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.

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

This dataset details how ICE recognizes the transformative potential of artificial intelligence (AI) to the mission space. the agency continued to establish the foundation for the safe, secure and ethical development and use of AI technology.

Artificial Intelligence (AI) Training Dataset Market Outlook

According to our latest research, the global Artificial Intelligence (AI) Training Dataset market size reached USD 3.80 billion in 2025, reflecting robust industry momentum. The market is expanding at a notable CAGR of 21.2% and is forecasted to attain USD 22.6 billion by 2034. This impressive growth is primarily attributed to the surging demand for high-quality, annotated datasets to fuel machine learning and deep learning models across diverse industry verticals. The proliferation of AI-driven applications, including generative AI and large language models, coupled with rapid advancements in data labeling technologies, is further accelerating the adoption and expansion of the AI training dataset market globally.

One of the most significant growth factors propelling the AI training dataset market is the exponential rise in data-driven AI applications across industries such as healthcare, automotive, retail, and finance. As organizations increasingly rely on AI-powered solutions for automation, predictive analytics, and personalized customer experiences, the need for large, diverse, and accurately labeled datasets has become critical. Enhanced data annotation techniques, including manual, semi-automated, and fully automated methods, are enabling organizations to generate high-quality datasets at scale, which is essential for training sophisticated AI models. The integration of AI in edge devices, smart sensors, and IoT platforms is further amplifying the demand for specialized datasets tailored for unique use cases, thereby fueling market growth. Organizations seeking compliant access to training content are also paying close attention to the evolving landscape of dataset licensing for AI training, as intellectual property considerations become a central concern for enterprise AI programs.

Another key driver is the ongoing innovation in machine learning and deep learning algorithms, which require vast and varied training data to achieve optimal performance. The increasing complexity of AI models, especially in areas such as computer vision, natural language processing, and autonomous systems, necessitates the availability of comprehensive datasets that accurately represent real-world scenarios. Companies are investing heavily in data collection, annotation, and curation services to ensure their AI solutions can generalize effectively and deliver reliable outcomes. Additionally, the rise of synthetic test data for AI and data augmentation techniques is helping address challenges related to data scarcity, privacy, and bias, further supporting the expansion of the AI training dataset market through 2034.

The market is also benefiting from the growing emphasis on ethical AI and regulatory compliance, particularly in data-sensitive sectors like healthcare, finance, and government. Organizations are prioritizing the use of high-quality, unbiased, and diverse datasets to mitigate algorithmic bias and ensure transparency in AI decision-making processes. This focus on responsible AI development is driving demand for curated datasets that adhere to strict quality and privacy standards. Moreover, the emergence of data marketplaces and collaborative data-sharing initiatives is making it easier for organizations to access and exchange valuable training data, fostering innovation and accelerating AI adoption across multiple domains.

As the AI training dataset market continues to evolve, the role of Perception Dataset Management Platforms is becoming increasingly crucial. These platforms are designed to handle the complexities of managing large-scale datasets, ensuring that data is not only collected and stored efficiently but also annotated and curated to meet the specific needs of AI models. By providing tools for data organization, quality control, and colla

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.

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.

🚀 Global AI Tools Dataset (2020–2026) | 1500+ AI Products

A comprehensive artificial intelligence dataset containing 1500+ AI tools across multiple categories, including Large Language Models (LLM), Image Generation AI, Video AI, Coding Assistants, Voice AI and AI Agents.

This dataset is designed for machine learning, data science, NLP research, recommendation systems and AI market analysis.

It provides structured information about AI tools, companies, pricing models, and adoption metrics to support AI ecosystem research and machine learning projects.

📊 Dataset Highlights

• 1500+ AI tools
• Multiple AI categories (LLM, Generative AI, Coding AI, Voice AI)
• Company metadata and valuation
• AI funding information
• Pricing model classification
• AI market ecosystem insights

This dataset is suitable for AI analytics, machine learning datasets, recommendation system development, and AI industry research.

