Recent economic data reveals that U.S. labor productivity continued to rise in the first quarter, albeit at a slightly moderated pace. This upward trend indicates that businesses are leveraging cutting-edge AI technologies to enhance employee efficiency, helping to offset pressure from higher energy costs linked to geopolitical conflicts in the Middle East. Multiple recent productivity reports reinforce the view that companies are treating advanced AI technologies—such as agent-based workflow systems—as "cost-saving, efficiency-boosting capital expenditures." This supports the argument that corporate AI investment remains in its early stages and that demand for AI applications has a long runway ahead. It also underpins the sustained surge in valuations for firms like Anthropic and OpenAI, as well as the prolonged bullish trajectory for cloud computing giants such as Microsoft and Google.
Data released Thursday by the U.S. Bureau of Labor Statistics showed that the productivity measure—output per hour for nonfarm workers—grew at an annualized rate of 0.8% in the first quarter, following a downwardly revised 1.6% increase in the fourth quarter. More notably, on a year-over-year basis, productivity rose significantly by 2.9%, the largest annual gain since 2024, highlighting robust productivity expansion driven by investments in AI agents.
The broader trend of rising labor productivity helps ensure that wage pressures are no longer the primary driver of inflation, aligning with recent remarks from Federal Reserve officials. In recent years, businesses have increasingly ramped up spending on emerging technologies like artificial intelligence to mitigate cost increases stemming from factors such as tariffs or conflicts involving Iran.
From another perspective, U.S. labor productivity cooled slightly compared to the previous quarter due to increased hours worked, but unit labor costs rose significantly less than in the prior quarter. As labor costs represent one of the largest expenses for many businesses, companies are increasingly committed to investing in advanced AI technologies and intelligent devices like humanoid robots to make workforce output more efficient. Higher productivity allows firms to moderate price increases for financially strained U.S. consumers.
Another economic report released on Thursday showed that unit labor costs—the price paid to employees per unit of output—increased at an annualized rate of 2.3% from the previous quarter. Hours worked rose 0.7% in the first quarter, after declining 0.2% in the prior quarter. Hourly compensation, not adjusted for inflation, grew at an annualized rate of 3.1%. However, after accounting for inflation, workers' real compensation edged lower early in the year. In fact, the U.S. Bureau of Labor Statistics noted that the share of output going to workers as compensation fell to just 54.1% in the first quarter, the lowest level since the series began in 1947.
The report also indicated that manufacturing productivity posted its largest quarterly increase in a year, rebounding strongly from a year-end slowdown.
Productivity data reinforces the AI investment thesis: companies are increasing spending on intelligent agents, and the bull market in AI applications is far from over. U.S. economic growth accelerated at the start of the year, after the longest-ever federal government shutdown constrained expansion in the final months of 2025. Business investment has surged recently, driven by continued strength in AI-related infrastructure spending. Economists widely expect labor productivity gains to continue this year as corporate investment in AI technology expands. More favorable corporate tax provisions and reduced uncertainty around tariffs and trade policy may also encourage greater AI investment.
Detailed productivity figures showed that nonfarm business output—excluding government spending—grew at an annualized rate of 1.5% in the first quarter, slightly stronger than at the end of 2025. With U.S. nonfarm productivity rising 0.8% annualized and 2.9% year-over-year in the first quarter, and unit labor costs increasing only 2.3% annualized, economists generally expect AI investment to continue supporting efficiency gains. These trends suggest that, faced with pressures from tariffs, oil prices, and wages, businesses prefer to boost output per worker through AI, automation, and software tools rather than simply expanding headcount.
Corporate urgency to improve efficiency and reduce operating costs has recently accelerated the adoption of two core categories of AI application software: generative AI applications and AI agents. Among these, AI agents capable of autonomously performing various tedious and complex tasks are likely to represent the ultimate trend in AI application over the next decade. The emergence of AI agents signals a shift from AI as an information-assistance tool to a highly intelligent productivity tool, which explains why Anthropic's valuation has surpassed $1 trillion, exceeding that of OpenAI.
