According to a global survey among marketing professionals in January 2025, approximately ** percent reported using artificial intelligence (AI) extensively in their data-driven marketing efforts. Around ** percent said they integrated AI in select areas, whereas ** percent were exploring AI, but have not implemented the technology. Some ** percent reported not having plans to use AI.

This dataset is a list of Department of Transportation (DOT) Artificial Intelligence (AI) use cases. Artificial intelligence (AI) promises to drive the growth of the United States economy and improve the quality of life of all Americans. Pursuant to Section 5 of Executive Order (EO) 13960, "Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government," Federal agencies are required to inventory their AI use cases and share their inventories with other government agencies and the public. In accordance with the requirements of EO 13960, this spreadsheet provides the mechanism for federal agencies to create their inaugural AI use case inventories. https://www.federalregister.gov/documents/2020/12/08/2020-27065/promoting-the-use-of-trustworthy-artificial-intelligence-in-the-federal-government

As of 2023, the majority of users engaging with generative artificial intelligence (Gen AI), or ** percent, was composed of young adults in between 18 and 24 years old. Most of the users are also male and with a college degree or higher.

Data for Artificial Intelligence: Data-Centric AI for Transportation: Work Zone Use Case proposes a data integration pipeline that enhances the utilization of work zone and traffic data from diversified platforms and introduces a novel deep learning model to predict the traffic speed and traffic collision likelihood during planned work zone events. This dataset is the processed integrated traffic data with work zone and incident information. Attached below are the number of lanes data and impacted work zone .pkl file.

Most organizations have not adapted AI to a great degree, with only a select number of employees within an organization using it in 2023. This is in all likelihood because the technology is still maturing and a select amount of employees might be running pilot programs or test programs for AI usage within companies. What is notable is more than a ******* of companies did not use any AI within their enterprise in 2023.

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Artificial Intelligence (AI) Market In Education Sector Size 2025-2029

The 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 AfricaUAE

By End-user Insights

The 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 development and Virtual Classrooms, offering Educational Experiences and Virtual support. AI is also being used for Academic mapping an

Imagine a world where your doctor’s diagnosis is assisted by a machine learning model, your home anticipates your needs before you speak, and your company's biggest asset is no longer its workforce, but its data. That’s not a glimpse of a distant future; it's the reality we’re living in. As...

Use of artificial intelligence (AI) by businesses and organizations in producing goods or delivering services over the last 12 months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.

Data from the Opinion and Lifestyle Survey (OPN) on the use of Artificial Intelligence (AI) and how people feel about its uptake in today’s society.

Executive Summary: Artificial intelligence (AI) is a transformative technology that holds promise for tremendous societal and economic benefit. AI has the potential to revolutionize how we live, work, learn, discover, and communicate. AI research can further our national priorities, including increased economic prosperity, improved educational opportunities and quality of life, and enhanced national and homeland security. Because of these potential benefits, the U.S. government has invested in AI research for many years. Yet, as with any significant technology in which the Federal government has interest, there are not only tremendous opportunities but also a number of considerations that must be taken into account in guiding the overall direction of Federally-funded R&D in AI. On May 3, 2016,the Administration announced the formation of a new NSTC Subcommittee on Machine Learning and Artificial intelligence, to help coordinate Federal activity in AI.1 This Subcommittee, on June 15, 2016, directed the Subcommittee on Networking and Information Technology Research and Development (NITRD) to create a National Artificial Intelligence Research and Development Strategic Plan. A NITRD Task Force on Artificial Intelligence was then formed to define the Federal strategic priorities for AI R&D, with particular attention on areas that industry is unlikely to address. This National Artificial Intelligence R&D Strategic Plan establishes a set of objectives for Federallyfunded AI research, both research occurring within the government as well as Federally-funded research occurring outside of government, such as in academia. The ultimate goal of this research is to produce new AI knowledge and technologies that provide a range of positive benefits to society, while minimizing the negative impacts. To achieve this goal, this AI R&D Strategic Plan identifies the following priorities for Federally-funded AI research: Strategy 1: Make long-term investments in AI research. Prioritize investments in the next generation of AI that will drive discovery and insight and enable the United States to remain a world leader in AI. Strategy 2: Develop effective methods for human-AI collaboration. Rather than replace humans, most AI systems will collaborate with humans to achieve optimal performance. Research is needed to create effective interactions between humans and AI systems. Strategy 3: Understand and address the ethical, legal, and societal implications of AI. We expect AI technologies to behave according to the formal and informal norms to which we hold our fellow humans. Research is needed to understand the ethical, legal, and social implications of AI, and to develop methods for designing AI systems that align with ethical, legal, and societal goals. Strategy 4: Ensure the safety and security of AI systems. Before AI systems are in widespread use, assurance is needed that the systems will operate safely and securely, in a controlled, well-defined, and well-understood manner. Further progress in research is needed to address this challenge of creating AI systems that are reliable, dependable, and trustworthy. Strategy 5: Develop shared public datasets and environments for AI training and testing. The depth, quality, and accuracy of training datasets and resources significantly affect AI performance. Researchers need to develop high quality datasets and environments and enable responsible access to high-quality datasets as well as to testing and training resources. Strategy 6: Measure and evaluate AI technologies through standards and benchmarks. . Essential to advancements in AI are standards, benchmarks, testbeds, and community engagement that guide and evaluate progress in AI. Additional research is needed to develop a broad spectrum of evaluative techniques. Strategy 7: Better understand the national AI R&D workforce needs. Advances in AI will require a strong community of AI researchers. An improved understanding of current and future R&D workforce demands in AI is needed to help ensure that sufficient AI experts are available to address the strategic R&D areas outlined in this plan. The AI R&D Strategic Plan closes with two recommendations: Recommendation 1: Develop an AI R&D implementation framework to identify S&T opportunities and support effective coordination of AI R&D investments, consistent with Strategies 1-6 of this plan. Recommendation 2: Study the national landscape for creating and sustaining a healthy AI R&D workforce, consistent with Strategy 7 of this plan.