📂 Dataset Files

1️⃣ ai_tools.csv

Main dataset containing information about AI tools and products.

Features include:

• Tool Name
• AI Category
• Company
• Launch Year
• Estimated User Base
• Pricing Model
• Open Source Status

This file can be used for machine learning classification, clustering, and recommendation systems.

2️⃣ ai_tool_categories.csv

Description of major AI technology categories, including:

• Large Language Models (LLM)
• Image Generation AI
• Video Generation AI
• Coding AI Assistants
• Voice AI Systems
• Autonomous AI Agents
• AI Productivity Tools

3️⃣ ai_company_metadata.csv

Metadata about companies developing AI tools, including:

• Company name
• Country
• Founding year
• Estimated valuation

Useful for AI startup ecosystem analysis and AI industry research.

4️⃣ ai_tool_funding.csv

Dataset containing AI startup funding rounds including:

• Funding round
• Investment amount
• Funding year

This can support AI startup funding analysis and venture capital trend analysis.

📑 Column Descriptions

🧠 Potential Machine Learning Use Cases

This dataset can be used for:

Machine Learning Projects

Classification of AI tools by category.

Recommendation Systems

Recommend AI tools based on category or company.

Natural Language Processing (NLP)

AI tool description analysis and categorisation.

Data Visualization

Analyse the **growth of AI tools from 2020 to 2026.

AI Market Analysis

Study trends in generative AI, LLMs and AI startups.

📈 AI Industry Insights

The global AI ecosystem has grown rapidly with the emergence of the following:

• Large Language Models (LLMs)
• Generative AI platforms
• AI coding assistants
• AI automation agents

Datasets like this help researchers and data scientists understand AI adoption, market growth and technology evolution.

🔄 Expected Update Frequency

Quarterly updates will include:

• New AI tools
• Updated company information
• AI funding updates

📜 License

CC0: Public Domain

🙌 Acknowledgement

This dataset was compiled using publicly available information about AI tools and companies. Some values were synthetically generated for research and educational purposes.

🔍 Keywords

Artificial Intelligence Dataset
AI Tools Dataset
Machine Learning Dataset
Generative AI Dataset
LLM Dataset
Natural Language Processing Dataset
Data Science Dataset
AI Market Analysis Dataset
AI Startup Dataset
AI Industry Dataset

This dataset can be used for machine learning, data science, artificial intelligence research, recommendation systems, and AI market analysis.

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).

There are the underlying data for our report "Artificial Intelligence: How knowledge is created, transferred, and used", published 2018. Data can be used to construct the graphs used in the report.

Artificial intelligence is one of the technological areas with the greatest economic projection in the short and medium term. So much so that its market value could exceed the 300 billion U.S. dollars mark by 2027. Alongside revenues, the number of users is also increasing, which could surpass the 500 million mark by 2028.

