
关于人工智能对未来就业的影响,各界存在诸多猜测,Fortune Intelligence等媒体亦有大量探讨。高盛(Goldman Sachs)首席经济学家简·哈奇乌斯正在研究这个课题。他率领团队广泛整合行业调查、政府数据和专有分析,编制了《人工智能应用追踪报告》(AI Adoption Tracker)。哈奇乌斯团队发现,2025年第二季度人工智能应用取得“显著进展”,美国公司运用AI生产商品或提供服务的比例从第一季度的7.4%升至9.2%。该报告亦描绘出一幅更为复杂的图景。他们发现,尽管生成式AI及相关技术正在迅速重塑企业投资与生产力,但其对就业的影响速度却更为缓慢且微妙。
以下为高盛《人工智能应用追踪报告》的三大核心观点。
1. 迄今为止,劳动力市场所受冲击有限
尽管美国企业人工智能采用率激增,但研究报告指出,整体劳动力市场状况目前基本未受影响。简而言之,“人工智能对劳动力市场的影响仍然有限,且尚无迹象表明其对大多数劳动力市场指标产生显著冲击。”这一结论与科技行业削减涉及AI的工作岗位的信号形成对比,也与数位知名CEO警告称人工智能可能会取代超50%白领员工的言论相左。
具体而言,高盛表示,在AI应用程度高的行业中,就业增长、薪资涨幅、失业率及裁员率等关键指标,与AI应用程度较低的行业相比,并未出现统计学上的显著差异。目前,与AI相关的职位招聘占所有IT岗位的24%,但仅占招聘总数的1.5%。这表明,尽管技术类岗位正在积极调整,但更广泛的劳动力结构转型仍是渐进式的。
值得注意的是,受AI影响的岗位失业率现已与整体经济水平趋同,驳斥了早期对大规模失业的担忧。近期并未有明确将AI列为原因的裁员公告,这进一步表明当前AI带来的冲击主要局限于特定职能领域,而非波及整个行业。
另一方面,分析师指出,在传闻中受到AI影响的职业(电话客服中心即是显著例证),其就业增长仍不尽如人意。这表明某些变化正在悄然发生,但尚处于早期阶段。
2. 生产力提升集中显现且成效显著
高盛指出,在已部署AI的领域,其对生产力的提升作用显著。哈奇乌斯团队援引学术研究及企业案例称,采用生成式AI平均可将劳动生产率提升23%~29%。具体估算值存在差异:学术研究得出的中位数为16%,平均值为23%;企业案例得出的中位数为30%,平均值为29%。尽管如此,这仍表明先行采用者已获得切实的效率提升。
随着企业从试验阶段转向将AI融入核心工作流程,最积极应用生成式AI的行业,如信息科技、金融和专业服务业,得到的生产力提升最为显著。
商界领袖和经济学家预计,随着应用深化及更多组织将AI纳入基础设施,其对生产力的综合影响将在宏观经济数据中表现得更加明显。
3. AI对就业的影响:仍处于初期
高盛分析中反复出现的一个主题是:AI对就业的影响尚未完全显现。一方面,与AI相关的职位空缺(尤其在IT领域)正在增加;另一方面,市场对机器学习工程师、AI研究员等职位的需求也在上升。调查结果显示,相当一部分公司正计划招聘具备此类技能的人才。
生产力提升终将惠及更多行业,而“AI应用强度”(即高度依赖AI的岗位占比)在信息技术和专业服务领域最高,预示着未来就业结构的转变可能会率先在这些行业显现。
报告指出,当前AI对劳动力市场的影响有限,但变革的种子已然播下。企业(尤其是大中型企业)AI采用率的提升,预示着未来的生产力变革与岗位变迁。然而就目前而言,至少在AI技术与业务流程实现更广泛、更深度的融合之前,对AI引发大规模失业的担忧似乎有些夸大了。
随着企业持续扩大AI应用规模以及配套基础设施的日益成熟,机遇与挑战均将随之增加,这就需要政策制定者、商界领袖及劳动者共同密切关注。
高盛拒绝进一步置评。(财富中文网)
关于本文,《财富》杂志使用了生成式AI辅助完成初稿。编辑在发布前已核实信息的准确性。
译者:刘进龙
审校:汪皓
关于人工智能对未来就业的影响,各界存在诸多猜测,Fortune Intelligence等媒体亦有大量探讨。高盛(Goldman Sachs)首席经济学家简·哈奇乌斯正在研究这个课题。他率领团队广泛整合行业调查、政府数据和专有分析,编制了《人工智能应用追踪报告》(AI Adoption Tracker)。哈奇乌斯团队发现,2025年第二季度人工智能应用取得“显著进展”,美国公司运用AI生产商品或提供服务的比例从第一季度的7.4%升至9.2%。该报告亦描绘出一幅更为复杂的图景。他们发现,尽管生成式AI及相关技术正在迅速重塑企业投资与生产力,但其对就业的影响速度却更为缓慢且微妙。
以下为高盛《人工智能应用追踪报告》的三大核心观点。
1. 迄今为止,劳动力市场所受冲击有限
