https://heliontechnologies.com/wp-content/uploads/2024/04/AI.jpeg" alt="Ai"> The dataset, "The Rise of Artificial Intelligence," contains 8 entries and 16 columns, providing various insights on AI adoption, market trends, and job impact from 2018 to 2025.

Year: The year of data (2018–2025). AI Software Revenue: Annual revenue generated from AI software (e.g., "$10.1 billion"). Global AI Market Value: The global market value of AI (e.g., "$29.5 billion"). AI Adoption (%): Percentage of organizations adopting AI. Organizations Using AI: Percentage of organizations currently using AI. Organizations Planning to Implement AI: Percentage of organizations planning to adopt AI. Global Expectation for AI Adoption: Global expectations for AI adoption. Net Job Loss in the US: The estimated job loss in the U.S. due to AI. Organizations Believing AI Provides Competitive Edge: Percentage of organizations that think AI gives them an edge. Companies Prioritizing AI in Strategy: Percentage of companies prioritizing AI in their strategy. Marketers Believing AI Improves Email Revenue: Percentage of marketers who believe AI enhances email revenue. Americans Using Voice Assistants: The percentage of Americans using voice assistants (e.g., "Over 50%"). Medical Professionals Using AI for Diagnosis: Percentage of medical professionals using AI for diagnosis. Jobs at High Risk of Automation - Transportation & Storage: Percentage of jobs at high risk in this sector. Jobs at High Risk of Automation - Wholesale & Retail Trade: Percentage of jobs at high risk in this sector. Jobs at High Risk of Automation - Manufacturing: Percentage of jobs at high risk in manufacturing.

In 2024, the market size change in the 'Machine Learning' segment of the artificial intelligence market worldwide was modeled to stand at 44.66 percent. Between 2021 and 2024, the market size change dropped by 99.08 percentage points. The market size change is expected to drop by 15.3 percentage points between 2024 and 2031, showing a continuous downward movement throughout the period.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Machine Learning.

The market size in the 'Autonomous & Sensor Technology' segment of the artificial intelligence market worldwide was modeled to stand at 26.46 billion U.S. dollars in 2024. Between 2020 and 2024, the market size rose by 10.73 billion U.S. dollars, though the increase followed an uneven trajectory rather than a consistent upward trend. The market size will steadily rise by 42.29 billion U.S. dollars over the period from 2024 to 2031, reflecting a clear upward trend.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Autonomous & Sensor Technology.

Coordinate responsible and trustworthy artificial intelligence (AI) governance and capabilities. AITO is the connective tissue for all things AI at the Department of Energy.

Dataset Description This dataset contains the metadata for 10,000 research papers in the field of artificial intelligence (AI) that were published on arXiv.org. The dataset includes the following columns:

authors: The authors of the paper. categories: The categories of the paper. comment: Any additional comments about the paper. doi: The Digital Object Identifier (DOI) for the paper. entry_id: The arXiv entry ID for the paper. journal_ref: The journal reference for the paper, if applicable. pdf_url: The URL to the PDF of the paper. primary_category: The primary category of the paper. published: The date the paper was published. summary : abstract of the paper

Summary This dataset is a valuable resource for researchers and practitioners in the field of AI. It can be used to track the latest research trends, identify emerging areas of research, and find relevant papers. The dataset can also be used to train machine learning models that can be used to analyze AI research papers.

Data License The dataset is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This means that you are free to use, share, and adapt the dataset, as long as you give credit to the original authors.

How to Use the Dataset The dataset can be downloaded from the Kaggle website. Once you have downloaded the dataset, you can use it with any software that can read CSV files. You can also use the dataset with machine learning libraries such as scikit-learn and TensorFlow.

This dataset was created to measure the impact of artificial intelligence on society. The data was collected in Turkey for a Public Opinion Research course, using snowball and convenience sampling methods.

The dataset consists of 205 entries and 20 variables.

The last three variables were designed to assess the participants' knowledge level of artificial intelligence. The intention was to create a new variable by scoring correct answers as '1' and incorrect answers as '0', and then to analyze the relationship between this new score and the other variables.

