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The US labor market added 178,000 jobs in March, according to the Bureau of Labor Statistics.\u00a0<\/strong><\/p>\n <\/p>\n The data showed<\/a> limited change from the prior month, even as companies kept talking about AI-led growth and better workplace efficiency.<\/p>\n That gap has kept attention on whether AI is lifting hiring and output as promised. Recent labor, workplace, and industry reports show a more mixed picture, especially in tech and entry-level roles.<\/p>\n Most job growth in March came from healthcare, construction, transportation and warehousing, and social assistance. Healthcare added 76,000 jobs, while construction gained 26,000 and transportation and warehousing added 21,000.<\/p>\n <\/p>\n The BLS data did not show the same strength in tech-linked areas. Computing infrastructure providers and web search portals showed little movement, while computer systems design and related services lost 13,000 jobs during the month.<\/p>\n That pattern stands in contrast to public claims that tech hiring is recovering. Marc Andreessen said<\/a> fears about AI-led job losses were overblown and shared data showing more job openings at tech firms.<\/p>\n But openings do not always lead to hiring. The March labor figures showed that the strongest hiring came from sectors outside core tech, while related digital services stayed flat or moved lower.<\/p>\n A recent Goldman Sachs report<\/a>, cited by Fortune, said AI cut about 16,000 jobs per month over the past year. At the same time, a 2025 SignalFire study said new graduate hiring had dropped<\/a> 50% from levels seen before the COVID-19 pandemic.<\/p>\n SignalFire said, \u201cThe door to tech once swung wide open for new grads. Today, it\u2019s barely cracked.\u201d The report linked that shift to smaller funding rounds, leaner teams, fewer graduate programs, and rising AI use.<\/p>\n Goldman Sachs also warned<\/a> that workers pushed out by technology often move into more routine jobs. The report said this shift can reduce the value of their existing skills and weaken labor outcomes for years.<\/p>\n That concern has widened the debate around AI and employment. While some leaders still expect long-term gains, recent data has kept attention on current hiring patterns and who bears the cost of the change.<\/p>\n Executives continue to report strong support for AI tools. Harvard Business Review said 80% of leaders use AI weekly, while 74% reported<\/a> positive returns from early deployments.<\/p>\n Workers reported a different experience. Mercer said<\/a> 43% of workers found their jobs more frustrating, while Workday said nearly four hours are lost fixing AI output for every 10 hours of claimed efficiency gains.<\/p>\n Harvard Business Review also pointed<\/a> to \u201cworkslop,\u201d described as content that looks polished but lacks substance. Researchers said 41% of workers had seen this kind of output, with each case adding almost two hours of rework.<\/p>\n Workday said only 14% of respondents \u201cconsistently achieve net-positive outcomes from AI use.\u201d That result suggests many workplaces are still dealing with errors, extra review, and weak trust in outputs.<\/p>\n The divide between executive use and daily staff experience may come from how teams use the tools. Harvard Business Review said senior leaders often apply AI to strategy, drafting, and synthesis, where the systems tend to perform better.<\/p>\n For routine operations that need steady accuracy, results appear less reliable. Brian Solis of ServiceNow called<\/a> this burden an \u201cAI tax,\u201d which he described as \u201cMore checking. More rework. More anxiety.\u201d<\/p>\n\n
Entry-level jobs face more pressure<\/strong><\/h1>\n
Worker experience does not match executive optimism<\/strong><\/h2>\n
OpenAI warns policy may lag behind change<\/strong><\/h2>\n