In March, the US jobs market recorded 178,000 new jobs, marking little change from the month before, according to the Bureau of Labor Statistics. 

The anemic growth in job listings comes amid volatile policy swings from the White House, increased energy prices due to the US and Israel’s war with Iran and, according to recent research, AI disruptions to the labor market. 

Proponents of AI and large language models have claimed that the tech will bring about an economic boom, thanks to the promise of efficiency breakthroughs. 

But as AI becomes more integrated into daily business operations, there is a widening gulf between that promise of growth and efficiency, and what is actually happening. 

AI dampens employment growth

On March 6, venture capitalist and Netscape co-founder Marc Andreessen said on X that fears about AI job displacement were overblown. 

He also posted an article from Business Insider stating that, at least in tech, job openings are on the rise. Citing data from TrueUp, a tech jobs tracker, Business Insider said that job openings at tech companies have doubled to 67,000 since 2023.  

But openings don’t necessarily translate to hiring. According to the Bureau of Labor Statistics, most employment growth in March did not happen in the tech industry. Of the 178,000 new jobs added in March, healthcare employed 76,000, construction grew by 26,000, transportation and warehousing added 21,000 and employment in social assistance increased by 14,000.  

While the report doesn’t have a single section tracking the tech industry, related services like computing infrastructure providers and web search portals saw a 1,500 job decrease, or almost no change, respectively. Computer systems design and related services lost 13,000 jobs.

Related: Jack Dorsey’s Block to cut 4,000 jobs in AI-driven restructuring

AI has actually axed 16,000 jobs per month over the past year, according to a recent report from Goldman Sachs, as cited by Fortune. In particular, AI has led to a collapse in hiring for entry-level roles. A 2025 study from SignalFire found that new grad hiring had dropped 50% compared to pre-COVID-19 pandemic levels. 

“The door to tech once swung wide open for new grads. Today, it’s barely cracked. The industry’s obsession with hiring bright-eyed grads right out of college is colliding with new realities: smaller funding rounds, shrinking teams, fewer new grad programs, and the rise of AI,” the SignalFire study stated. 

This disruption could create ripples far into the future. According to Goldman Sachs, “AI-driven displacement could impose lasting costs on affected workers, worsening labor market outcomes for several years.”

“A key mechanism behind these worse outcomes is occupational downgrading. Workers displaced by technology are more likely to move into more routine occupations requiring fewer analytical and interpersonal skills, likely because the same technological shifts that eliminated their positions also eroded the value of their existing skills,” they continued. 

These job losses are justified by the theory that AI will, at the very least, make workplaces more productive. But even that isn’t a given.

Reality of AI use clashes with C-suite expectations

Executives are still overwhelmingly supportive of AI. According to Harvard Business Review, 80% of leaders report weekly use of AI, with 74% reporting positive returns on early deployments. 

But workers don’t feel the same. A study from HR consulting firm Mercer found that, for 43% of workers, their job is more frustrating. 

One major issue is the number of mistakes churned out by generative AI. “For every 10 hours of efficiency gained through AI, nearly four hours are lost to fixing its output,” a Workday report stated. 

AI can also be used to offload labor onto coworkers in what researchers at the Harvard Business Review have called “workslop” i.e., “content that appears polished but lacks real substance, offloading cognitive labor onto coworkers.”

They said that “41% of workers have encountered such AI-generated output, costing nearly two hours of rework per instance and creating downstream productivity, trust, and collaboration issues.”

According to Workday, only 14% of respondents to their survey said they “consistently achieve net-positive outcomes from AI use.”

Part of the gulf between executives’ understanding of AI and the reality at the productive level may be explained by the technology itself. 

Per the Harvard Business Review, “Senior leaders tend to use AI for high-level synthesis, strategic drafting, and decision support, tasks where the technology performs well, so the current capabilities tend to benefit their work.”

For messier day-to-day operations like “workflows built over years, teams with uneven technical comfort, output that has to be consistently right, not just fast,” it doesn’t work so well. 

“When the tool works, both groups understand and reap the benefits. When it fails, typically only one of them has to cope with the aftermath.”

Brian Solis, the head of global innovation at enterprise AI firm ServiceNow, said that this divide has created an “AI tax,” i.e., “More checking. More rework. More anxiety. Faster pace. AI slop. Less trust.” 

Andreessen may not believe that the AI job-cut narratives are real, but OpenAI does. The AI company has acknowledged the impact the technology has on employment, and has even released a series of policy proposals to address it.

The list contains ideas that are “intentionally early and exploratory” that serve as a “a starting point for discussion that we invite others to build on.” It includes proposals to expand healthcare coverage, retirement savings and setting a new industrial policy agenda. 

Far from Andreessen’s optimism, OpenAI’s proposal included a warning: “Unless policy keeps pace with technological change, the institutions and safety nets needed to navigate this transition could fall behind.”

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