The C-Suite Says AI Will Create Jobs. The Data Says Otherwise.

There’s a growing chasm between what executives say about AI and what workers experience. On one side: 80% of leaders report positive returns on AI, with 74% saying their early deployments are paying off. On the other: AI is cutting 16,000 jobs per month, entry-level hiring has collapsed by 50%, and only 14% of workers say they consistently achieve net-positive outcomes from using AI.

Both things can be true. The problem is that they’re happening to different people.

The Boardroom View

According to Harvard Business Review, 80% of leaders report using AI weekly, and 74% say they’re seeing positive returns on early deployments. That’s not surprising — as HBR itself notes, senior leaders tend to use AI for “high-level synthesis, strategic drafting, and decision support” — tasks where the technology performs well.

For executives, AI is a force multiplier. It drafts memos, summarizes reports, and generates strategic options. The output looks polished, the time savings feel real, and the ROI appears on dashboards. The experience is genuinely positive.

But that’s not the whole story.

The Worker Reality

For everyone below the C-suite, AI’s impact looks different.

AI is axing 16,000 jobs per month, according to Goldman Sachs data cited by Fortune. These aren’t hypothetical future losses — they’re happening now, month after month.

Entry-level hiring has collapsed. SignalFire’s research found that new grad hiring has dropped 50% compared to pre-pandemic levels. The traditional career on-ramp — junior positions where people learn, make mistakes, and grow into senior roles — is being dismantled.

As SignalFire put it: “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.”

Workers aren’t feeling the benefits. Mercer’s research found that for 43% of workers, their job is more frustrating because of AI, not less.

The “Workslop” Problem

Harvard Business Review researchers coined a term for a growing phenomenon: workslop. That’s “content that appears polished but lacks real substance, offloading cognitive labor onto coworkers.”

41% of workers have encountered AI-generated workslop, and each instance costs nearly two hours of rework. The problem cascades — someone generates something with AI, it looks done, it gets passed along, and then a human has to fix it. The efficiency gain is captured by the person who generated it. The rework cost is borne by someone else.

Workday’s survey quantified the gap: for every 10 hours of efficiency gained through AI, nearly 4 hours are lost to fixing its output. Only 14% of respondents said they “consistently achieve net-positive outcomes from AI use.”

That’s a brutal ratio. And it explains why the people actually using AI day-to-day have a very different take on it than those overseeing from above.

The March Jobs Numbers Tell the Story

The Bureau of Labor Statistics reported 178,000 new jobs in March — barely changed from the month before and barely a ripple in an economy that needs far more to keep pace with population growth.

Where did those jobs come from? Healthcare added 76,000. Construction grew by 26,000. Transportation and warehousing added 21,000. Social assistance increased by 14,000.

These are not AI-adjacent industries. They’re sectors where humans still do physical, care-based work that AI hasn’t figured out how to automate yet.

Meanwhile, computer systems design and related services lost 13,000 jobs in the same month. Computing infrastructure providers saw a 1,500-job decrease. The very sector that’s building AI tools is shedding workers while the executives running those companies celebrate productivity gains on earnings calls.

Occupational Downgrading

Goldman Sachs identified a mechanism they call “occupational downgrading” — workers displaced by AI don’t just lose their jobs. They move into roles requiring fewer analytical and interpersonal skills, earning less and using fewer of their capabilities.

“The same technological shifts that eliminated their positions also eroded the value of their existing skills,” Goldman Sachs noted. “AI-driven displacement could impose lasting costs on affected workers, worsening labor market outcomes for several years.”

This isn’t a temporary disruption followed by retraining and a better job. For many workers, it’s a permanent downgrade.

Even OpenAI Is Worried

Here’s the tell: OpenAI itself — the company most responsible for the technology — has released policy proposals acknowledging the employment disruption. Their recommendations include expanding healthcare coverage, improving retirement savings, and setting a new industrial policy agenda.

As OpenAI wrote: “Unless policy keeps pace with technological change, the institutions and safety nets needed to navigate this transition could fall behind.”

When the company building the technology is warning about its effects, it’s worth listening.

What This Means for Your Career

For early-career professionals: The entry-level market has fundamentally shifted. Traditional paths — junior developer, analyst, associate — are thinner than they’ve been in years. The SignalFire data is stark: 50% fewer new grad positions. You need to find alternative on-ramps: freelance project work, open-source contributions, specialized certifications, or roles in industries where AI adoption is slower.

For mid-career workers: Your advantage is institutional knowledge and judgment — things AI still struggles with. But be aware that “workslop” means your workload may actually increase as you clean up AI-generated output. Push for clear policies about AI use and accountability in your organization.

For senior leaders: The data is clear — AI works differently at different levels of the organization. The 80% positive-experience number at the top doesn’t trickle down. If your AI strategy only considers executive-level outcomes, you’re building on incomplete data.

The Bottom Line

The C-suite’s AI enthusiasm isn’t wrong — for them. AI genuinely improves executive workflows. But the 14% net-positive outcome rate for everyday workers tells a different story. The 16,000 monthly job losses, the 50% collapse in entry-level hiring, and the occupational downgrading identified by Goldman Sachs are not theoretical future risks. They’re present-day realities.

The gap between boardroom optimism and worker experience isn’t a misunderstanding. It’s a structural feature of how AI adoption is unfolding. The technology concentrates benefits at the top and distributes costs downward. Recognizing that is the first step toward doing something about it.

Sources

Goldman Sachs (via Fortune): AI job displacement data
SignalFire: 2025 State of Tech Talent Report — new grad hiring decline
Harvard Business Review: Executive AI usage survey (80% weekly use, 74% positive ROI)
Workday: AI productivity survey (10 hours gained, 4 hours lost)
Mercer: Worker frustration survey (43% report more frustration)
Bureau of Labor Statistics: March 2026 employment report