The global number of AI tools users in the 'AI Tool Users' segment of the artificial intelligence market was forecast to continuously increase between 2025 and 2031 by in total ***** million (+****** percent). After the tenth consecutive increasing year, the number of AI tools users is estimated to reach *** billion and therefore a new peak in 2031. Notably, the number of AI tools users of the 'AI Tool Users' segment of the artificial intelligence market was continuously increasing over the past years.Find more key insights for the number of AI tools users in countries and regions like the market size in the 'Generative AI' segment of the artificial intelligence market in Australia and the market size change in the 'Generative AI' segment of the artificial intelligence market in Europe.The Statista Market Insights cover a broad range of additional markets.

First, please create a public dataset. Resources that do not require authorization can be uploaded directly to the resources area. If a resource requires authorization to access, please store it in the cloud drive provided by the account membership system, which supports access control. Next, dataset administrators should add a custom field named "needapply" with a value of "true" to the dataset. This enables an application process. Once approved, authorized users will be able to download the restricted data.

The AI Training Dataset In Healthcare Market size was valued at USD 341.8 million in 2023 and is projected to reach USD 1464.13 million by 2032, exhibiting a CAGR of 23.1 % during the forecasts period. The growth is attributed to the rising adoption of AI in healthcare, increasing demand for accurate and reliable training datasets, government initiatives to promote AI in healthcare, and technological advancements in data collection and annotation. These factors are contributing to the expansion of the AI Training Dataset In Healthcare Market. Healthcare AI training data sets are vital for building effective algorithms, and enhancing patient care and diagnosis in the industry. These datasets include large volumes of Electronic Health Records, images such as X-ray and MRI scans, and genomics data which are thoroughly labeled. They help the AI systems to identify trends, forecast and even help in developing unique approaches to treating the disease. However, patient privacy and ethical use of a patient’s information is of the utmost importance, thus requiring high levels of anonymization and compliance with laws such as HIPAA. Ongoing expansion and variety of datasets are crucial to address existing bias and improve the efficiency of AI for different populations and diseases to provide safer solutions for global people’s health.

Between 2023 and 2027, the majority of companies surveyed worldwide expect big data to have a more positive than negative impact on the global job market and employment, with ** percent of the companies reporting the technology will create jobs and * percent expecting the technology to displace jobs. Meanwhile, artificial intelligence (AI) is expected to result in more significant labor market disruptions, with ** percent of organizations expecting the technology to displace jobs and ** percent expecting AI to create jobs.

Percent Users vs Non-Users Distribution by Era - Females. Data underlying the fifth figure of Part 2 of the FY2018 Utilization Profile, a report on Veterans' use of VA benefits and services.

Analysis of ‘Proportion of people who use mobile phones for private reasons (from 16 to 74 years old) by autonomous communities and sex (API identifier: 45691)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-175-45691 on 07 January 2022.

--- Dataset description provided by original source is as follows ---

Table of INEBase Proportion of people who use mobile phones for private reasons (from 16 to 74 years old) by autonomous communities and sex. Annual. Autonomous Communities and Cities. Survey on Equipment and Use of Information and Communication Technologies in Households

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Percentage of young people (16 to 24 years old) who in the last 12 months have used any of the computer skills in information gathered for Autonomous Communities and Cities and type of computer skills (API identifier: 46294)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-175-46294 on 07 January 2022.

--- Dataset description provided by original source is as follows ---

Table of INEBase Percentage of young people (16 to 24 years old) who in the last 12 months have used any of the computer skills in information gathered for Autonomous Communities and Cities and type of computer skills. Annual. Survey on Equipment and Use of Information and Communication Technologies in Households

--- Original source retains full ownership of the source dataset ---

This is a historical measure for Strategic Direction 2023. For more data on Austin demographics please visit austintexas.gov/demographics. This measure answers the question of percentage of people working in Austin that come from outside Austin. The LODES program collects administrative records from unemployment insurance reporting systems. Residence location is derived from annual federal administrative data. LODES are produced and released at the census block level, with all tabulations consisting of paired, origin-destination flows that can also be aggregated to the residence and workplace margins.

AI Content Detector Market size is growing at a moderate pace with substantial growth rates over the last few years and is estimated that the market will grow significantly in the forecasted period i.e. 2024 to 2031.

