AI ‘Time-Savers’ Paradoxically Pile More Work on Employees’ Plates

While 96% of executives believe AI will boost productivity, 77% of employees report the opposite. AI tools often require workers to review outputs for accuracy and learn new workflows alongside existing duties. Instead of replacing work, AI frequently adds oversight responsibilities. This has led to 71% of full-time employees experiencing burnout. The productivity paradox continues as companies struggle to measure AI’s value and integrate it effectively.

While businesses rush to adopt artificial intelligence tools that promise to save time and boost efficiency, a troubling trend has emerged for the workers using them. New data reveals a stark disconnect between leadership expectations and employee reality when it comes to AI implementation in the workplace.

Nearly all C-suite leaders (96%) expect AI to boost productivity, yet 77% of employees report the opposite effect. Workers say AI has actually decreased productivity and increased their workload. This gap between potential and reality shows how AI is being deployed in many companies. This pattern mirrors the productivity paradox observed during previous waves of computer technology adoption, where expected efficiency gains failed to materialize despite significant investments.

The AI productivity promise falls flat as workers shoulder heavier burdens while executives celebrate potential gains.

Employees now spend significant time reviewing AI-generated content for accuracy. They must learn new tools and workflows while maintaining their existing responsibilities. Rather than replacing work, AI often adds more layers of oversight, requiring employees to cross-check and correct outputs.

The productivity paradox becomes clearer when examining daily workflows. While AI might speed up individual tasks, these gains are offset by new inefficiencies elsewhere. Workers find themselves in more meetings, handling more coordination, and managing new demands on top of their core job functions.

This increased workload is taking a toll. About 71% of full-time employees report experiencing burnout attributed to AI-driven workload increases. The constant pressure to produce more in less time leads to emotional exhaustion and stress.

Training requirements present another challenge. Workers must devote considerable effort to upskilling and continuous learning. Some worry about skill erosion as traditional processes are replaced, potentially limiting natural expertise development and career growth. Similar challenges face the renewable sector where workers must continuously adapt to rapid technological advances despite creating 4.9% more jobs in 2023 than the previous year.

The benefits of AI remain localized and unstructured at the individual level. Companies struggle to measure the value created by AI at scale or to change organizational processes to capture efficiencies. These productivity gains tend to be privatized by employees as surplus time absorption often occurs through meetings and workplace distractions.

While a task might be completed faster, the overall structure of production often remains unchanged.

This reality check suggests that for AI to deliver on its promises, organizations need to rethink how these tools integrate into existing workflows rather than simply adding them to employees’ already full plates.