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New Research Finds Enterprise AI Is Intensifying Work and Driving Burnout

Researchers say explicit norms for using AI can curb workload creep, protecting decision quality.

Overview

  • An eight‑month UC Berkeley embedded study at a 200‑person U.S. tech firm found voluntary AI adoption expanded workloads, blurred roles, and deferred hiring by having existing staff absorb extra tasks.
  • AI introduced parallel workstreams and constant attention‑switching—managing multiple agents, double‑tracking code, and reviving back‑burner tasks—producing sustained cognitive load.
  • A DHR Global survey cited in coverage reported 83% of corporate professionals experiencing burnout, with higher rates among associates and entry‑level workers than among C‑suite leaders.
  • First‑person accounts from engineers describe “AI fatigue,” reporting more output paired with exhaustion, increased review and coordination work, and concerns about skill atrophy.
  • The researchers recommend organizations establish an “AI practice” with deliberate pauses, sequenced workflows, and protected human connection to distinguish real productivity from unsustainable intensity.