Funding for artificial intelligence companies in the United States has increased exponentially in recent years, growing from a little under *** million U.S. dollars in 2011 to around **** billion in 2019. Overall worldwide funding in AI startups amounted to approximately **** billion U.S. dollars in the same year. Artificial intelligence refers to the creation of intelligent hardware or software able to replicate human behaviors such as learning and problem solving.

Machine learning applications most funded   

Companies focusing on machine learning applications are the most funded in the artificial intelligence (AI) market. Machine learning application companies raised ** billion U.S. dollars in cumulative funding as of September 2019. Other well-funded AI categories include machine learning platforms as well as computer vision applications and platforms. Intel Capital is the leading AI investor with a total of ** investments in AI companies as of April 2021. *** Startups, NEA and Y Combinator also rank high in terms of AI investment deals.

Gain insights into the future of the US AI market up to 2028. Explore trends, growth drivers, and projections shaping the landscape of artificial intelligence in the us.

Artificial intelligence (AI) holds tremendous promise to benefit nearly all aspects of society, including the economy, healthcare, security, the law, transportation, even technology itself. On February 11, 2019, the President signed Executive Order 13859, Maintaining American Leadership in Artificial Intelligence. This order launched the American AI Initiative, a concerted effort to promote and protect AI technology and innovation in the United States. The Initiative implements a whole-of-government strategy in collaboration and engagement with the private sector, academia, the public, and like-minded international partners. Among other actions, key directives in the Initiative call for Federal agencies to prioritize AI research and development (R&emp;D) investments, enhance access to high-quality cyberinfrastructure and data, ensure that the Nation leads in the development of technical standards for AI, and provide education and training opportunities to prepare the American workforce for the new era of AI. In support of the American AI Initiative, this National AI R&emp;D Strategic Plan: 2019 Update defines the priority areas for Federal investments in AI R&emp;D. This 2019 update builds upon the first National AI R&emp;D Strategic Plan released in 2016, accounting for new research, technical innovations, and other considerations that have emerged over the past three years. This update has been developed by leading AI researchers and research administrators from across the Federal Government, with input from the broader civil society, including from many of America’s leading academic research institutions, nonprofit organizations, and private sector technology companies. Feedback from these key stakeholders affirmed the continued relevance of each part of the 2016 Strategic Plan while also calling for greater attention to making AI trustworthy, to partnering with the private sector, and other imperatives.

The United States Artificial Intelligence Optimised Data Center Market Report is Segmented by Data Center Type (CSP Data Centers, Colocation Data Centers, Others (Enterprise and Edge)), by Component (Hardware, Software Technology, Services - (Managed Services, Professional Services, Etc. ). The Report Offers the Market Size and Forecasts for all the Above Segments in Terms of Value (USD).

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 market size in the artificial intelligence market in the United States was forecast to continuously increase between 2025 and 2031 by in total ***** billion U.S. dollars (+***** percent). After the ninth consecutive increasing year, the market size is estimated to reach ***** billion U.S. dollars and therefore a new peak in 2031. Find more key insights for the market size in countries and regions like the market size in the 'Machine Learning' segment of the artificial intelligence market in Nordics and the market size in the 'Machine Learning' segment of the artificial intelligence market in the world.The Statista Market Insights cover a broad range of additional markets.

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

United States Artificial Intelligence (AI) Market By Size, Share, Trends, Growth, Forecast 2018-2028, Segmented By Type, By Technology, By Deployment, By Industry, By Region, Competition Forecast and Opportunities

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Market Size
Forecast Market Size
CAGR
Fastest Growing Segment
Largest Market
Key Players

The U.S. AI Training Dataset Market size was valued at USD 590.4 million in 2023 and is projected to reach USD 1880.70 million by 2032, exhibiting a CAGR of 18.0 % during the forecasts period. The U. S. AI training dataset market deals with the generation, selection, and organization of datasets used in training artificial intelligence. These datasets contain the requisite information that the machine learning algorithms need to infer and learn from. Conducts include the advancement and improvement of AI solutions in different fields of business like transport, medical analysis, computing language, and money related measurements. The applications include training the models for activities such as image classification, predictive modeling, and natural language interface. Other emerging trends are the change in direction of more and better-quality, various and annotated data for the improvement of model efficiency, synthetic data generation for data shortage, and data confidentiality and ethical issues in dataset management. Furthermore, due to arising technologies in artificial intelligence and machine learning, there is a noticeable development in building and using the datasets. Recent developments include: In February 2024, Google struck a deal worth USD 60 million per year with Reddit that will give the former real-time access to the latter’s data and use Google AI to enhance Reddit’s search capabilities. , In February 2024, Microsoft announced around USD 2.1 billion investment in Mistral AI to expedite the growth and deployment of large language models. The U.S. giant is expected to underpin Mistral AI with Azure AI supercomputing infrastructure to provide top-notch scale and performance for AI training and inference workloads. .

