ChatGPT is used most widely among those between ** and ** around the world. The youngest group, those under **, are the second largest userbase, and together those under ** account for over ** percent of ChatGPT users. It is perhaps unsurprising that the younger age brackets use the chatbot more than older as that is the common trend with new technologies. Male users were far more numerous than female users, with males representing over ** percent of total users in 2023.

Introduction

ChatGPT Statistics: ChatGPT, an innovation of OpenAI, has made a substantial entrance into the world of technology, shattering all records with its fast user growth. Chat GPT is an AI-generated chatbot that has been making waves in the technical world since its launch. It has a startling ability to mimic human conversation, making it a reliable tool for various tasks that range from drafting emails, answering queries, and writing essays to even assisting with coding as well.

The substructure of ChatGPT is built on OpenAI's GPT-3, which is a large language model that was showered as one of the enlightened language models when introduced in 2020. This article hunts through the captivating ChatGPT Statistics and traverses everything from user growth nationwide to revenue generation and much more.

ChatGPT has taken the world by storm, setting a record for the fastest app to reach a 100 million users, which it hit in two months. The implications of this tool are far-reaching, universities...

Introduction

ChatGPT Statistics: In today’s technologically advancing world, Artificial Intelligence (AI) is no longer just science fiction; it has also become an integral part of everyday life. One of the most exciting examples of AI in action is ChatGPT, a powerful language model developed by OpenAI. ChatGPT is a conversational AI tool capable of generating human-like responses, assisting with a variety of tasks ranging from writing to coding, customer service, education, and more. In everyday life, the implementation of ChatGPT is growing enormously as it enables communication faster, smarter, and more intuitively.

This article examines how ChatGPT operates and its statistical analysis from various perspectives, including its practical applications, and the evolving conversations surrounding its benefits, limitations, and future potential.

According to a survey of adults in the United States conducted in January 2023, ** percent of respondents used ChatGPT to generate text themselves. In comparison, overall ** percent of the female respondents claimed to have never used nor seen anyone else use it, while ** percent of respondents reported having seen text being generated by the AI technology for someone else.

In a survey conducted across **** Southeast Asian countries in February 2023, almost half of the respondents selected collection of personal data as one of the concerns they had regarding the usage of chatbots like ChatGPT. In contrast, ethical issues related to data privacy and intellectual property were a concern for ** percent of the respondents.

Unsurprisingly, those between 18 and 24 were the most likely to use ChatGPT among the various age groups, with ** percent of respondents saying so. This is likely due to younger people adopting tech at a faster rate than older generations.

A major challenge of our time is reducing disparities in access to and effective use of digital technologies, with recent discussions highlighting the role of AI in exacerbating the digital divide. We examine user characteristics that predict usage of the AI-powered conversational agent ChatGPT. We combine behavioral and survey data in a web tracked sample of N=1376 German citizens to investigate differences in ChatGPT activity (usage, visits, and adoption) during the first 11 months from the launch of the service (November 30, 2022). Guided by a model of technology acceptance (UTAUT-2), we examine the role of socio-demographics commonly associated with the digital divide in ChatGPT activity and explore further socio-political attributes identified via stability selection in Lasso regressions. We confirm that lower age and higher education affect ChatGPT usage, but neither gender nor income do. We find full-time employment and more children to be barriers to ChatGPT activity. Using a variety of social media was positively associated with ChatGPT activity. In terms of political variables, political knowledge and political self-efficacy as well as some political behaviors such as voting, debating political issues online and offline and political action online were all associated with ChatGPT activity, with online political debating and political self-efficacy negatively so. Finally, need for cognition and communication skills such as writing, attending meetings, or giving presentations, were also associated with ChatGPT engagement, though chairing/organizing meetings was negatively associated. Our research informs efforts to address digital disparities and promote digital literacy among underserved populations by presenting implications, recommendations, and discussions on ethical and social issues of our findings.

In a survey conducted across four Southeast Asian countries in February 2023, ** percent of the respondents in Singapore selected the collection of personal data as one of the concerns they had regarding the usage of chatbots like ChatGPT. In contrast, this was an issue for ** percent of respondents in Indonesia.