According to a recent MarketsandMarkets study, the AI agent market is projected to reach $53 billion by 2030, implying a compound annual growth rate of 46% starting from 2025. The concentrated emergence of autonomous task-performing AI agents like Anthropic's Claude Cowork and OpenClaw in 2026 is no coincidence; it stems from the simultaneous convergence of five key curves: model capability, tool protocols, AI developer frameworks, inference costs, and end-context capacity.
At the application layer, AI agents are likely to become the dominant commercial interface, as they translate "intelligence" directly into "action," advancing AI from merely answering questions to executing, collaborating, and completing highly complex multi-step tasks. There is no doubt that the "AI disrupts everything" narrative is igniting a new wave of corporate efficiency revolution.
For example, Block, led by Twitter co-founder Jack Dorsey, laid off over 4,000 employees—nearly half of the tech company's workforce—while North American internet giants like Meta (Facebook's parent) and Snap have also announced significant job cuts. Block's public statements indicate that agent-based AI tools enable leaner teams to maintain higher operational efficiency over the long term. Its CFO later emphasized that the operational efficiency gains from agent-based workflows make deep workforce reductions almost "inevitable" for any business.
From an AI engineering and corporate IT perspective, the investment thesis supporting the long-term bullish trajectory for AI application leaders like Microsoft, Google, and Oracle continues to strengthen. Companies pursuing productivity gains are increasing deployment of AI tools, automation, and intelligent agents, which in turn drives sustained demand for cloud AI computing resources, model APIs, enterprise AI suites, code agents, and office Copilots. Thus, the latest productivity data reinforces the view that corporate AI investment remains early-stage and AI application demand has a long growth runway. This provides medium- to long-term demand support for OpenAI, Anthropic, and cloud/software giants like Microsoft, Google, Amazon, and Oracle.
Notably, Anthropic has recently accelerated deployment of AI agents in enterprise and financial scenarios, reporting staggering revenue growth of "80 times" on an annualized basis in the first quarter, alongside launching industry-specific AI agents for banking and insurance. Google has also placed AI agents at the core of its enterprise monetization strategy, maintaining its capital expenditure plan of $175–185 billion for the year, with "slightly more than half" of its massive AI-related investments directed toward cloud computing.
Soft Landing Expectations Strengthen Separate data released by Challenger, Gray & Christmas Inc. on Thursday morning showed that the total number of layoff announcements in the U.S. private sector during the first four months of 2026 fell by approximately 10% compared to the same period a year earlier. The monthly employment report due from the U.S. government on Friday is expected to show robust nonfarm payroll growth in April, accelerated wage increases, and a stable unemployment rate, following a strong rebound in job gains the previous month.
Another government report on Thursday indicated that initial jobless claims remained low last week, signaling limited layoffs across the broader U.S. economy. The ADP employment report, often seen as a preview of the government's figures, showed that U.S. businesses added jobs at the fastest pace in over a year during April, offering fresh evidence of labor market stabilization. According to ADP Research Institute data released Wednesday, private sector employment increased by 109,000 in April, the strongest reading since early 2025, after a revised gain of 61,000 the previous month.
The rebound in ADP employment, driven by strong AI investment, has significantly bolstered economists' expectations for a perfect "soft landing" of the U.S. economy. However, it has also weakened the case for Fed interest rate cuts this year. With employment data not deteriorating significantly, consumer spending holding up, and energy and tariff-related factors rekindling inflation, the Fed is more likely to maintain a cautious "higher for longer" stance.
The latest economic figures suggest that businesses have not significantly frozen hiring despite high oil prices, tariffs, and geopolitical tensions. Meanwhile, U.S. real GDP grew at an annualized rate of 2.0% in the first quarter, below expectations but rebounding noticeably from the 0.5% growth in the fourth quarter of 2025, with support from AI-related capital expenditure, resumed government spending, and core private demand. In other words, the U.S. economy is not exhibiting the employment collapse typical ahead of a recession, but rather showing the "slower yet resilient growth" characteristic of a soft landing—bringing the Fed's desired outcome within reach.
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