Current and Future Use of Large Language Models for Knowledge Work

Large Language Models (LLMs) have introduced a paradigm shift in interaction with AI technology, enabling knowledge workers to complete tasks by specifying their desired outcome in natural language. LLMs have the potential to increase productivity and reduce tedious tasks in an unprecedented way. A systematic study of LLM adoption for work can provide insight into how LLMs can best support these workers. To explore knowledge workers' current and desired usage of LLMs, we ran a survey (n=216). Workers described tasks they already used LLMs for, like generating code or improving text, but imagined a future with LLMs integrated into their workflows and data. We ran a second survey (n=107) a year later that validated our initial findings and provides insight into up-to-date LLM use by knowledge workers. We discuss implications for adoption and design of generative AI technologies for knowledge work.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757403
Citations
2
Primary Topic
Personal Information Management and User Behavior
Type
article
Field-Weighted Citation Impact
8.34
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article

Current and Future Use of Large Language Models for Knowledge Work

Werner Geyer, Michelle Brachman, Casey Dugan, Amina El-Ashry
2 citations
Proceedings of the ACM on Human-Computer Interaction
Personal Information Management and User Behavior
8.34
article

Current and Future Use of Large Language Models for Knowledge Work

Werner Geyer, Michelle Brachman, Casey Dugan, Amina El-Ashry
article en
2 citations

Abstract

Large Language Models (LLMs) have introduced a paradigm shift in interaction with AI technology, enabling knowledge workers to complete tasks by specifying their desired outcome in natural language. LLMs have the potential to increase productivity and reduce tedious tasks in an unprecedented way. A systematic study of LLM adoption for work can provide insight into how LLMs can best support these workers. To explore knowledge workers' current and desired usage of LLMs, we ran a survey (n=216). Workers described tasks they already used LLMs for, like generating code or improving text, but imagined a future with LLMs integrated into their workflows and data. We ran a second survey (n=107) a year later that validated our initial findings and provides insight into up-to-date LLM use by knowledge workers. We discuss implications for adoption and design of generative AI technologies for knowledge work.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
Cambridge Scientific (United States) (US)
Openalex Percentile: Top 3%
Personal Information Management and User Behavior
8.34
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