Disruptive technologies such as ChatGPT and similar Large Language Models (LLMs) have transformed mundane everyday tasks of information users since their debut in late 2022. In this study, we leverage uses and gratifications theory to test a distinct set of motivations that drive users’ satisfaction and continued use intentions of ChatGPT and similar large language models. Data were collected using a national online survey of 323 adults residing in the United States. We conducted data analysis using Partial Least Squares (PLS-SEM) to investigate both direct and indirect impact of factors on users' gratification, thereby influencing the continued utilization of these tools for everyday information seeking. Results show four motivational factors - social influence, trust, personalization, and perceived usefulne ss - that positively influence users' satisfaction or sense of gratification, impacting their intentions to continue using these tools. This is one of the few early studies of ChatGPT and other LLMs from an information science perspective. KEYWORDS Information seeking; ChatGPT; Large Language Model (LLM); Use and Gratification; Continued use intention INTRODUCTION Disruptive technologies usher in new ways of doing things. Specifically, they upend “systems or habits” because they can do the task or the thing faster and arguably better (Smith, 2022). The 21st century has been marked by the rise of several disruptive technologies, from blockchains to cloud s
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