Global AI Content Detector Market Drivers

Rising Concerns Over Misinformation: The proliferation of fake news, misinformation, and inappropriate content on digital platforms has led to increased demand for AI content detectors. These systems can identify and flag misleading or harmful content, helping to combat the spread of misinformation online.

Regulatory Compliance Requirements: Stringent regulations and legal obligations regarding content moderation, data privacy, and online safety drive the adoption of AI content detectors. Organizations need to comply with regulations such as the General Data Protection Regulation (GDPR) and the Digital Millennium Copyright Act (DMCA), spurring investment in AI-powered content moderation solutions.

Growing Volume of User-Generated Content: The exponential growth of user-generated content on social media platforms, forums, and websites has overwhelmed traditional moderation methods. AI content detectors offer scalable and efficient solutions for analyzing vast amounts of content in real-time, enabling platforms to maintain a safe and healthy online environment for users.

Advancements in AI and Machine Learning Technologies: Continuous advancements in artificial intelligence and machine learning algorithms have enhanced the capabilities of content detection systems. AI models trained on large datasets can accurately identify various types of content, including text, images, videos, and audio, with high precision and speed.

Brand Protection and Reputation Management: Businesses prioritize brand protection and reputation management in the digital age, as negative content or misinformation can severely impact brand image and consumer trust. AI content detectors help organizations identify and address potentially damaging content proactively, safeguarding their reputation and brand integrity.

Demand for Personalized User Experiences: Consumers increasingly expect personalized online experiences tailored to their preferences and interests. AI content detectors analyze user behavior and content interactions to deliver relevant and engaging content, driving user engagement and satisfaction.

Adoption of AI-Powered Moderation Tools by Social Media Platforms: Major social media platforms and online communities are investing in AI-powered moderation tools to enforce community guidelines, prevent abuse and harassment, and maintain a positive user experience. The need to address content moderation challenges at scale drives the adoption of AI content detectors.

Mitigation of Online Risks and Threats: Online platforms face various risks and threats, including cyberbullying, hate speech, terrorist propaganda, and child exploitation content. AI content detectors help mitigate these risks by identifying and removing harmful content, thereby creating a safer online environment for users.

Cost and Resource Efficiency: Traditional content moderation methods, such as manual review by human moderators, are time-consuming, labor-intensive, and costly. AI content detectors automate the moderation process, reducing the need for human intervention and minimizing operational expenses for organizations.

This EnviroAtlas dataset shows the employment rate, or the percent of the population aged 16-64 who have worked in the past 12 months. The employment rate is a measure of the percent of the working-age population who are employed. It is an indicator of the prevalence of unemployment, which is often used to assess labor market conditions by economists. It is a widely used metric to evaluate the sustainable development of communities (NRC, 2011, UNECE, 2009). This dataset is based on the American Community Survey 5-year data for 2008-2012. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This dataset supports measure M.C.5 of SD 2023. The sources of data are the American Community Survey and the Austin Transportation Department. Each row displays the percentage of people in different demographic categories who participated in mobility engagement process as compared to percentage of people in the same demographic category in Austin. This dataset can be used to understand how well the City reaches different communities and subpopulations when soliciting public input. View more details at https://data.austintexas.gov/stories/s/Percentage-of-participants-in-mobility-public-enga/pfnb-5uev/

Singapore was the nation with the highest combined value where enterprises were exploring or had actively deployed AI within their business in 2023. China, India, and the UAE were all close behind, with over ** percent of respondents claiming exploration or deployment of AI. Western countries, in particular European mainland nations such as France, Germany, and Italy, had the highest rate of non-usage or no exploration of AI, though even the U.S. had a similar share of enterprises not engaged with AI. This may reflect the specialized industries that thrive in those countries, needing individualized human skills to operate.

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.

