In 2020, the global AI software market is expected to grow approximately ** percent year-on-year, reaching a forecast size of ***** billion U.S. dollars. AI is a term used to describe a variety of technologies referring to the creation of intelligent software or hardware able to learn and solve problems. These include machine learning, computer vision, and natural language processing (NLP), among others. AI is expected to have wide adoption in and implications for every industry vertical and is likely to be one of the next great technological shifts, like the advent of the computer age or the smartphone revolution.  AI Revolution: an increase or decrease in human labor?    Despite its potential to optimize the way many industries operate, AI is feared to replace human labor in some. The automotive and assembly, and telecom industries worldwide are predicted to undergo the biggest workforce cuts in the next 3 years due to the adoption of AI technologies. However, infrastructure, professional services and high-tech industries are predicted to increase their workforce sizes with the adoption of AI technologies during the same time period. This highlights the somewhat polarizing effects of AI to human jobs. In some industries, the introduction of AI greatly expedites processes and minimizes human error, which leads to the replacement of human labor. While in others, AI creates new hybrid roles where humans enable machines and AI augments human capabilities.  AI’s impacts on global economic    Despite changes in the global workforce, AI is predicted to contribute to global economic growth. A 2018 global survey estimates that AI will contribute to approximately **** percent of China’s GDP in 2030, **** percent of the GDP in North America, and **** percent of UAE’s GDP. Some of these increases in GDP stem from improvements in productivity and product enhancements due to the adoption of AI technologies. For example, AI in the technology, media and telecommunications industry is forecast to increase global GDP in 2030 by **** percent – *** percent from gains associated with productivity, and * percent from gains associated with product enhancements.

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 artificial intelligence (AI) chip market is experiencing rapid growth, with projections indicating it will grow by a further **** percent in 2025, reaching **** billion U.S. dollars. In 2026, the AI chip market is expected to be worth ***** billion U.S. dollars.

This document reports current trends and examples of Federal R&D investments, program information, and activities in artificial intelligence that directly address the R&D challenges and opportunities noted in The National Artificial Intelligence Research and Development Strategic Plan: 2019 Update, available at https://www.nitrd.gov/pubs/National-AI-RD-Strategy-2019.pdf

The statistic shows cumulative artificial intelligence (AI) funding by category worldwide through **************. Machine learning application companies raised about ** billion U.S. dollars in funding through **************.

On June 4-6, 2019, the NSTC NITRD Program, in collaboration with the NSTC's MLAI Subcommittee, held a workshop to assess the research challenges and opportunities at the intersection of cybersecurity and artificial intelligence. The workshop brought together senior members of the government, academic, and industrial communities to discuss the current state of the art and future research needs, and to identify key research gaps. This report is a summary of those discussions, framed around research questions and possible topics for future research directions. More information is available at https://www.nitrd.gov/nitrdgroups/index.php?title=AI-CYBER-2019.

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 raw Maryland 2019 Average Annual Daily Traffic data

The statistic shows the leading use cases of cognitive and artificial intelligence (AI) systems, based on their market share in 2019. In 2019, automated customer service agents are expected to account for **** percent of the use cases of AI and cognitive systems.

Snapshot img { margin: 10px !important; } France Artificial Intelligence In Manufacturing And Supply Chain Market Size 2025-2029

The France artificial intelligence in manufacturing and supply chain market size is forecast to increase by USD 1.6 billion at a CAGR of 19.0% between 2024 and 2029.

The artificial intelligence market in manufacturing and supply chain in France is progressing, supported by a national imperative to enhance industrial sovereignty and competitive resilience. This focus directs investment toward sophisticated technologies that reinforce the domestic industrial base and lessen reliance on external manufacturing. Such a policy creates an environment where ai in industrial design functions as a strategic requirement rather than just an operational update. Concurrently, the proliferation of artificial intelligence for industrial process design and optimization represents a significant change, moving from analysis and prediction to autonomous creation and synthesis. This ability expedites innovation cycles in complex, design-focused sectors by enabling the quick generation and assessment of optimized components, workflows, and entire supply chain networks. This signifies a new phase of AI-influenced industrial innovation.The market's forward movement is conditioned by substantial operational impediments. A primary concern is the profound difficulty associated with data integration, quality, and governance within a heterogeneous industrial landscape. The efficacy of even the most advanced AI models, including those utilized for predictive ai in supply chain and generative manufacturing applications, is entirely dependent upon the availability of clean, consolidated, and context-rich information. The existing landscape of disparate data silos, incompatible legacy systems, and inconsistent data standards forms a formidable barrier to widespread adoption and scaling of these technologies. This situation requires a fundamental re-evaluation of how data is managed as a core corporate asset, moving toward a more centralized and standardized approach to enable genuine AI-based transformation within the artificial intelligence market in the industrial sector.

