AI Efficiency Gains Mostly Reabsorbed into Work, Not Leisure or Pay

Artificial intelligence tools are significantly boosting productivity, but the time saved is largely being reinvested into other tasks rather than leading to reduced working hours or increased pay, according to recent research and Israeli data. While employees may complete tasks faster, the freed-up time is typically allocated to new or existing responsibilities, with 85% of users reporting that saved time was reassigned. This phenomenon is observed across various professions, including customer support and software development, where AI can expedite processes.

Studies indicate that the benefits of AI are most pronounced for less experienced workers, leading to substantial improvements in task completion and satisfaction. However, highly experienced professionals sometimes see a decrease in performance and customer satisfaction when using AI for tasks outside its core capabilities, or even when using it for familiar tasks, as seen in a study of experienced software developers who were slowed down by AI tools despite believing they were saving time. This suggests that perceived time savings do not always align with actual efficiency gains.

In Israel, AI adoption is growing, with 39% of businesses now using AI in production, up from 28% a year prior. While AI is performing tasks previously done by employees in 21% of businesses, most employers (88%) report no impact on overall staffing levels, with only a small percentage noting recruitment or workforce reductions. The Bank of Israel also found no indication that AI has reduced employment in the high-tech sector, where jobs and vacancies have actually increased.

Experts advise a structured approach to integrating AI, emphasizing the need for clear agreements between employers and employees on how time savings will be utilized. This includes measuring actual efficiency gains, accounting for post-completion work like revisions, defining new responsibilities or training opportunities, and establishing trial periods to assess the impact before adjusting work targets or compensation. There's also a concern, particularly among younger workers, that AI might be training their replacements, highlighting the need for open discussion about career development alongside AI adoption.