The majority of the variables were conceived as Likert scale questions. The task of assigning numerical values has been left to the person who will analyze the data.

The dataset is composed entirely of real data.

***Here are the detailed descriptions for each column in the dataset.

• ID: A unique identifier for each survey respondent.

• What is your age range?: The age group of the participant.

• What is your gender?: The gender of the participant.

• What is your education level?: The highest education level completed by the participant.

• What is your employment status?: The current employment status of the participant.

• What is your occupation? (optional): The self-reported occupation of the participant. This field is optional.

• How often do you use technological devices?: The participant's self-reported frequency of daily technology use.

• How much knowledge do you have about artificial intelligence (AI) technologies?: The participant's self-assessed level of knowledge about AI technologies.

• Do you generally trust artificial intelligence (AI)?: The participant's general level of trust in artificial intelligence.

• Do you think artificial intelligence (AI) will be generally beneficial or harmful to humanity?: The participant's opinion on whether AI will ultimately be beneficial or harmful to humanity.

• Please rate how actively you use AI-powered products in your daily life on a scale from 1 to 5.: A numerical rating provided by the participant, from 1 (not active at all) to 5 (very active), on their usage of AI products.

• Would you like to use more AI products in the future?: The participant's stated desire to use more AI-powered products in the future.

• I think artificial intelligence (AI) could threaten individual freedoms.: The participant's level of agreement with the stat- ement that AI could pose a threat to individual freedoms.

• Could artificial intelligence (AI) completely eliminate some professions?: The participant's opinion on the possibility of AI completely replacing some job professions.

• Do you think your own job could be affected by artificial intelligence (AI)?: The participant's belief on whether their own job could be impacted by AI.

• Do you believe that artificial intelligence (AI) should be limited by ethical rules?: The participant's level of agreement with the statement that AI development and use should be constrained by ethical rules.

• Could artificial intelligence (AI) one day become conscious like humans?: The participant's opinion on the possibility of AI achieving human-like consciousness.

• Which of the following do you think is NOT an artificial intelligence (AI) application?: A multiple-choice question to test the participant's knowledge of what constitutes an AI application.

• Which of the following is a machine learning algorithm used in the field of artificial intelligence?: A multiple-choice question to test the participant's knowledge of common machine learning algorithms.

• The artificial intelligence application called 'ChatGPT' is an example of which type of AI system?: A multiple-choice question to test the participant's knowledge about the classification of specific AI systems like ChatGPT.***

OECD.ai uses data on AI publications from OpenAlex and Scopus to provide detailed insights into research activities across countries. OpenAlex is a comprehensive, open-source bibliographic database offering extensive information on academic publications. It is maintained by The OpenResearch Foundation and includes over 245 million research publications, including journals, conferences, and workshop papers. Scopus is a curated abstract and citation database offered commercially by Elsevier, with over 75 million indexed records.

The "Number of AI publications" indicator in Data360 is the "AI Publications by Country" indicator from OpenAlex. OECD.ai offers a similar indicator drawn from the Scopus database that gives somewhat different values (see https://oecd.ai/en/data?selectedArea=ai-research&selectedVisualization=16738); OpenAlex was chosen because it uses more permissive open source licensing than Scopus.

This collection includes only a subset of indicators from the source dataset.

The market size in the 'Natural Language Processing' segment of the artificial intelligence market worldwide was modeled to be 39.79 billion U.S. dollars in 2024. Between 2020 and 2024, the market size rose by 26.41 billion U.S. dollars, though the increase followed an uneven trajectory rather than a consistent upward trend. The market size will steadily rise by 161.7 billion U.S. dollars over the period from 2024 to 2031, reflecting a clear upward trend.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Natural Language Processing.

📊 About the Dataset

This dataset explores the influence of AI-generated content across various industries, including journalism, social media, entertainment, and marketing. It provides insights into public sentiment, engagement trends, economic impact, and regulatory responses over time.

With AI-generated content becoming increasingly prevalent, this dataset serves as a valuable resource for data analysts, business strategists, and machine learning researchers to study trends, detect biases, and predict future AI adoption patterns.

💡 This dataset is perfect for AI adoption analysis, industry forecasting, and ethical AI research!