The market size change in the artificial intelligence market in the United States was forecast to continuously decrease between 2025 and 2031 by in total *** percentage points. According to this forecast, in 2031, the market size change will have decreased for the seventh consecutive year to **** percent. Find more key insights for the market size change in countries and regions like the number of AI tools users in the 'AI Tool Users' segment of the artificial intelligence market in Nordics and the market size change in the 'Generative AI' segment of the artificial intelligence market in the world.The Statista Market Insights cover a broad range of additional markets.

The United States artificial intelligence market size reached approximately USD 33.96 Billion in 2024. The market is further projected to grow at a CAGR of 25.50% between 2025 and 2034, reaching a value of USD 329.16 Billion by 2034.

One out of two C-suite executives stated that Artificial Intelligence (AI) and Machine Learning (ML) were deployed in their healthcare organization, according to a survey conducted in the U.S. in 2019. In the surveyed upper market organizations, the implementation of AI and ML reached ** percent.

U.S. Artificial Intelligence (AI) Market size, market analysis, Market Revenue, trends, Regional Outlook, competition and growth opportunities till 2028

The size of the U.S. Machine Learning (ML) Market was valued at USD 4.74 USD billion in 2023 and is projected to reach USD 43.38 USD billion by 2032, with an expected CAGR of 37.2% during the forecast period. The U.S. Machine Learning (ML) Market refers to the application and development of machine learning technologies within the United States. Machine learning, a subset of artificial intelligence (AI), involves algorithms and models that allow systems to learn from data, identify patterns, and make decisions or predictions without being explicitly programmed. In the U.S., the ML market is growing rapidly, driven by advancements in computing power, large data sets, and the increasing demand for automation and AI across industries. This remarkable ascent is fueled by a confluence of factors, including the advent of hybrid and genetically modified seeds, proactive government initiatives aimed at enhancing agricultural productivity, an escalating consciousness regarding food security, and the rapid advancement of technologies that underpin precision agriculture. Hybrid seeds, offering a potent combination of desirable traits from multiple parent varieties, are poised to revolutionize crop production by improving yield, resilience, and nutritional content. innovation. Key drivers for this market are: Growing Adoption of Mobile Commerce to Augment the Demand for Virtual Fitting Room Tool . Potential restraints include: Lack of Coding Skills Likely to Limit Market Growth. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

The USA AI Data Management Market size is expected to reach $26.2 Billion by 2030, rising at a market growth of 20.7% CAGR during the forecast period. The AI data management market in the United States has experienced significant growth in recent years, driven by the increasing adoption of artific

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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 f

Unlock data-backed intelligence on the US Artificial Intelligence Market, size at USD 42 billion in 2023, featuring revenue trends and strategic insights.

To inform a community strategy for building and maintaining U.S. leadership in software engineering and AI engineering, the Carnegie Mellon University's Software Engineering Institute (CMU SEI) and the Software Productivity, Sustainability, and Quality (SPSQ) Interagency Working Group co-hosted the workshop at the National Science Foundation from June 20th to the 21st, 2023. The event gathered thought leaders from federal research funding agencies, research laboratories, mission agencies, and commercial organizations. Participants used the SEI’s Architecting the Future of Software Engineering: A National Agenda for Software Engineering Research and Development1 as a starting point because the areas of focus that the study identifies have been confirmed as increasingly critical, particularly due to the rapid advances of generative artificial intelligence (AI) in the two years since its release. Specifically, participants identified the following three research areas from the study as having direct relevance: AI-augmented Software Development, Assuring Continuously Evolving Software Systems, and Engineering AI-Enabled Software Systems...

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Aerospace Artificial Intelligence Market Size 2025-2029

The aerospace artificial intelligence (AI) market size is forecast to increase by USD 7.24 billion at a CAGR of 45.9% between 2024 and 2029.