尽管美国企业人工智能采用率激增,但研究报告指出,整体劳动力市场状况目前基本未受影响。简而言之,“人工智能对劳动力市场的影响仍然有限,且尚无迹象表明其对大多数劳动力市场指标产生显著冲击。”这一结论与科技行业削减涉及AI的工作岗位的信号形成对比,也与数位知名CEO警告称人工智能可能会取代超50%白领员工的言论相左。
具体而言,高盛表示,在AI应用程度高的行业中,就业增长、薪资涨幅、失业率及裁员率等关键指标,与AI应用程度较低的行业相比,并未出现统计学上的显著差异。目前,与AI相关的职位招聘占所有IT岗位的24%,但仅占招聘总数的1.5%。这表明,尽管技术类岗位正在积极调整,但更广泛的劳动力结构转型仍是渐进式的。
值得注意的是,受AI影响的岗位失业率现已与整体经济水平趋同,驳斥了早期对大规模失业的担忧。近期并未有明确将AI列为原因的裁员公告,这进一步表明当前AI带来的冲击主要局限于特定职能领域,而非波及整个行业。
另一方面,分析师指出,在传闻中受到AI影响的职业(电话客服中心即是显著例证),其就业增长仍不尽如人意。这表明某些变化正在悄然发生,但尚处于早期阶段。
2. 生产力提升集中显现且成效显著
高盛指出,在已部署AI的领域,其对生产力的提升作用显著。哈奇乌斯团队援引学术研究及企业案例称,采用生成式AI平均可将劳动生产率提升23%~29%。具体估算值存在差异:学术研究得出的中位数为16%,平均值为23%;企业案例得出的中位数为30%,平均值为29%。尽管如此,这仍表明先行采用者已获得切实的效率提升。
随着企业从试验阶段转向将AI融入核心工作流程,最积极应用生成式AI的行业,如信息科技、金融和专业服务业,得到的生产力提升最为显著。
商界领袖和经济学家预计,随着应用深化及更多组织将AI纳入基础设施,其对生产力的综合影响将在宏观经济数据中表现得更加明显。
3. AI对就业的影响:仍处于初期
高盛分析中反复出现的一个主题是:AI对就业的影响尚未完全显现。一方面,与AI相关的职位空缺(尤其在IT领域)正在增加;另一方面,市场对机器学习工程师、AI研究员等职位的需求也在上升。调查结果显示,相当一部分公司正计划招聘具备此类技能的人才。
生产力提升终将惠及更多行业,而“AI应用强度”(即高度依赖AI的岗位占比)在信息技术和专业服务领域最高,预示着未来就业结构的转变可能会率先在这些行业显现。
报告指出,当前AI对劳动力市场的影响有限,但变革的种子已然播下。企业(尤其是大中型企业)AI采用率的提升,预示着未来的生产力变革与岗位变迁。然而就目前而言,至少在AI技术与业务流程实现更广泛、更深度的融合之前,对AI引发大规模失业的担忧似乎有些夸大了。
随着企业持续扩大AI应用规模以及配套基础设施的日益成熟,机遇与挑战均将随之增加,这就需要政策制定者、商界领袖及劳动者共同密切关注。
高盛拒绝进一步置评。(财富中文网)
关于本文,《财富》杂志使用了生成式AI辅助完成初稿。编辑在发布前已核实信息的准确性。
译者:刘进龙
审校:汪皓
There’s a lot of speculation, including in the pages of Fortune Intelligence, about the impact that artificial intelligence will have on the jobs of the future. Goldman Sachs Chief Economist Jan Hatzius is on the case, leading a team that draws from a breadth of industry surveys, government data, and proprietary analysis to produce an AI Adoption Tracker. For the second quarter of 2025, Hatzius’ team found “notable progress” in AI adoption, with 9.2% of U.S. companies using AI to produce goods or services, compared to 7.4% in the first quarter. The report also delivers a nuanced picture, finding that while generative AI and related technologies are rapidly reshaping corporate investment and productivity, their effect on employment is evolving at a slower, subtler pace.