The United States Artificial Intelligence Data Center Market Report is Segmented by Data Center Type (Cloud Service Providers, Colocation Data Centers, and More), Component (Hardware, Software Technology, and Services), Tier Standard (Tier III and Tier IV), and End-User Industry (IT and IT Services, Internet and Digital Media, and More). The Market Forecasts are Provided in Terms of Value (USD).

In 2024, the market size change in the 'Natural Language Processing' segment of the artificial intelligence market worldwide was modeled to amount to 32.43 percent. Between 2021 and 2024, the market size change dropped by 17.57 percentage points. The market size change is forecast to decline by 14.27 percentage points from 2024 to 2031, fluctuating as it trends downward.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Natural Language Processing.

Contains Artificial Intelligence Patent Landscape data classifying 13,244,037 granted patents and PGPubs published from 1976 through 2023 in eight AI component technologies using state-of-the art machine learning based models.

snapshot-tab-pane Artificial Intelligence (AI) Market In Education Sector Size 2025-2029The artificial intelligence (ai) market in education sector size is forecast to increase by USD 4.03 billion at a CAGR of 59.2% between 2024 and 2029.The Artificial Intelligence (AI) market in the education sector is experiencing significant growth due to the increasing demand for personalized learning experiences. Schools and universities are increasingly adopting AI technologies to create customized learning paths for students, enabling them to progress at their own pace and receive targeted instruction. Furthermore, the integration of AI-powered chatbots in educational institutions is streamlining administrative tasks, providing instant support to students, and enhancing overall campus engagement. However, the high cost associated with implementing AI solutions remains a significant challenge for many educational institutions, particularly those with limited budgets. Despite this hurdle, the long-term benefits of AI in education, such as improved student outcomes, increased operational efficiency, and enhanced learning experiences, make it a worthwhile investment for forward-thinking educational institutions.Companies seeking to capitalize on this market opportunity should focus on developing cost-effective AI solutions that cater to the unique needs of educational institutions while delivering measurable results. By addressing the cost challenge and providing tangible value, these companies can help educational institutions navigate the complex landscape of AI adoption and unlock the full potential of this transformative technology in education.What will be the Size of the Artificial Intelligence (AI) Market In Education Sector during the forecast period? Request Free SampleArtificial Intelligence (AI) is revolutionizing the education sector by enhancing teaching experiences and delivering personalized learning. AI technologies, including deep learning and machine learning, power adaptive learning platforms and intelligent tutoring systems. These systems create learner models to provide personalized recommendations and instructional activities based on individual students' needs. AI is transforming traditional educational models, enabling intelligent systems to handle administrative tasks and data analysis. The integration of AI in education is leading to the development of intelligent training software for skilled professionals.Furthermore, AI is improving knowledge delivery through data-driven insights and enhancing the learning experience with interactive and engaging pedagogical models. AI technologies are also being used to analyze training formats and optimize domain models for more effective instruction. Overall, AI is streamlining administrative tasks and providing personalized learning experiences for students and professionals alike.How is this Artificial Intelligence (AI) In Education Sector Industry segmented?The artificial intelligence (ai) in education sector industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. End-userHigher educationK-12Learning MethodLearner modelPedagogical modelDomain modelComponentSolutionsServicesApplicationLearning platform and virtual facilitatorsIntelligent tutoring system (ITS)Smart contentFraud and risk managementOthersTechnologyMachine LearningNatural Language ProcessingComputer VisionSpeech RecognitionGeographyNorth AmericaUSCanadaMexicoEuropeFranceGermanyItalySpainUKAPACChinaIndiaJapanSouth KoreaSouth AmericaBrazilMiddle East and AfricaUAEBy End-user InsightsThe higher education segment is estimated to witness significant growth during the forecast period.The global education sector is witnessing significant advancements with the integration of Artificial Intelligence (AI). AI technologies, including Machine Learning (ML), are revolutionizing various aspects of education, from K-12 schools to higher education and corporate training. Intelligent Tutoring Systems and Adaptive Learning Platforms are increasingly popular, offering Individualized Instruction and Personalized Learning Experiences based on each student's Learning Pathways and Skills Gap. AI-enabled solutions are enhancing Student Engagement by providing Interactive Learning Tools and Real-time communication, while AI platforms and startups are developing Smart Content and Tailored Content for Remote Learning environments. AI is also transforming administrative tasks, such as Assessment processes and Data Management, by providing Personalized Recommendations and Automated Grading.Universities and educational institutions are leveraging AI for Pedagogical model dev