The statistic shows the cumulative revenues from the ten leading artificial intelligence (AI) use cases worldwide, between 2016 and 2025. Over the ten years between 2016 and 2025, AI software for vehicular object detection, identification, and avoidance is expected to generate * billion U.S. dollars.

In a 2025 survey, around ** percent of respondants claimed to use AI tools intentionally on a daily basis either for personal use, work or study purposes. Similarly, ** percent reported to never use AI tools

According to a 2025 survey of marketing professionals in the United States and Canada, ** percent of respondents said their organization was using artificial intelligence (AI) for generating insights and recommendations, and personalizing content at scale, respectively. Another ** percent were using AI for optimizing campaign journeys in their marketing processes. In comparison, ** percent were not actively using AI in marketing.

In 2023, information and communication was the industry with the most usage of artificial intelligence (AI) for machine learning for data analysis in Norway with a share of 22 percent. All other industries only had shares of 5 percent or less.

As of 2023, about ** percent of surveyed employees from companies in the United States of America and United Kingdom claim to use artificial intelligence (AI) in the logic-based task of data analysis. Approximately ** percent claim to use it for routine administrative tasks. These numbers are forecasted to grow, as the share of employees that wish to use the technology for both tasks is much higher, lying around ** percent.

The number of AI tools users in the 'AI Tool Users' segment of the artificial intelligence market worldwide was modeled to stand at ************** in 2024. Following a continuous upward trend, the number of AI tools users has risen by ************** since 2020. Between 2024 and 2031, the number of AI tools users will rise by **************, continuing its consistent upward trajectory.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Artificial Intelligence.

It facilitates monitoring of the EU’s digital targets for 2030 set by the Digital Compass for the EU's Digital Decade, evolving around four cardinal points: skills, digital transformation of businesses, secure and sustainable digital infrastructures, and digitalization of public services.

The aim of the European ICT usage survey is to collect and disseminate harmonised and comparable information on the use of Information and Communication Technologies and e-commerce in enterprises at European level.

Coverage:

The characteristics to be provided are drawn from the following list of subjects:

• ICT systems and their usage in enterprises,
• use of the internet and other electronic networks by enterprises,
• e-commerce,
• e-business processes and organisational aspects,
• ICT competence in the enterprise and the need for ICT skills,
• barriers to the use of ICT, the internet and other electronic networks, e-commerce and e-business processes,
• ICT security and incidents,
• access to and use of the internet and other network technologies for connecting objects and devices (Internet of Things),
• access to and use of technologies providing the ability to connect to the internet or other networks from anywhere at any time (ubiquitous connectivity),
• use of Artificial Intelligence,
• use of Cloud computing,
• data analytics,
• use of 3D printing,
• use of robotics,
• use of social media,
• internet advertising
• ICT and the environment.

Breakdowns:

• by size class,
• by NACE Rev. 2 categories,
• by NUTS 2 regions (until 2010 and on optional basis since 2023)

In 2023, the youngest technology professionals in the age range of 18-25 were the most receptive to new artifical intelligence (AI) tools, with a weekly adoption rate of about ** percent. The adoption rate goes down as the age of the IT professionals increases.

Global Artificial Intelligence (AI) in Consumer market size was USD 150 billion in 2023 and is grow to USD 1,350 billion by 2032 with a CAGR of 27.65%.

Technology professionals in Asia had the highest weekly adoption of artificial intelligence (AI) tools with a rate of **** percent in 2023. In contrast, the United States had the lowest adoption rate of AI tools with only about ** percent.