A major challenge of our time is reducing disparities in access to and effective use of digital technologies, with recent discussions highlighting the role of AI in exacerbating the digital divide. We examine user characteristics that predict usage of the AI-powered conversational agent ChatGPT. We combine behavioral and survey data in a web tracked sample of N=1376 German citizens to investigate differences in ChatGPT activity (usage, visits, and adoption) during the first 11 months from the launch of the service (November 30, 2022). Guided by a model of technology acceptance (UTAUT-2), we examine the role of socio-demographics commonly associated with the digital divide in ChatGPT activity and explore further socio-political attributes identified via stability selection in Lasso regressions. We confirm that lower age and higher education affect ChatGPT usage, but neither gender nor income do. We find full-time employment and more children to be barriers to ChatGPT activity. Using a variety of social media was positively associated with ChatGPT activity. In terms of political variables, political knowledge and political self-efficacy as well as some political behaviors such as voting, debating political issues online and offline and political action online were all associated with ChatGPT activity, with online political debating and political self-efficacy negatively so. Finally, need for cognition and communication skills such as writing, attending meetings, or giving presentations, were also associated with ChatGPT engagement, though chairing/organizing meetings was negatively associated. Our research informs efforts to address digital disparities and promote digital literacy among underserved populations by presenting implications, recommendations, and discussions on ethical and social issues of our findings.

Introduction

ChatGPT-4 Statistics: In 2024, ChatGPT-4 has seen a notable surge in user engagement, processing millions of queries daily. Its high accuracy and reliability have made it a popular choice for businesses and individuals. Over 70% of users report high satisfaction, reflecting the model's effectiveness across various applications, from customer service to content creation. ChatGPT-4 excels at interpreting and generating human-like text, thanks to continuous updates that enhance its ability to handle complex queries.

Developed by OpenAI, ChatGPT stands for "Chat Generative Pre-trained Transformer." This advanced model surpasses GPT-3.5 by offering improved accuracy, better context handling, and even image understanding. These features highlight ChatGPT-4's transformative role in AI-driven communication.

As of 2023, about ** percent of the global population who are familiar with ChatGPT were using the tool at least once a month, while over ** percent reported using it weekly. Indian respondents were the most frequent users, having just over ** percent of their respondents claimed to use ChatGPT every day.

This dataset presents ChatGPT usage patterns across U.S. Census regions, based on a 2025 nationwide survey. It tracks how often users followed, partially used, or never used ChatGPT by state region.

This dataset presents ChatGPT usage patterns across different age groups, showing the percentage of users who have followed its advice, used it without following advice, or have never used it, based on a 2025 U.S. survey.

Introduction

OpenAI Statistics: OpenAI, Inc. is an AI company based in San Francisco, California, and was started in December 2015. Its main goal is to build powerful and safe AI systems. OpenAI wants to create smart machines, called AGI, that can do most jobs better than humans, especially the ones that add economic value. This is also best known for developing advanced AI tools like ChatGPT, designed to solve real-world problems and improve daily life. Its mission is to make powerful AI available to everyone in a way that benefits society.

This article includes several current statistical analyses that are taken from different insights, which will guide in understanding the topic effectively as it covers the overall market, sales, user demographics, usage shares, website traffic, and many other factors.