What will be the size of the France Artificial Intelligence In Manufacturing And Supply Chain Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019 - 2023 and forecasts 2025-2029 - in the full report.
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How is this market segmented?

The market 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-userAutomotiveAerospaceConstructionChemicalOthersTypeSoftwareHardwareServicesDeploymentOn-premisesCloud-basedHybridGeographyEuropeFrance

By End-user Insights

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

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The Automotive segment was valued at USD 272.50 million in 2019 and showed a gradual increase during the forecast period.

Market Dynamics

Our researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

The Global Artificial Intelligence Market In Manufacturing And Supply Chain in France Market is experiencing significant expansion, driven by national strategies like France 2030 and a strong industrial heritage. Companies are aggressively integrating Artificial Intelligence (AI) to enhance operational efficiency, with applications ranging from predictive maintenance on factory floors to AI-driven quality control systems that reduce defects. This technological adoption is prevalent across both large corporations and innovative SMEs, fostering a competitive landscape. The convergence of AI with IoT and big data analytics is enabling smarter factories, optimizing resource allocation, and boosting productivity, thereby solidifying France's position as a key player in the European Industry 4.0 movement. This strategic focus is crucial for maintaining global competitiveness and fostering industrial sovereignty.In the realm of supply chain management, AI is a transformative force, enabling more resilient and agile logistics networks throughout France. Machine learning algorithms are being employed for sophisticated demand forecasting, which minimizes inventory costs and prevents stockouts. For Original Equipment Manufacturers (OEM), AI offers enhanced visibility and traceability across complex, multi-tiered supplier networks, mitigating risks associated with global disruptions. Furthermore, AI-powered platforms are optimizing transportation routes to reduce fuel consumption and delivery

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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

Context

The AI Index is a starting point for informed conversations about the state of artificial intelligence (AI). The report aggregates a diverse set of metrics, and makes the underlying data easily accessible to the general public.

Acknowledgements

This data is from Stanford University's Human Centered AI Center and is posted here: https://hai.stanford.edu/ai-index/2019

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Artificial Intelligence (AI) Market Size 2025-2029

The artificial intelligence (AI) market size is valued to increase by USD 369.1 billion, at a CAGR of 34.7% from 2024 to 2029. Prevention of fraud and malicious attacks will drive the artificial intelligence (ai) market.

Major Market Trends & Insights

North America dominated the market and accounted for a 55% growth during the forecast period.
By Component - Software segment was valued at USD 27.50 billion in 2023
By End-user - Retail segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 975.62 billion
Market Future Opportunities: USD 369.10 billion
CAGR from 2024 to 2029 : 34.7%

Market Summary

The market is a dynamic and ever-evolving landscape, characterized by continuous advancements in core technologies and applications. Key technologies driving this growth include machine learning, natural language processing, and robotics, while applications span industries such as healthcare, finance, and manufacturing. The market is also witnessing a significant shift towards cloud-based AI services, with major players like Microsoft, Google, and Amazon leading the charge. However, challenges persist, including the need to prevent fraud and malicious attacks, the shortage of AI experts, and increasing regulatory scrutiny.
According to recent reports, the global AI market is expected to reach a 25% adoption rate by 2025, underscoring its transformative potential across various sectors. This data-driven narrative reflects the ongoing unfolding of market activities and evolving patterns, providing valuable insights for businesses looking to leverage AI for competitive advantage.

What will be the Size of the Artificial Intelligence (AI) Market during the forecast period?

