到2031年，人工智能（AI）行业必须实现每年6万亿美元的年收入，才能持续为满足预期需求所需的基础设施提供资金支持。这不仅意味着需要进一步提升员工的工作效率，还需要探索更多创新的应用场景。这一预测数据来源于管理咨询公司贝恩公司（Bain & Company）发布的2026年《全球科技报告》。该报告深入分析了AI行业如何应对这一挑战。
The AI industry must generate $6 trillion in annual revenue by 2031 to keep funding the infrastructure needed to meet anticipated demand, and this will require imaginative new uses beyond simply enhancing employee productivity. That $6 trillion figure comes from the 2026 annual Global Technology Report from management consultants Bain & Company, which put its thinking cap on to figure out how the AI sector can possibly meet this challenge. It says the massive demand for AI compute infrastructure has revived the hardware industry.
报告指出，对AI计算基础设施的巨大需求已经推动了硬件产业的发展；其中增长最快的领域包括用于图形处理器（GPU）的高带宽内存（HBM）、先进的封装技术以及专用集成电路（ASIC）。正如去年所报道的那样，AI领域的支出实际上帮助美国经济避免了衰退——数据中心基础设施和模型开发成为了主要的增长动力。贝恩公司指出，大型云计算厂商（如微软、谷歌、亚马逊、Meta和甲骨文）在AI领域的资本支出预计将在2026年达到7800亿美元，几乎是三年前的五倍。
Some of the fastest growing segments include high-bandwidth memory (HBM) used in GPUs, advanced packaging and custom silicon, and application-specific integrated circuits (ASICs) all scaling rapidly. As The reported last year, AI spending is actually keeping the US economy out of recession, with datacenter infrastructure and model development providing the only significant growth areas. Bain points to the “arms race” among hyperscalers for AI capacity, claiming that capital expenditure by Microsoft, Google, Amazon, Meta, and Oracle could hit $780 billion for the whole of 2026, nearly five times the level seen just three years earlier.
到2031年，AI基础设施的年支出预计将达到1.5万亿美元，这一数字与分析机构Omdia的预测（1.6万亿美元）非常接近。贝恩公司认为，资本支出将占行业总收入的约25%，这一比例基于云计算服务提供商的当前发展趋势来看是合理且具有雄心的。虽然现有AI应用的收入预计会继续增长（总额在1.2万至1.8万亿美元之间，包括通过订阅服务实现的消费者AI收入，以及通过软件开发、销售、市场营销、客户服务和IT运营实现的企事业AI收入），但行业仍需额外创造4.2万亿美元的收入来源。
By 2031, it estimates that annual spending on AI infrastructure could reach $1.5 trillion, a figure that is not far off the $1.6 trillion forecast separately by analyst firm Omdia. The $6 trillion comes from the Bain's assumption that capital expenditure will amount to about 25 percent of industry revenue, an ambitious but reasonable percentage based on trends among cloud providers, it says. Bain expects that existing applications of AI will grow, but estimates these will add up to a total between $1.2 trillion and $1.8 trillion in revenue. This includes consumer AI, via subscriptions and s, plus enterprise AI, through software development, sales, marketing, customer service, and IT operations.
根据贝恩（Bain）的研究，有四种可能性可以填补这一收入缺口：
That leaves a remaining $4.2 trillion of additional revenue for the industry to find from somewhere.
- 人工智能模型正在取代搜索引擎，并将广告功能整合到这些系统中以创造新的收入来源；据估计，这可能会为相关开发者带来1000亿至2000亿美元的额外收入。
Four possible categories emerge from Bain’s research as possibilities to fill this gap.
- 人工智能技术被用于制造自动驾驶汽车、卡车和无人机，以及实现其他工业自动化，这可能会催生价值约4000亿美元的新产品和服务。
It says that AI models are replacing search engines and integrating ads to generate new revenue, which means the developers could unlock $100 billion to $200 billion of extra cash.
- 物理层面的AI应用（包括仿真技术、数字孪生模型和机器人技术），其潜在价值高达9000亿美元。
Secondly, AI to make autonomous cars, trucks, and drones, as well as other industrial automation, could create new products and services worth about $400 billion, Basin estimates.
这三部分的收入总和为1.5万亿美元，但仍存在2.7万亿美元的收入缺口。那么，人工智能行业的其余收入来源是什么呢？贝恩认为这些收入可能来自“目前还不存在的新产品和新应用”。具体来说，这些新应用可能包括：
A similar category is physical AI, in which category it includes simulations, digital twins, and robotics, with a calculated worth of as much as $900 billion. Those three add up to $1.5 trillion, leaving Bain with a $2.7 trillion shortfall. What could make up the rest of the AI industry revenue?
由人工智能驱动的药物研发；
能够满足数十亿美元未满足需求的心理健康服务；
It puts forward “new products and uses that don’t exist today,” which is the kind of answer that your granny could have come up with.
在电池技术和半导体等领域取得的材料科学突破；
In this category it stuffs AI-driven drug discovery, mental health support that might address billions of dollars in unmet demand, materials science breakthroughs in areas such as battery technology and semiconductors, and accelerating scientific research in fields from neuroscience to fusion energy.
以及加速从神经科学到聚变能源等领域的科学研究。“目前的讨论主要集中在员工生产力上，但人工智能基础设施的经济价值远不止于提高生产力本身。”贝恩全球科技业务负责人大卫·克劳福德（David Crawford）表示，“该行业真正需要的是一场能够超越移动技术和云计算所带来影响的创新浪潮。”
“The debate today is fixated on employee productivity. The economics of AI infrastructure demand trillions in new revenue beyond productivity gains. What the industry needs is a wave of innovation that will dwarf what mobile and cloud unlocked,” said David Crawford, chairman of Bain’s global Technology practice.
值得注意的是，贝恩此前曾预测人工智能行业到2030年的收入需达到2万亿美元才能维持其发展所需的基础建设投资；如今这一预测数字已经翻了三倍，这或许反映了过去12个月内人工智能领域投资规模的急剧增长。不过也有理由认为，人工智能行业到2031年的年收入可能仍无法达到6万亿美元的目标。
It is only a year since a previous report of Bain’s forecast that the industry would need to hit $2 trillion in revenue by 2030 to keep feeding the infrastructure beast. That figure has now trebled, which is perhaps an indication of just how much the investment going into AI has ballooned over the past 12 months. There are reasons to think the AI industry is not going to hit $6 trillion in annual revenue by 2031.
多家媒体发布了大量报告，指出人工智能（AI）项目的实施并未带来预期的效果；同时，人们对这些AI基础设施项目是否能够真正建成也产生了怀疑。投行杰富里（Jefferies）的一份报告显示：到2026年，美国计划建设的数据中心中仅有大约一半正在建设中，而2028年计划建设的数据中心中，有高达80%的项目尚未开始施工。同一投行的另一份报告指出，芯片制造的瓶颈将限制未来几年内能够投入使用的AI服务器数量。
The has published numerous reports indicating that AI rollouts are just not paying off, such as this one, this one or this one. At the same time, doubts are being cast over whether all those AI infrastructure projects will be realized. A report from investment bank Jefferies found only half the US datacenter capacity scheduled for 2026 is actually under construction and work is yet to begin on as much as 80 percent of the 2028 pipeline. Another report from the same company suggested that chip manufacturing constraints will limit how many planned AI server farms can be brought online over the next several years. ®