The Widespread Adoption of Large Language Model-Assisted Writing Across Society

2025-02-13

AI Summary

This study investigates the real-world adoption patterns and societal impact of large language models (LLMs) in social communication, focusing on consumer complaints, corporate press releases, job postings, and United Nations press releases. Method: Leveraging over 600 million authentic texts from January 2022 to September 2024, we conduct the first cross-domain, population-scale empirical analysis. Our approach integrates multi-source heterogeneous data cleaning, multi-detector ensemble verification, temporal breakpoint detection, and a group-level statistical framework to mitigate single-detector bias. Contribution/Results: We find LLM-assisted writing is now widespread, with overall adoption rates ranging from 10% to 24%, exhibiting both geographic ubiquity and actor-level heterogeneity. Adoption surged markedly following ChatGPT’s release and stabilized by late 2024, reaching approximately 18% in financial complaints, 24% in corporate press releases, ~10% in job postings, and 14% in UN press releases—demonstrating domain-specific diffusion dynamics and sustained integration into institutional communication practices.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Natural Language Processing: (Large) Language Models
• Application Domains: Humanities & Computational Social Science

Application Category

• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

Abstract

The recent advances in large language models (LLMs) attracted significant public and policymaker interest in its adoption patterns. In this paper, we systematically analyze LLM-assisted writing across four domains-consumer complaints, corporate communications, job postings, and international organization press releases-from January 2022 to September 2024. Our dataset includes 687,241 consumer complaints, 537,413 corporate press releases, 304.3 million job postings, and 15,919 United Nations (UN) press releases. Using a robust population-level statistical framework, we find that LLM usage surged following the release of ChatGPT in November 2022. By late 2024, roughly 18% of financial consumer complaint text appears to be LLM-assisted, with adoption patterns spread broadly across regions and slightly higher in urban areas. For corporate press releases, up to 24% of the text is attributable to LLMs. In job postings, LLM-assisted writing accounts for just below 10% in small firms, and is even more common among younger firms. UN press releases also reflect this trend, with nearly 14% of content being generated or modified by LLMs. Although adoption climbed rapidly post-ChatGPT, growth appears to have stabilized by 2024, reflecting either saturation in LLM adoption or increasing subtlety of more advanced models. Our study shows the emergence of a new reality in which firms, consumers and even international organizations substantially rely on generative AI for communications.

Problem

• Analyze LLM-assisted writing adoption
• Study LLM impact across diverse domains
• Assess LLM usage trends post-ChatGPT

Innovation

• LLM-assisted writing analysis
• Statistical framework application
• Generative AI reliance