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How is the Artificial Intelligence (AI) Market Segmented ?

The 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

  Retail
  Banking
  Manufacturing
  Healthcare
  Others


Technology

  Deep learning
  Machine learning
  NLP
  Gen AI


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Component Insights

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

Artificial Intelligence (AI) is revolutionizing the software development landscape as developers leverage AI tools to create intelligent applications. These tools, which include algorithms, libraries, frameworks, and developer kits, enable the integration of machine learning, speech recognition, and other advanced AI features. According to recent studies, the usage of AI in software development is becoming increasingly common, with 30% of developers reporting current implementation and 45% planning to adopt AI tools in the near future. Moreover, the future growth prospects of the AI market are promising, with 35% of businesses anticipating significant increases in AI adoption within the next three years.

AI software is poised to transform various sectors by automating manual tasks, enhancing employee experience, and providing data-driven insights. Fuzzy logic systems and genetic algorithms are integral components of AI, enabling process optimization and data mining techniques. Expert systems, speech recognition technology, sentiment analysis tools, and decision support systems facilitate improved customer relationship management. Deep learning models and risk assessment models contribute to pattern recognition systems, while neural network architecture and natural language generation advance knowledge representation. Anomaly detection systems, machine learning algorithms, and robotic process automation are essential for cognitive computing and AI-powered automation. Fraud detection algorithms, computer vision systems, and reinforcement learning are crucial for industries like finance, healthcare, and manufacturing.

Furthermore, reasoning mechanisms, natural language processing, predictive modeling, image processing techniques, and chatbot development are vital for creating intelligent applications across various sectors. The continuous evolution of AI technology and its applications underscores the importance of staying informed and adopting these tools to remain competitive in today's business landscape.

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The Software segment was valued at USD 27.50 billion in 2019 and showed a gradual increase during the forecast period.

Requ

The operating profit of Artificial Intelligence Tech with headquarters in the United States amounted to ****** million U.S. dollars in 2023. The reported fiscal year ends on February 28.Compared to the earliest depicted value from 2019 this is a total decrease by approximately 12.21 million U.S. dollars. The trend from 2019 to 2023 shows, however, that this decrease did not happen continuously.

This document includes relevant text from the 2016 and 2019 national AI R&D strategic plans, along with updates prepared in 2023 based on Administration and interagency evaluation of the National AI R&D Strategic Plan: 2019 Update as well as community responses to a Request for Information on updating the Plan. The 2019 strategies were broadly determined to be valid going forward. The 2023 update adds a new Strategy 9, which establishes a principled and coordinated approach to international collaboration in AI research.

Description:

The dataset ‘DMSP Particle Precipitation AI-ready Data’ accompanies the manuscript “Next generation particle precipitation: Mesoscale prediction through machine learning (a case study and framework for progress)” submitted to AGU Space Weather Journal and used to produce new machine learning models of particle precipitation from the magnetosphere to the ionosphere. Note that we have attempted to make these data ready to be used in artificial intelligence/machine learning explorations following a community definition of ‘AI-ready’ provided at https://github.com/rmcgranaghan/data_science_tools_and_resources/wiki/Curated-Reference%7CChallenge-Data-Sets

The purpose of publishing these data is two-fold:

To allow reuse of the data that led to the manuscript and extension, rather than reinvention, of the research produced there; and

To be an ‘AI-ready’ challenge data set to which the artificial intelligence/machine learning community can apply novel methods.

These data were compiled, curated, and explored by: Ryan McGranaghan, Enrico Camporeale, Kristina Lynch, Jack Ziegler, Téo Bloch, Mathew Owens, Jesper Gjerloev, Spencer Hatch, Binzheng Zhang, and Susan Skone

Citation:

For anyone using these data, please cite each of the following papers:

McGranaghan, R. M., Ziegler, J., Bloch, T., Hatch, S., Camporeale, E., Lynch, K., et al. (2021). Toward a next generation particle precipitation model: Mesoscale prediction through machine learning (a case study and framework for progress). Space Weather, 19, e2020SW002684. https://doi.org/10.1029/2020SW002684

McGranaghan, R. (2019), Eight lessons I learned leading a scientific “design sprint”, Eos, 100, https://doi.org/10.1029/2019EO136427. Published on 11 November 2019.

