Is AI Producing Major Productivity Gains in Faculty Data Work?

p strongLarge AI-driven productivity gains in faculty data management are still uncommon, although value varies markedly by career stage and discipline./strong/p p Primary Research Group found that only 2.36% of surveyed faculty believed AI tools had increased their data-management productivity by more than 50%. Non-tenured faculty on the tenure track were more likely than tenured or non-tenure-track colleagues to call AI extraordinarily useful. Physics faculty reported the highest use of AI for data visualization./p p Productivity claims should be tied to a task. AI may accelerate code drafting, cleaning suggestions, visualization or summarization while adding time for verification and correction. A fast result that cannot be reproduced, documented or trusted is not a true gain in research productivity./p p Research teams can run small comparisons: measure the time and error rate for a defined workflow with and without AI, retain the prompts or code and note where human intervention was necessary. Differences by field are likely because data formats, regulatory requirements and accepted methods vary./p p The near-term case is incremental rather than transformational. Institutions should invest in evaluated use cases and training, not assume that access to a general AI tool will automatically yield major improvements across all data-intensive work./p p  /p