The North America Artificial Intelligence Data Center Market Report is Segmented by Data Center Type (Cloud Service Providers, Colocation Data Centers, and More), Component (Hardware, Software Technology, and Services), Tier Standard (Tier III and Tier IV), End-User Industry (IT and IT Services, Internet and Digital Media, and More). The Market Forecasts are Provided in Terms of Value (USD).

The AI Data Services market is booming, projected to reach $100 billion by 2033 with a 20% CAGR. Discover key trends, growth drivers, and leading companies shaping this dynamic sector. Learn more about data annotation, AI data labeling, and market segmentation.

Explore key AI statistics, including adoption rates, market growth, industry applications, workforce impact, and innovation trends!

Dataset related to surveys on the use of artificial intelligence in higher education

Artificial Intelligence Market size was estimated at USD 308.49 billion in 2025 and is anticipated to grow at a CAGR of 31.3% from 2026 to 2034.

The Germany Artificial Intelligence Data Center Market Report is Segmented by Data Center Type (Cloud Service Providers, Colocation Data Centers, and More), Component (Hardware, Software Technology, and Services), Tier Standard (Tier 3 and Tier 4), and End-User Industry (IT and ITES, Internet and Digital Media, and More). The Market Forecasts are Provided in Terms of Value (USD).

Artificial Intelligence Market Outlook 2025-2034

The global artificial intelligence market was valued at $214.6 billion in 2025 and is projected to reach $3,680.5 billion by 2034, expanding at an exceptional compound annual growth rate (CAGR) of 35.7% during the forecast period from 2026 to 2034, making it one of the fastest-growing technology markets globally. Artificial intelligence has transitioned from a specialized academic discipline into a foundational pillar of modern enterprise strategy, government policy, and consumer technology, encompassing a broad spectrum of capabilities including machine learning, natural language processing, computer vision, generative AI, and autonomous decision-making systems. The extraordinary pace of investment across all verticals, from healthcare diagnostics and financial risk modeling to autonomous vehicles and precision agriculture, underscores the technology's pervasive relevance. As of 2026, more than 77% of devices worldwide leverage AI-powered features in some form, and enterprise AI adoption has surpassed 60% across Fortune 500 companies, reflecting a seismic shift in how organizations approach productivity, customer engagement, and competitive differentiation.

The primary growth driver accelerating the artificial intelligence market through the forecast period is the mass commercialization and rapid maturation of generative AI platforms. Following the explosive adoption of large language models (LLMs) such as GPT-4 and its successors, enterprises across sectors have initiated formal AI integration roadmaps with dedicated budget allocations. Spending on AI infrastructure, including specialized graphics processing units (GPUs), tensor processing units (TPUs), and AI-optimized cloud instances, has surged dramatically since 2023, with global AI infrastructure investment exceeding $120 billion in 2025 alone. Governments in the United States, China, the European Union, and India have committed billions in sovereign AI investment programs, creating regulatory and funding tailwinds that further stimulate market expansion. Simultaneously, the democratization of AI tools through low-code and no-code platforms has lowered the barrier to entry for small and medium enterprises (SMEs), broadening the addressable customer base significantly. The convergence of AI with edge computing, 5G networks, and Internet of Things (IoT) ecosystems is enabling real-time inference at the device level, unlocking new use cases in predictive maintenance, smart cities, and personalized retail experiences. Furthermore, the proliferation of AI-as-a-Service (AIaaS) offerings from hyperscalers such as Microsoft Azure, Amazon Web Services (AWS), and Google Cloud has made enterprise-grade AI accessible without substantial upfront capital expenditure, democratizing access and accelerating adoption velocity across mid-market enterprises and emerging economies alike.