A growing number of workers across white-collar fields express nostalgia for their pre-AI work environments amid concerns about the rapidly increasing role of artificial intelligence in the workplace. A recent survey by consultancy Adaptavist found that approximately 65% of white-collar employees regularly long for the working conditions before AI technologies became widespread. The study also revealed that about one-third of respondents believe generative AI hinders creativity, while a similar proportion worry about the potential misuse of the technology.

Despite early promises that AI would reduce monotonous tasks and ease workloads, many workers report that the opposite has occurred. Instead, AI tools have accelerated the pace of work and expanded job responsibilities, leaving employees feeling overwhelmed. Moreover, nearly half of the survey participants said that the necessity to fact-check AI-generated outputs has added an additional layer of labor, contradicting expectations that automation would simplify work processes.

This sentiment is echoed in anecdotal observations from various industries. While generating reports or content using AI might appear efficient, the verification process is time-consuming, as these tools frequently produce errors or irrelevant information. Professionals such as lawyers and consultants have faced reprimands for submitting AI-produced materials containing fabricated references, highlighting risks associated with uncritical use of the technology.

The impact of AI on creativity also remains a subject of debate. Academic studies suggest that although generative AI can introduce novel elements, it often leads to repetition and a narrowing of idea diversity. For instance, research from the Wharton School at the University of Pennsylvania indicated that relying heavily on platforms like ChatGPT for creative input can result in homogenous outputs and a depletion of unique concepts. These findings raise concerns about the long-term effects of AI on innovation and originality.

Organizational approaches to AI adoption have further fueled employee uncertainty. Many companies initially encouraged broad experimentation with AI to automate routine work, but more recently some have sought to tighten controls to manage costs and address ethical or environmental concerns. This shift has left workers navigating inconsistent messaging about the role of AI in their daily tasks.

Public attitudes toward AI also reveal complexities beyond outright acceptance or rejection. In May, former Google CEO Eric Schmidt received a negative reaction from students when urging them to embrace the AI revolution, underscoring unease about the pace and implications of technological change. Commentators draw parallels between current protests and the 18th-century Luddite movement, suggesting that resistance often stems from concerns about how innovations are implemented rather than blanket opposition to technology itself.

Experts emphasize that nostalgia for earlier workplace experiences often reflects a deeper desire for stability, agency, and economic assurance during times of rapid change. Jason Dressel, chief executive of the History Factory, notes that AI’s integration into everyday work challenges traditional perceptions of individual contribution and value.

While the encroachment of AI in creative industries raises questions about cultural homogenization and intellectual property, some observers caution against idealizing the past. The entertainment and publishing sectors long produced formulaic and repetitive content prior to AI’s emergence. Additionally, critics question whether traditional training models—such as requiring graduates to perform repetitive tasks—remain suitable when AI can automate such functions.

Ultimately, experts suggest that reflecting honestly on past work practices can help identify which elements to preserve and which to reform in the AI era, but this requires balancing realistic appraisals with an openness to new possibilities.