ChatGPT is used most widely among those between 25 and 34 around the world. The youngest group, those under 24, are the second largest userbase, and together those under 34 account for over 60 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 65 percent of total users in 2023.

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.

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.

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.

A survey conducted in 2025 among shoppers showed that almost ** percent of gen Z consumers have used AI shopping assistants or ChatGPT to help them with their online purchases. 48 percent of Millennials reported the same habit.

This is the dataset and documents used for the study execution provided by the authors. In this raw data, you can find the scripts used by the evaluators and the TAM form submitted by them during the evaluation process.This raw data is part of the developed work published on ICEIS 2025 by the title of: "Exploring the Use of ChatGPT for the Generation of User Story Based Test Cases: An Experimental Study"All the data presented here is licensed under the CC BY 4.0 license and should be followed for any copyright matter.

According to an August 2023 survey, Gen Z internet users showed were the least keen on using manual search engines such as Google and Yahoo! for finding information online. Around ** percent of Gen Z respondents used these tools, compared to ** percent of total internet users. Instead, Gen Z users preferred using other methods, especially social media platforms, with ** percent of respondents from this generation claiming to do so. There was a notable difference in the use of AI platforms such as chatbots like ChatGPT and Google Gemini, with ** percent of Gen Z users employing them to find information online against the ** percent of the total of internet users.

In recent years, artificial intelligence (AI) has been increasingly used in education and supports teachers in creating educational material and students in their learning progress. AI- driven learning support has recently been further strengthened by the release of ChatGPT, in which users can retrieve expla- nations for various concepts in a few minutes through chat. However, to what extent the use of AI models, such as ChatGPT, is suitable for the creation of didactically and content-wise good exercises for programming courses is not yet known. Therefore, in this paper, we investigate the use of AI-generated exercises for beginner and intermediate programming courses in higher education using ChatGPT. We created 12 exercise sheets with ChatGPT for a beginner to intermediate programming course focusing on the objects-first approach. We report our process, prompts, and experience using ChatGPT for this task and outline good practices we identified. The generated exercises are assessed and revised, primarily using ChatGPT, until they met the requirements of the programming course. We assessed the quality of these exercises by using them in our course as external teaching assignment at the University of Education Ludwigsburg and let the students evaluate them. Results indicate the quality of the generated exercises and the time-saving for creating them using ChatGPT. However, our experience showed that while it is fast to generate a good version of an exercise, almost every exercise requires minor manual changes to improve its quality.

Context

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Based on their wikipedia page

ChatGPT (Chat Generative Pre-trained Transformer) is a large language model-based chatbot developed by OpenAI and launched on November 30, 2022, that enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. Successive prompts and replies, known as prompt engineering, are considered at each conversation stage as a context.

These reviews were extracted from Google Store App

Usage

This dataset should paint a good picture on what is the public's perception of the app over the years. Using this dataset, we can do the following

1. Extract sentiments and trends
2. Identify which version of the app had the most positive feedback, the worst.
3. Use topic modeling to identify the pain points of the application.

(AND MANY MORE!)

Note

Images generated using Bing Image Generator

The AI Image Generator Market size was valued at USD 356.1 USD Million in 2023 and is projected to reach USD 1094.58 USD Million by 2032, exhibiting a CAGR of 17.4 % during the forecast period. AI image generator refers to a software application for generating image data by means of artificial intelligence, utilizing such models as deep learning, neural networks, and others. Some of them are GANs which stand for Generative Adversarial Networks, VAEs which stand for Variational Autoencoders, and diffusion models. Essential characteristics include crystal clear display of the resultant image, conversion of the source image to another style, and image improvement. It makes use for the generation of art, designing, virtual fitting, and even in-game design . These generators facilitate the quickly and cheaply generated visualization and image modifications depending on certain parameters or styles, hence changing the creative landscapes of various industries by improving efficiency and creativity. Recent developments include: September 2023 - OpenAI, a company specializing in the generative AI industry, introduced DALL-E 3, the latest version of its image generator. This upgrade, powered by the ChatGPT controller, produces high-quality images based on natural-language prompts and incorporates ethical safeguards., May 2023 - Stability AI introduced StableStudio, an open-source version of its DreamStudio AI application, specializing in converting text into images. This open-source release enabled developers and creators to access and utilize the technology, creating a wide range of applications for text-to-image generation., April 2023 - VanceAI launched an AI text-to-image generator called VanceAI Art Generator, powered by Stable Diffusion. This tool could interpret text descriptions and generate corresponding artworks. Users could combine image types, styles, artists, and adjust sizes to transform their creative ideas into visual art., March 2023 - Adobe unveiled Adobe Firefly, a generative AI tool in beta, catering to users without graphic design skills, helping them to create images and text effects. This announcement coincided with Microsoft’s launch of Copilot, offering automatic content generation for 365 and Dynamics 365 users. These advancements in generative AI provided valuable support and opportunities for individuals facing challenges related to writing, design, or organization., March 2023 - Runway AI introduced Gen-2, a combination of AI models capable of producing short video clips from text prompts. Gen-2, an advancement over its predecessor Gen-1, would generate higher-quality clips and provide users with increased customization options.. Key drivers for this market are: Growing Adoption of Augmented Reality (AR) and Virtual Reality (VR) to Fuel the Market Growth. Potential restraints include: Concerns related to Data Privacy and Creation of Malicious Content to Hamper the Market. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