Supplemental Material Contents: · 1-Demographic Information.xlsx: contains the demographic information of the participants in the study. · 2-Forms.zip: contains the forms and questionnaires used to collect data for the experiment: demographic form, pre-study, post-study, and AAR/AI questionnaires. · 3-GitHub-Repository.zip: a copy of the GitHub repository used in the study. · 4-Tutorial Scripts.zip: script used in the experiment with the groups to be consistent with all participants. · 5-Logs-Rubric-Grades.zip: contains the participant data log (commit and PR), rubric for grading submissions, and grades. · 6-RQ1-Data-and-Analysis.zip: contains the data and analysis with respect to RQ1. · 7-RQ2-Data-and-Analysis.zip: contains the data and analysis with respect to RQ2. · 8-Participant Prompts.xlsx: contains the experimental group participant prompts with ChatGPT. 2. Forms.zip The forms zip contains the following files: · Demographics.pdf: a form used to collect demographic information from participants before the study. · Control Pre-Study Questionnaire.pdf: Pre study questionnaire control group (Self-Efficacy Questionnaire) · Control Post-Study Questionnaire.pdf: Post study questionnaire control group (NASA-TLX, Self-Efficacy Questionnaire) · Treatment - AAR_AI task.pdf: Pre and Post task AAR/AI questionnaire for experimental group. · Experimental Pre-Study Questionnaire.pdf: Pre study questionnaire experimental group (Self-Efficacy Questionnaire, Question for Familiarity with AI) · Experimental-Post Study Questionnaire.pdf: Post study questionnaire experimental group (AAR/AI step 7, Continuance Intention, NASA-TLX, HAI Guideline Questions, Self-Efficacy Questionnaire) 3-GitHub-Repository.zip The GitHub repository used in the study: contains the main.py code file and the Readme.md file (having the written instructions for the participants). 4-Tutorial Scripts.zip Contains: · Control-Script.pdf: Script for the control group. · Experimental-Script.pdf: Script for the experimental group. 5-Logs-Rubric-Grades.zip · rubric.pdf: Created rubric for grading task performance. · GitHub-Task3-Log.xlsx: File containing the data regarding the status of commit made and PR raised for each participant. · grades.xlsx: Detailed grades for each participant in experimental (treatment) and control groups. 6-RQ1-Data-and-Analysis.zip Note: The term 'treatment' has been used in the files of this folder to represent the experimental group: participants using ChatGPT for the tasks. · NASA TLX: folder containing the participant data (TLX.xlsx), code for statistical analysis (Stat-TLX.py) and statistical reports (analysis-TLX.csv). · Task Performance: folder containing the participant data (grades.xlsx & Scores.xlsx(overall grade)), code for statistical analysis (Stat-Correctness.py) and statistical reports (analysis.csv). · Self-Efficacy: folder containing: o Self-Efficacy-detailed.xlsx: participant data o Paired Stats: folder containing data (Total Self Efficacy.csv), code for statistical analysis(paired-stats.py), and statistical reports (analysis.csv). o Box plot: folder containing the code for generating the box plot and its output. · Continuance Intention.xlsx: participant data (experimental) for continuance intention of ChatGPT. · Stat-Table-H1-2-Paper.xlsx: Statistics table for NASA TLX and task performance as presented in the paper. 7-RQ2-Data-and-Analysis.zip · AAR_AI-Responses.xlsx: AAR/AI responses filled by participants in experimental group. · Quotation Manager-Faults&Conseq.xlsx: Contains the quotations from AAR/AI responses along with corresponding codes. Also contains the quotes that link faults to consequences in a separate sheet. · Codebook.xlsx: The final codebook (faults and consequences). · HAI-data.xlsx: Contains the reported guideline violations along with disaggregated analysis (grouped by gender). · Likert Plot-HAI: folder contains the code for generating the Likert plot figure presented in the paper.

This dataset was collected for research purposes and contains numerical data representing consumers' attitudes toward AI usage. The data was gathered through a survey conducted from May 22 to June 12, 2024. The dataset covers responses from participants in South Korea, China, Vietnam, and Japan. Key variables include consumer perceptions, adoption patterns, and demographic information to support analysis on regional differences in AI acceptance.

This dataset shows how men and women in the U.S. reported using ChatGPT in a 2025 survey, including whether they followed its advice or chose not to use it.

A chatbot from Chinese AI lab DeepSeek sent shockwaves through the market in January, due to its ability to perform mathematics, coding and reasoning at a similar level to ChatGPT and other top-tier...

According to a survey conducted in 2024, Black and Hispanic teenagers in the United States were more likely to say that they used ChatGPT to help with their schoolwork, at 31 percent, compared to only 22 percent of white teenagers. Teens in grades 11 and 12 were also more likely to use ChatGPT for schoolwork than those in lower grade levels.