Here are three takeaways from the Goldman AI Adoption Tracker.
1. Limited labor market disruption (so far)
Despite a surge in AI adoption across U.S. firms, the research note found overall labor market outcomes remain largely unaffected for now. Simply put, “AI’s impact on the labor market remains limited and there is no sign of a significant impact on most labor market outcomes.” This contrasts with signs that the tech sector is cutting jobs exposed to AI, and with several prominent CEOs warning AI could displace upward of 50% of the white-collar workforce.
Specifically, Goldman says key metrics such as job growth, wage gains, unemployment rates, and layoff rates in AI-exposed industries have shown little statistically significant deviation from less exposed sectors. AI-related job postings now account for 24% of all IT openings, but still represent just 1.5% of total job postings, indicating that while technology roles are adapting, the broader workforce shift is gradual.
Notably, the unemployment rate for AI-exposed occupations has now reconciled with the wider economy, refuting early fears of mass displacement. There have been no recent layoff announcements explicitly citing AI as the cause, further underscoring the current containment of disruption to specific functions rather than entire industries.
On the other hand, the analysts noted, payrolls growth continues to underperform in occupations where AI is having an anecdotal impact, as with the notable example of telephone call centers. This suggests that something is happening that is only being whispered about. Still, it’s early days.
2. Productivity gains concentrated, but significant
Goldman says AI’s influence on productivity where it’s already been deployed is pronounced. Hatzius’ team cited academic studies and company anecdotes indicating generative AI adoption delivers, on average, a 23%–29% boost to labor productivity. The estimates vary, with academic studies generating a median of 16% and average of 23%, while company anecdotes produce a median of 30% and average of 29%. Still, this suggests tangible efficiency improvements for early adopters.
Sectors leveraging generative AI most actively—information, finance, and professional services—are seeing the largest increases in productivity as firms move from experimentation to integrating AI into their core workflows.
Business leaders and economists expect that as adoption deepens and more organizations build AI into their infrastructure, the aggregate productivity impact will become more visible in macroeconomic data.
3. The AI employment story: still in its early chapters
A recurring theme in the Goldman Sachs analysis is that the full employment effect of AI is still developing. While AI-related openings are growing, especially in IT, there is also an uptick in demand for roles such as machine-learning engineers and AI researchers. Surveys reflect that a substantial share of companies are planning to hire for these skillsets.
Productivity improvements may eventually widen to more industries, and “AI intensity” (share of roles heavily using AI) remains highest in information-technology and professional-service sectors, signaling where future employment shifts might first materialize.
The report said the current impact of AI on the labor market is limited, but the seeds of transformation are being sown. Increases in corporate AI adoption, especially among large and medium-sized firms, point toward future productivity and role changes. But for now, fears of widespread AI-induced job loss appear overstated—at least until broader, deeper integration of the technology with business processes occurs.
As companies continue to scale AI and as supporting infrastructure matures, opportunities and challenges will both be amplified, warranting close observation by policymakers, business leaders, and workers alike.
Goldman Sachs declined to comment further.
For this story, Fortune used generative AI to help with an initial draft. An editor verified the accuracy of the information before publishing.