According to a worldwide study conducted by Capgemini in April 2023, around ** to ** percent of all interviewed users familiar with generative artificial intelligence tools have used chatbots. Meanwhile, between * and * percent of all interviewees used generative AI search tools like ChatGPT and Gemini, with Gen X users being the most keen on using it.

This dataset provides a daily-updated collection of user reviews and ratings specifically for the ChatGPT Android application. It includes crucial information such as the review text, associated ratings, and the dates when reviews were posted. The dataset also details the relevancy of each review. It serves as a valuable resource for understanding user sentiment, tracking app performance over time, and analysing trends within the AI and Large Language Model (LLM) application landscape.

Columns

• reviewId: A unique identifier assigned to each user review.
• id: An additional, distinct identifier associated with each review.
• userName: The name of the user who submitted the review.
• content: The textual body or comment provided by the user in their review.
• score: The numerical rating given by the user, typically on a scale from 1 to 5, indicating their satisfaction or experience.
• thumbsUpCount: The total number of 'likes' or positive reactions that a particular review has received.
• appVersion: The specific version of the ChatGPT Android application that the user was running when they posted their review.
• reviewDate: The precise date and time at which the user review was originally posted.

Distribution

The dataset is primarily available in a tabular format, typically a CSV file, facilitating easy integration and analysis. It comprises over 637,000 unique reviews, reflecting a substantial volume of user feedback. This dataset is updated on a daily basis, ensuring access to the latest user opinions and rating trends. While the exact file size is not specified, the number of records indicates a considerable volume of data.

Usage

This dataset is ideal for various analytical applications, including: * Sentiment Analysis: Extracting and understanding user emotions and opinions towards the ChatGPT Android app. * Natural Language Processing (NLP) Tasks: Training and testing NLP models for text classification, entity recognition, and language generation based on real-world user input. * App Performance Monitoring: Tracking changes in user ratings and feedback over time to gauge application performance and identify areas for improvement. * Market Research: Gaining insights into user perception of AI and LLM applications within the mobile market. * Competitive Analysis: Comparing user feedback for the ChatGPT app against other similar applications. * Feature Prioritisation: Identifying desired features or common pain points mentioned by users to inform product development.

Coverage

This dataset offers global coverage, collecting reviews from users across the world. The time range for the reviews spans from 25 July 2023 to 30 June 2025. This extensive period allows for longitudinal studies of user sentiment and app evolution. It captures feedback from a diverse demographic of ChatGPT Android app users. Some data points, such as appVersion, may occasionally have null values.

License

CC-BY-NC-SA

Who Can Use It

• Data Scientists and Analysts: For conducting sentiment analysis, topic modelling, and training machine learning models on large volumes of text data.
• App Developers and Product Managers: To understand user feedback, identify bugs, track feature requests, and plan future app enhancements.
• Market Researchers: To assess market trends, consumer behaviour, and the reception of AI-powered applications.
• Academic Researchers: For studies on human-AI interaction, user experience, and public perception of emerging technologies.
• Businesses in the AI/LLM Sector: To perform competitive analysis and inform strategic decisions based on real user feedback.

Dataset Name Suggestions

• ChatGPT Android App Reviews
• Daily ChatGPT Mobile Ratings
• AI App User Feedback Data
• ChatGPT Google Play Reviews
• User Sentiment for ChatGPT App

Attributes

Original Data Source: ChatGPT reviews [DAILY UPDATED]

ChatGPT is the most widely used text generation AI tool in the world in 2023, with nearly ** percent share of users. Its launch in late 2022 marked a significant spike in both awareness and interest in AI tools and their development.

Recent developments include: A more advanced version of Google's conversational AI service, Bard, with more features, which would compete with Microsoft-backed ChatGPT, is apparently getting ready to launch in 2023. Bard, which was introduced in February, seeks to provide novel ways for users to interact with information, including text, photos, videos, and audio. Experts in the field have claimed that, in contrast to ChatGPT, which went live last year, the platform has not attracted as many users., To deliver next-generation Conversational AI solutions to Avaya's substantial global base of contact centre clients, Cognigy, the market leader in Conversational AI, today announced at Enterprise Connect 2023 an expanded partnership with Avaya, a leading global in solutions to enhance and simplify communications and collaboration., Cognigy's revolutionary Conversational AI and Generative AI solutions, which are integrated with the Avaya Experience Platform, will allow Avaya customers to develop next-generation customer experiences while boosting productivity and boosting staff engagement.. Key drivers for this market are: Automating routine tasks and providing 24/7 support with AI-driven chatbots and virtual assistants helps businesses reduce operational costs and improve scalability. Potential restraints include: Developing and deploying effective conversational AI systems can be complex, requiring integration with existing systems and significant customization to meet business needs. Notable trends are: The rise of voice assistants like Amazon Alexa, Google Assistant, and Apple's Siri is driving the adoption of voice-based conversational AI, particularly in consumer-facing applications..

