A wave of pre–AI nostalgia is sweeping through the modern workplace, as new research from digital transformation consultancy Adaptavist reveals that two-thirds (65%) of knowledge workers regularly feel nostalgic for how work operated before generative AI, and 38% say they would remove GenAI tools from the world entirely if they had the chance.

The research, which surveyed 2,500 professionals across the UK, US, Canada, Germany and Spain, found that rather than freeing workers from drudgery, AI has introduced new pressures, eroded the value of skilled work, and left employees feeling less engaged and less valued than before.

Nearly a third (30%) of respondents said they preferred how work operated before GenAI tools were widely adopted, with a further 26% expressing no preference either way. The desire to turn back the clock is stronger among younger workers: 40% of both Gen Z and Millennials say they would remove GenAI from the world, compared to 32% of Gen X and 29% of Boomers.

Creative and Ethical Deficit

One of the leading drivers for this ‘pre-AI nostalgia’ is the creative and ethical trade off, with many workers believing their work held more value before the widespread implementation of GenAI.

About a third (31%) of workers who would remove AI say they would do so because they believe it reduces creativity.

On the other hand, 29% cite concerns over misuse, and 28% worry about surveillance and privacy.

Just under half (46%) say that dealing with low-quality ‘AI slop’ makes their job feel less meaningful and more repetitive, with 37% admitting it has made them less engaged at work overall.

Verification Tax

Perhaps the most striking finding is the gap between AI’s promise of efficiency and the reality workers are experiencing day-to-day.

Workers are paying a verification tax, with 42% now spending more time verifying and fact-checking AI output than the time they actually save by using it.

Poor quality AI-generated work is actively slowing down projects for 49% of workers, while 55% believe it is reducing overall team efficiency.

The influx of low-quality AI-generated content is damaging morale and making the modern workplace feel more sluggish and harder to navigate than the one workers left behind.

Human vs Machine

Workers are also grappling with an uncomfortable new reality: being measured against machines.

Half (50%) feel their performance is now being compared – fairly or not – to AI-generated output.

A quarter (25%) say they use AI simply to meet workload demand, and 23% use it just to keep up with colleagues.

Workers now face intense pressure to improve performance (26%), improve quality (25%), and be more efficient (24%) – simply to keep pace in a machine-accelerated environment.

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Despite the frustration, this is not a wholesale rejection of AI. Sentiment toward organisational AI strategies remains broadly positive: 67% of workers would like their organisation to increase AI use, 69% trust that AI is being used ethically, and 66% say their organisation has been transparent about its adoption.

Yet 36% of workers often do not understand why they are expected to use AI in their role, and an equal proportion report AI fatigue as a result. The findings suggest that adoption is not the same as engagement, and that the gap between the two is where disillusionment takes root.

“These findings point to an underlying gap we see in most AI implementations,” Neal Riley, AI Innovation Lead at The Adaptavist Group, said.

“It is much easier for organisations to focus on adoption metrics – who is using AI, how often they are using it – than it is to measure its impact on the work itself.

“By understanding the nature of the work and the different value streams across your business, you can more accurately measure outcomes and impact rather than simply counting actions.

“When AI is introduced thoughtfully, with the right guardrails and genuine support for the people using it, it can enhance rather than erode what makes work meaningful and impactful.