Artificial Intelligence (AI) is revolutionizing the aerospace industry with its application in various domains, including software for flight simulation and virtual assistants for cockpit interaction. The rising trend of digital transformation in aviation is driving market growth, as AI enables automation in aircraft maintenance, threat detection systems, and additive manufacturing. The increasing use of drones equipped with sensors and data analytics capabilities is another significant trend, offering opportunities for real-time data collection and analysis. However, concerns surrounding data security and privacy are major challenges, necessitating strong cybersecurity measures. Machine learning algorithms, image recognition, and natural language processing are key technologies enabling AI in the aerospace sector, enhancing travel experiences and optimizing operational efficiency. The adoption of AI is set to continue, with the market expected to grow significantly in the coming years.

What will be the Size of the Aerospace Artificial Intelligence (AI) Market During the Forecast Period?

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The market encompasses the application of AI models, including machine learning, computer vision, and natural language processing, to enhance various aspects of the aerospace sector. AI technologies are increasingly being integrated into flight operations for predictive maintenance, optimization of fuel consumption, and improving pilot training through computer vision and voice recognition. In customer service, virtual assistants and voice recognition systems facilitate efficient communication between airlines and passengers.
Air traffic control benefits from AI's ability to analyze big data and identify data patterns for improved safety and efficiency. AI is also employed for observation tasks, such as analyzing time series data for anomaly detection and predictive maintenance in aircraft components. The aerospace AI market is poised for significant growth, as human intelligence is augmented by AI software to address complex challenges and optimize processes.

How is this Aerospace Artificial Intelligence (AI) Industry segmented and which is the largest segment?

The aerospace artificial intelligence (AI) industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Software
  Hardware
  Services


End-user

  Defense and military
  Commercial aviation
  Aircraft manufacturers
  Space exploration
  Airports


Application

  Machine learning
  Natural language processing
  Computer vision
  Context awareness computing


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK
    France
    Italy


  APAC

    China
    India
    Japan
    South Korea


  Middle East and Africa



  South America

By Component Insights

The software segment is estimated to witness significant growth during the forecast period.

Aerospace Artificial Intelligence (AI) software plays a crucial role in the development and operation of autonomous systems for UAVs, drones, and spacecraft. AI algorithms, including machine learning, computer vision, and neural networks, enable navigation, obstacle detection, and real-time decision-making. For instance, Airbus SE's Air Superiority Tactical Assistance Real-Time Execution System (ASTares) digitizes human-level experience to support tactical coordination in the Future Combat Air System (FCAS). In the aerospace sector, AI software optimizes flight control systems by analyzing data from sensors and adjusting flight parameters in real-time. This leads to improved fuel efficiency, reduced emissions, and enhanced safety. AI models are also integrated into customer service applications, such as virtual assistants and chatbots, to streamline airline industry processes and improve customer satisfaction.

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The software segment was valued at USD 141.10 million in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 35% 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.

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The aerospace industry is embracing Artificial Intelligence (AI) to enhance operational efficiency and automate processes in North America. Machine le

The artificial intelligence in healthcare market is valued at USD 17.2 billion in 2025 and is projected to reach USD 77.5 billion by 2035, expanding at a strong CAGR of 18.2%.

Attributes	Key Insights
Estimated Size, 2025	USD 17.2 billion
Projected Size, 2035	USD 77.5 billion
Value-based CAGR (2025 to 2035)	18.2%

Semi-Annual Industry Outlook

Particular	Value CAGR
H1	19.2% (2024 to 2034)
H2	18.8% (2024 to 2034)
H1	18.2% (2025 to 2035)
H2	17.7% (2025 to 2035)

Analyzing Artificial Intelligence in Healthcare Market by Top Investment Segments

Product Type	CAGR (2025 to 2035)
Hardware	19.1%

Technology Type	CAGR (2025 to 2035)
Machine Learning	19.3%

Application	CAGR (2025 to 2035)
Robot-Assisted Surgery	20.2%

End User	CAGR (2025 to 2035)
Healthcare Providers	18.9%

Country-wise Insights

Countries	Value CAGR (2025 to 2035)
USA	6.6%
Canada	8.8%
Germany	13.2%
France	11.0%
Italy	12.1%
UK	9.9%
Spain	9.3%
China	17.1%