snapshot-tab-pane Artificial Intelligence (AI) In Education Sector Market Size 2026-2030The artificial intelligence (ai) in education sector market size is valued to increase by USD 3.37 billion, at a CAGR of 45% from 2025 to 2030. Escalating demand for personalized and adaptive learning experiences will drive the artificial intelligence (ai) in education sector market.Major Market Trends & InsightsNorth America dominated the market and accounted for a 41.7% growth during the forecast period.By End-user - Higher education segment was valued at USD 285.7 million in 2024By Learning Method - Learner model segment accounted for the largest market revenue share in 2024Market Size & ForecastMarket Opportunities: USD 3.86 billionMarket Future Opportunities: USD 3.37 billionCAGR from 2025 to 2030 : 45%Market SummaryThe artificial intelligence in education sector is experiencing profound expansion as institutions pivot toward intelligent infrastructure to enhance scalability and engagement. A key driver is the move from standardized instruction to hyper-personalized education, where machine learning algorithms and natural language processing create adaptive learning environments. This transition is supported by the broad adoption of cloud-based platforms, which facilitate data-driven instruction.A significant trend is the evolution from basic generative models to sophisticated agentic AI workflows that automate administrative tasks like grading and scheduling, allowing educators to focus on mentorship. For instance, a university system can deploy predictive analytics to analyze student performance metrics, identifying at-risk individuals and enabling timely interventions to reduce dropout rates.However, challenges such as data sovereignty and the need for robust AI ethics frameworks persist, requiring careful management to ensure equitable and secure implementation across diverse educational settings.What will be the Size of the Artificial Intelligence (AI) In Education Sector Market during the forecast period? Get Key Insights on Market Forecast (PDF) Get Free SampleHow is the Artificial Intelligence (AI) In Education Sector Market 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 2026-2030, as well as historical data from 2020-2024 for the following segments.End-userHigher educationK-12Learning methodLearner modelPedagogical modelDomain modelComponentSolutionsServicesApplicationLearning platform and virtual facilitatorsIntelligent tutoring system (ITS)Smart contentFraud and risk managementOthersGeographyNorth AmericaUSCanadaMexicoEuropeGermanyUKFranceAPACChinaIndiaJapanSouth AmericaBrazilArgentinaMiddle East and AfricaSaudi ArabiaUAESouth AfricaRest of World (ROW)By End-user InsightsThe higher education segment is estimated to witness significant growth during the forecast period.The higher education segment is at the forefront of the artificial intelligence in education sector, driven by strategic integration across all operational facets.A notable shift from pilot programs to systemic adoption is evident, with institution-wide implementation of AI surging to 66%. Universities are leveraging generative models and AI-powered course recommendations to develop specialized teaching materials and intelligent tutoring systems.The use of digital twin learners and predictive analytics has become central to institutional strategy, enabling proactive student interventions.This move is supported by advanced curriculum architecture and sophisticated pedagogical models that cater to a diverse student body, focusing on AI-driven skill mapping to prepare graduates for a landscape dominated by automated systems and machine learning algorithms, which is a part of digital transformation in education. Get Free SampleThe Higher education segment was valued at USD 285.7 million in 2024 and showed a gradual increase during the forecast period. Get Free SampleRegional AnalysisNorth America is estimated to contribute 41.7% to the growth of the global market during the forecast period.Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. See How Artificial Intelligence (AI) In Education Sector Market Demand is Rising in North America Get Free SampleThe geographic landscape of the artificial intelligence in education sector is led by North America, where 86% of educational organizations have adopted generative artificial intelligence for administrative and instructional enhancement.This region's dominance is supported by a mature technological infrastructure and substantial private sector investment in AI-e

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.***

In 2024, the market size change in the 'Autonomous & Sensor Technology' segment of the artificial intelligence market worldwide was modeled to amount to 30.92 percent. Between 2021 and 2024, the market size change dropped by 69.03 percentage points. The market size change is expected to drop by 25.49 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 Autonomous & Sensor Technology.

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

Introduction

Artificial Intelligence (AI) is a transformative technology that aims to mimic human intelligence and perform tasks that typically require human cognitive abilities. It encompasses various subfields, such as machine learning, natural language processing, computer vision, and robotics. AI systems are designed to analyze vast amounts of data, learn from patterns, make predictions, and automate complex processes. The potential applications of AI are vast, ranging from healthcare and finance to transportation and manufacturing.

The global Artificial Intelligence (AI) market is set to reach approximately USD 2,745 billion by 2032, marking a substantial increase from USD 177 billion in 2023, with a steady CAGR of 36.8%.

The AI market has been experiencing rapid growth, driven by advancements in technology, increased data availability, and the need for automation and intelligent decision-making. Organizations across industries are recognizing the value of AI in improving efficiency, enhancing customer experiences, and gaining a competitive edge. The AI market encompasses a wide range of solutions, including AI software platforms, AI-enabled hardware, and AI services.

By 2034, the Artificial Intelligence (AI) Market is expected to reach a valuation of USD 10,173.0 bn, expanding at a healthy CAGR of 38.5%.

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

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 Thailand 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).