The Big Data Technology Market size was valued at USD 349.40 USD Billion in 2023 and is projected to reach USD 918.16 USD Billion by 2032, exhibiting a CAGR of 14.8 % during the forecast period. Big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business problems that wouldn’t have been able to tackle before. Big data technology is defined as software-utility. This technology is primarily designed to analyze, process and extract information from a large data set and a huge set of extremely complex structures. This is very difficult for traditional data processing software to deal with. Among the larger concepts of rage in technology, big data technologies are widely associated with many other technologies such as deep learning, machine learning, artificial intelligence (AI), and Internet of Things (IoT) that are massively augmented. In combination with these technologies, big data technologies are focused on analyzing and handling large amounts of real-time data and batch-related data. Recent developments include: February 2024: - SQream, a GPU data analytics platform, partnered with Dataiku, an AI and machine learning platform, to deliver a comprehensive solution for efficiently generating big data analytics and business insights by handling complex data., October 2023: - MultiversX (ELGD), a blockchain infrastructure firm, formed a partnership with Google Cloud to enhance Web3’s presence by integrating big data analytics and artificial intelligence tools. The collaboration aims to offer new possibilities for developers and startups., May 2023: - Vpon Big Data Group partnered with VIOOH, a digital out-of-home advertising (DOOH) supply-side platform, to display the unique advertising content generated by Vpon’s AI visual content generator "InVnity" with VIOOH's digital outdoor advertising inventories. This partnership pioneers the future of outdoor advertising by using AI and big data solutions., May 2023: - Salesforce launched the next generation of Tableau for users to automate data analysis and generate actionable insights., March 2023: - SAP SE, a German multinational software company, entered a partnership with AI companies, including Databricks, Collibra NV, and DataRobot, Inc., to introduce the next generation of data management portfolio., November 2022: - Thai Oil and Retail Corporation PTT Oil and Retail Business Public Company implemented the Cloudera Data Platform to deliver insights and enhance customer engagement. The implementation offered a unified and personalized experience across 1,900 gas stations and 3,000 retail branches., November 2022: - IBM launched new software for enterprises to break down data and analytics silos that helped users make data-driven decisions. The software helps to streamline how users access and discover analytics and planning tools from multiple vendors in a single dashboard view., September 2022: - ActionIQ, a global leader in CX solutions, and Teradata, a leading software company, entered a strategic partnership and integrated AIQ’s new HybridCompute Technology with Teradata VantageCloud analytics and data platform.. Key drivers for this market are: Increasing Adoption of AI, ML, and Data Analytics to Boost Market Growth . Potential restraints include: Rising Concerns on Information Security and Privacy to Hinder Market Growth. Notable trends are: Rising Adoption of Big Data and Business Analytics among End-use Industries.

Analysis of ‘Number and percentage of people who successfully complete workforce development training, EOA.F.4’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/b6fa3a5c-c88b-4263-881a-a87f9e6482a2 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Presents data related to the number and percentage of people who successfully complete workforce development training with one of the partnering community benefit organizations (CBOs), also known as "Community Partners" in the Austin Metro Area Master Community Workforce Plan.

--- Original source retains full ownership of the source dataset ---

The social environment represents the external conditions under which people engage in social activity within their community. It includes aspects of social opportunity, leisure and recreation, education, access to health services, health status and participation in democratic processes. Fourteen indicators have been used to assess aspects of quality of the social environment.

This measure represents the percentage of identified as having cognitive impairments who were competitively employed after receiving services from Iowa Vocational Rehabilitation Services.

A worldwide survey carried out in 2024 showed that Boomers are the most concerned about the use of personal data when shopping online. 60 percent of them avoided sharing personal details because they did not trust data privacy with AI technologies.

Analysis of ‘Free Users Moderator Rates ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/5b03f6eac8d8c922a24afa4f on 14 January 2022.

--- Dataset description provided by original source is as follows ---

Track the number of users exempted from the payment of a moderator fee.

In the light of the new regulation of the National Register of Users (NNU), in application since December 2017, this indicator presents all the criteria for exemption from the payment of a moderating fee. Please note that a user may benefit from an exemption for fulfilling more than one criterion.

Thus, the total number of users exempted from the payment of a moderating fee in the SNS is presented in a specific field, representing the entire universe of users who benefit from the exemption from payment of Moderator Fee in the National Health Service, meeting at least one of the criteria provided for.

--- Original source retains full ownership of the source dataset ---

This dataset shows the percentage of U.S. adults who say they trust ChatGPT more than a human expert, based on a 2025 national AI trust survey.