Workers Yearn for Pre-AI Offices as ‘Slop’ Erodes Meaning and Extends Hours

Office workers don’t hide their frustration anymore. Two-thirds say they miss the days before AI tools flooded their inboxes, reports, and meetings with low-quality output they now call slop. They spend extra hours checking facts. They rewrite vague summaries. And many wonder why leadership pushes the technology so hard when it adds to their load instead of lightening it.

The Human Cost Emerges in Fresh Data

A survey of 2,500 knowledge workers across the US, UK, Canada, Germany and Spain, conducted in March 2026 by Attest for professional services firm Adaptavist, lays bare the sentiment. Futurism first highlighted the findings on August 1. Sixty-five percent feel nostalgic for pre-AI work routines. Thirty-six percent admit they often don’t understand why AI appears in their roles. Over a third would wipe generative tools from their lives if given the chance.

The numbers don’t stop there. Forty-two percent report they spend more time verifying AI output than the time those tools supposedly save them. Forty-nine percent say poor-quality AI slows entire projects. Almost half — 46 percent — feel their jobs have grown more repetitive and less meaningful. And 54 percent worry AI could shrink demand for their specific roles inside five years.

Adaptavist put it plainly in its report. “Without clear guardrails, accountability, and alignment, the promise of AI efficiency risks being offset by a growing burden on the very people it is designed to support.” The firm released the full Human Cost of AI Transformation research report alongside the data.

But the Adaptavist numbers stand alongside broader evidence that the productivity story has soured. Harvard Business Review examined the contradiction in September 2025. Authors Kate Niederhoffer, Gabriella Rosen Kellerman, Angela Lee, Alex Liebscher, Kristina Rapuano and Jeffrey T. Hancock noted that companies with fully AI-led processes nearly doubled last year while workplace AI use has doubled since 2023, per Gallup and Accenture data. Yet a MIT Media Lab report found 95 percent of organizations see no measurable return on their AI investments. So much activity. So little payoff. The piece defined “workslop” as AI-generated content that looks polished yet lacks substance or originality, turning into filler that creates more cleanup work downstream.

Executives at partner firms echoed the concerns with specific insight. Kevin Nanney, chief product officer at Tempo Software, pointed to generational differences. “42% of Gen Z tells us they prefer working life before AI,” he said. “These are people who have never known a professional world without the internet, yet they’re the generation most likely to say they preferred work before AI came along. That’s worth sitting with. It tells us that the problem isn’t capability or familiarity. It’s meaning.”

Mike Potter, co-founder and CEO of Rewind, pushed back on the idea that expertise no longer matters. Twenty-three percent of workers in the Adaptavist data feel their personal expertise is now less valued. Potter called that a misread. “AI is incredibly fast and increasingly capable — but it operates without judgment. It doesn’t know what it doesn’t know. The people who understand their domain, who can spot when an AI agent is confidently wrong, who know what ‘good’ looks like in their field — they’re more critical now, not less.”

Other voices from the report struck similar notes. Anand Unadkat, senior solutions architect at Atlassian, highlighted the “verification tax.” “While 73% of workers acknowledge efficiency, the fact that 42% spend more time verifying output signals a ‘verification tax’ that leaders must eliminate.” Lisa Schaffer, global work management practice lead at Adaptavist, noted the anxiety even at the top. Twenty-nine percent of C-suite leaders feel “very” concerned about AI reducing the need for their own roles in five years.

The pattern repeats in recent coverage. A Forbes article from October 2025 warned that AI’s supposed productivity gains can flip into losses once “AI workslop” takes hold. CNBC covered related MetLife research in March 2026 showing 53 percent of US workers admitted turning in workslop — content that appears acceptable but fails to advance real goals. Managers notice. Fifty-four percent say they’ve received it, breeding mistrust and extra rounds of revision.

So why does the workday stretch longer? The verification burden explains part of it. Constant fact-checking, prompt tuning and correction eat hours that once went to core tasks. Cognitive load climbs. Decision fatigue sets in. One analysis on Flow Chain Sensei from May 2026 described “AI brain fry” — the mental exhaustion from supervising outputs that demand human judgment to fix. Thirty-four percent of workers experiencing that level of strain reportedly intend to quit, according to Boston Consulting Group data cited there.

Yet adoption pressure continues. Companies chase efficiency numbers. Leaders cite Gartner forecasts of $2.5 trillion in global AI spend for 2026. Employees see the push. Fifty percent in the Adaptavist survey say their performance now gets compared against AI benchmarks. A quarter feel pressured to work faster, produce higher quality or hit efficiency targets because of it. The result? More output that looks impressive on the surface. More downstream fixes. Longer effective days even if the clock doesn’t officially move.

Adaptavist also surfaced quiet resistance. Thirty-three percent of knowledge workers consider switching industries because of AI. Thirty-four percent think about retiring earlier. C-level executives show the highest concern — 46 percent eye an industry change, 47 percent ponder stepping away sooner. At the same time, 74 percent actively learn new skills to stay relevant, with 85 percent of C-suite leaders doing so. The intent to adapt exists. The trust that employers guide the change wisely does not always follow.

Project management platforms may offer one practical bridge. Sixty-six percent of respondents said these tools grow more important for AI-enabled workflows. Sixty-three percent believe they help teams extract real value. Integration inside familiar systems — Atlassian, Microsoft 365, monday.com — could reduce the friction. Several contributors to the Adaptavist report pushed that angle. Moni Houser of monday.com argued that with 67 percent of workers wanting more AI, the question shifts from whether to adopt to how to scale it inside daily processes without creating chaos.

Still, the human element resists simple fixes. Generic AI summaries replace thoughtful memos. Polished but empty slides fill decks. Colleagues forward AI-generated emails that another AI then summarizes before a third AI drafts the reply. Communication loops grow but substance shrinks. Leila Hormozi captured the absurdity in an April 2026 Facebook post that circulated widely: workers write AI emails, summarize them with AI, then respond with AI. “Are we actually even communicating?”

Merriam-Webster named “slop” its 2025 word of the year, citing the explosion of low-quality AI content across feeds, inboxes and workplaces. Fisher Phillips noted in January 2026 that employers should define acceptable AI use, assign ownership, train managers to spot slop and slow the rollout where needed. The advice aims to prevent productivity theater — the illusion of output that actually generates more revision cycles and erodes team trust.

Executives who ignore the signals risk losing talent. The Adaptavist data shows clear majorities acknowledge AI can drive efficiency. They simply don’t experience it that way in practice. Transparency helps. Sixty-six percent said their organizations have been open about AI plans. Sixty percent received adequate training. Yet 39 percent feel the pace of change impossible to match. Thirty-six percent report AI fatigue that already reduces their tool usage.

The picture that forms is not one of rejection but of exhaustion. Workers want tools that amplify judgment rather than demand endless oversight. They want clarity on why AI enters their workflow and how it connects to real outcomes. Most of all they want the sense that their expertise still counts. When slop multiplies, that sense fades. Hours stretch as they compensate. Meaning slips away. And the old office — imperfect, slower, more human — starts to look like a refuge.

Leaders face a choice. They can treat AI deployment as a top-down mandate measured by adoption metrics. Or they can treat it as a design problem that starts with the actual cost borne by the people doing the work. The Adaptavist report, the Harvard Business Review analysis and the steady drumbeat of 2025 and 2026 coverage all point the same direction. Without attention to guardrails, accountability and genuine dialogue, the burden keeps growing. The nostalgia keeps rising. And the workday keeps getting longer even as the technology promises the opposite.