmark leads at 42%, while Romania sits at 5.2%.
即便在使用人工智能的企业中，真正全面铺开的也寥寥无几。报告引用麦肯锡数据称，88%的组织在某些环节使用人工智能，但仅7%实现了全面规模化应用。
Even where firms use AI, few have gone all in. The report cites McKinsey data showing 88% of organisations use AI somewhere, but just 7% have fully scaled it.
“不存在阻碍欧洲在人工智能采用方面领跑的内在障碍，”伦敦商学院教授Nicos Savva表示。
“There is no inherent roadblock to Europe leading in AI adoption,” said Nicos Savva, a professor at London Business School.
卡在试点阶段 负责Celonis北欧及中东业务的Karia表示，许多公司低估了变革中的人的因素。他补充说，采用进度比预期慢。
Stuck in pilot mode Karia, who runs northern Europe and the Middle East for German software firm Celonis, said many companies had underestimated the human side of change. Adoption has been slower than expected, he added.
高管们把不可靠的输出、网络风险和运行成本列为谨慎的理由。伦敦商学院副院长Gary Dushnitsky告诉Sifted，一些企业正在限制人工智能使用，权衡成本与收益。
Executives cited unreliable outputs, cyber risk and running costs as reasons for caution. Some firms are now limiting AI use as they weigh cost against benefit, LBS deputy dean Gary Dushnitsky told Sifted.
回报也难觅。报告引用营销公司Whito的研究称，75%使用人工智能的企业看到生产率提升，但仅12%看到营收增长。
Returns are also hard to find. The report cites research from marketing firm Whito showing 75% of firms using AI see productivity gains, but only 12% see more revenue.
英国公司Aiimi的技术负责人Paul Maker直言不讳：“大家手里都拿到了锤子，现在拼命找钉子。”
Paul Maker, technology chief at UK firm Aiimi, put it bluntly. “Everyone’s been given a hammer and now they’re desperately looking for nails,” he said.
恐惧与缓慢变革 伦敦商学院教授Lynda Gratton表示，对失业的恐惧也在拖慢采用步伐。
Fear and slow change Fear of job losses is also slowing take-up, said LBS professor Lynda Gratton.
“如果你觉得人工智能会毁掉你的工作，那么你就不会想要采用它，”她说。
“If you feel AI will destroy your work, then you won’t want to adopt it,” she said.
伦敦商学院院长谢尔盖·古里耶夫警告称，如果人们停止学习独立思考，匆忙行事可能会适得其反。他表示，快速启动可能会削弱长期采用。
LBS dean Sergei Guriev warned that rushing could backfire if people stop learning to think for themselves. A quick start, he said, could undermine longer-term adoption.
一些延迟是正常的。报告引用了高盛经济学家埃尔西·彭的研究，她发现个人电脑大约用了15年才在生产力数据中显现出来。
Some of the delay is normal. The report cites Goldman Sachs economist Elsie Peng, who found the PC took about 15 years to show up in productivity data.
在哪些领域有效 报告称，人工智能在法律和银行业的采用速度最快。目前，欧洲央行监管的银行中有超过85%正在使用人工智能。
Where it is working Adoption is fastest in law and banking. More than 85% of banks supervised by the European Central Bank now use AI, the report says.
比利时初创公司Oper开发了一个人工智能代理，用于为承保商Creafin检查抵押贷款文件。该系统以Creafin信贷技术员赫尔曼·维尔杜特的名字命名，他表示，他的团队花在修复数据上的时间远多于撰写抵押贷款的时间。
Belgian startup Oper built an AI agent to check mortgage paperwork for underwriter Creafin. It is named after Herman Verdoodt, a Creafin credit technician, who said his team spends far more time fixing data than writing mortgages.
工厂的采用较慢。爱尔兰安全公司Protex AI的首席执行官丹·霍布斯表示，许多工厂无法停机数天来重新布线其系统。
Factories are slower. Many cannot shut down for days to rewire their systems, said Dan Hobbs, chief executive of Irish safety firm Protex AI.
欧洲的自身路径 报告主张欧洲不应试图在美国前沿模型上效仿。报告称，超过75%的先进人工智能算力位于美国，而欧洲则不到4%。
Europe’s own route The report argues Europe should not try to copy the US on frontier models. More than 75% of advanced AI computing power sits in the US, against less than 4% in Europe, it says.
相反，报告指出，应借鉴那些将工程师嵌入客户公司内部的初创公司模式，这类似于Palantir的做法。报告还强调了人工智能并购，例如Dwelly这样的初创公司收购传统企业并围绕人工智能重建它们。
Instead, it points to startups that place engineers inside client firms, much like Palantir does. It also highlights AI roll-ups, where startups such as Dwelly buy traditional businesses and rebuild them around AI.
一些欧洲人工智能公司也选择保持独立。报告指出，英国虚拟形象初创公司Synthesia据称去年拒绝了Adobe提出的30亿美元收购要约。
Some European AI firms are also choosing to stay independent. UK avatar startup Synthesia reportedly turned down a $3bn offer from Adobe last year, the report notes.
杜什尼茨基表示，欧洲的定位或许应建立在控制力和韧性之上，而非价格。
Dushnitsky said Europe’s pitch could rest on control and resilience rather than price.
“也许欧洲的价值主张应围绕韧性、保密性和隐私性来构建，”他说。
“Perhaps the European value proposition should be built around resilience, confidentiality and privacy,” he said.
这呼应了那些希望制定更智慧的人工智能规则，而非更少规则的创始人。报告得出结论，良好的规则可以通过赋予企业尝试的信心来加速采用。
That echoes founders who want smarter AI rules, not fewer. The report concludes that good rules can speed adoption by giving firms the confidence to try.