During a 2022 survey conducted among professionals in the United States, it was found that 29 percent of respondents belonging to Gen Z used generative AI tools. Moreover, 28 percent of Gen X and 27 percent of millennials respondents used such tools, respectively.

Generative AI

Generative artificial intelligence (AI) refers to algorithms that focus on producing new content, such as text, images, music, speech, code, or video. Generative AI is part of deep learning, the machine learning branch which aims to reduce the manual work of programming parameters for AI. Currently, researchers and developers use generative AI in various industries, like advertising and marketing, but rumors suggest that more businesses and consumers will adopt this technology in the near future to perform a wide range of tasks.

ChatGPT

An example of generative AI is ChatGPT, the famous chatbot software launched in November 2022 by the American startup OpenAI, which is also well known for its art generative AI program Dall-E. The chatbot can produce text based on given inputs, recognize mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT has quickly gained popularity, becoming one of the major breakthroughs of the last few decades in the technology industry. Indeed, it was the fastest IoT service to accumulate a one-million user base, in only five days.

The AI answer generator market is experiencing rapid growth, driven by increasing demand for automated content creation, improved customer service experiences, and the need for efficient data processing across various sectors. The market, estimated at $2 billion in 2025, is projected to exhibit a robust Compound Annual Growth Rate (CAGR) of 25% from 2025 to 2033, reaching an estimated $10 billion by 2033. This significant expansion is fueled by several key factors. The rising adoption of AI across industries like education, customer support, and marketing is a major driver, as businesses seek to enhance efficiency and reduce operational costs. Furthermore, advancements in Natural Language Processing (NLP) and machine learning are continuously improving the accuracy and sophistication of AI answer generators, leading to wider acceptance and application. The emergence of innovative business models, such as subscription-based access and API integrations, is also contributing to market expansion. However, challenges remain, including concerns about data privacy, the potential for biased outputs, and the ongoing need for human oversight to ensure accuracy and ethical considerations. The market is segmented by application (e.g., customer service chatbots, educational tools, content generation), deployment model (cloud-based, on-premises), and end-user industry (e.g., education, healthcare, finance). Key players in the market, such as Answer.Al, ChatGPT, and others listed, are continuously innovating to improve their offerings and expand their market share. The competitive landscape is dynamic, with ongoing mergers and acquisitions, strategic partnerships, and the development of new features to differentiate products. Future growth will be largely determined by factors such as technological advancements, regulatory frameworks, and the increasing adoption of AI across diverse sectors. Addressing concerns surrounding ethical AI development and ensuring responsible innovation will be crucial for sustainable growth in this rapidly evolving market.

In March 2023, OpenAI released the latest version of ChatGPT, GPT-4, which addressed some of the concerns users had with GPT-3.5. The concerns were mainly about the misuse of the AI-powered chatbot and its safety measurements. In the new report, the company claimed that in the version 4, the model's response rate to requests for disallowed content has decreased by ** percent. The tool's generation of toxic content has been reduced by almost ** percent. In response to sensitive requests, such as medical advice and self-harm, the model follows company policies ** percent more often.

Prompts play a crucial role in guiding language models like ChatGPT to generate relevant and coherent responses. They serve as instructions or cues that provide context and steer the model's understanding and output. Effective prompts can shape the conversation, elicit specific information, or encourage creative responses. Prompt engineering, on the other hand, refers to the process of designing and refining prompts to achieve desired outcomes. Both prompts and prompt engineering are important for several reasons

prompts and prompt engineering are essential for guiding language models, enabling control over outputs, generating desired content, fostering creativity, and enhancing the overall user experience. They form a critical component in the interaction between users and AI systems, ensuring meaningful and contextually appropriate conversations. This is one of the inspiration behind this dataset.

In this dataset we generated this prompts samples by various chatbots and few from Bard and from ChatGpt. the main intention and idea behind that is 1) Prompt Engineering 2) Rich data . This type of few samples of prompt which for helpful for training various generative ai applications.but in this dataset the prompts samples are low amount .but you generate synthetic data from that .

Comprehensive comparison of Latency (Time to First Token) vs. Output Speed (Output Tokens per Second) by Model

Comparison of Tokens used to run all evaluations in the Artificial Analysis Intelligence Index by Model