The Artificial Intelligence (AI) in Workspace market is poised for significant expansion, projected to reach approximately USD 14,820 million by 2025 and grow at a robust Compound Annual Growth Rate (CAGR) of 4.9% throughout the forecast period. This expansion is fundamentally driven by the increasing demand for enhanced productivity, automation of routine tasks, and the need for sophisticated data analysis to inform business decisions. Companies are increasingly integrating AI-powered solutions such as intelligent chatbots for customer service and internal support, advanced voice assistants for hands-free operations, and collaborative office tools that streamline team communication and project management. Furthermore, the burgeoning adoption of AI in network monitoring and data analytics is crucial for optimizing operational efficiency and deriving actionable insights from vast datasets. The market’s growth is also bolstered by technological advancements in AI algorithms, processing power, and the widespread availability of cloud infrastructure, making these solutions more accessible and cost-effective for businesses of all sizes. The competitive landscape is characterized by a dynamic interplay of established tech giants and innovative startups, focusing on developing both hardware and software components, as well as offering comprehensive AI services. Key players like Google, IBM, Microsoft, and Oracle are heavily investing in R&D to offer integrated AI platforms, while specialized companies are carving out niches in specific applications. The market’s segmentation reveals a strong demand across various applications, with Automated Systems and Data Analytics expected to lead the charge, followed by Chatbots and Voice Assistants. Geographically, North America, particularly the United States, is anticipated to remain a dominant region due to its early adoption of AI technologies and strong presence of innovative enterprises. The Asia Pacific region, driven by China and India, is expected to witness the fastest growth, fueled by rapid digital transformation and increasing investments in AI infrastructure and talent. Restraints such as data privacy concerns, the high cost of implementation for some advanced solutions, and the need for skilled personnel to manage AI systems are being addressed through ongoing innovation and development of user-friendly platforms. This report offers an in-depth analysis of the Artificial Intelligence (AI) in Workspace market, providing valuable insights for stakeholders aiming to navigate this dynamic landscape. The study spans a comprehensive period from 2019 to 2033, with a base year of 2025 and a forecast period extending from 2025 to 2033, encompassing historical data from 2019-2024. The report delves into market concentration, key trends, regional dominance, product insights, and crucial market drivers, challenges, and emerging opportunities. With an estimated market size projected to reach tens of millions of dollars, this report is an indispensable resource for understanding the present and future of AI integration in professional environments.

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AI In Consumer Electronics Market Size 2025-2029

The ai in consumer electronics market size is valued to increase by USD 125.94 billion, at a CAGR of 15.2% from 2024 to 2029. Increasing consumer demand for enhanced personalization and intuitive user experiences will drive the ai in consumer electronics market.

Major Market Trends & Insights

APAC dominated the market and accounted for a 37% growth during the forecast period.
By Technology - Machine learning segment was valued at USD 32 billion in 2023
By Application - Personalized recommendations segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 259.68 million
Market Future Opportunities: USD 125940.50 million
CAGR from 2024 to 2029 : 15.2%

Market Summary

In the dynamic consumer electronics market, artificial intelligence (AI) has emerged as a key driver of innovation and growth. The relentless pursuit of enhanced personalization and intuitive user experiences fuels the demand for AI integration in various devices. From voice assistants in smartphones and smart speakers to predictive analytics in wearable technology, AI is transforming the way consumers interact with their devices. Simultaneously, on-device AI processing is gaining traction as a response to the increasing data demands and the need for real-time responses. This trend enables devices to learn from user behavior and adapt accordingly, providing a more personalized and efficient user experience.
However, the proliferation of AI in consumer electronics is not without challenges. Heightened concerns regarding data privacy and security have become a significant hurdle for manufacturers and developers. Ensuring user data is protected while allowing for seamless AI integration is a delicate balance that must be maintained. Despite these challenges, the future of AI in consumer electronics remains promising. As technology continues to evolve, we can expect AI to become more sophisticated and integrated into our daily lives, offering new opportunities for innovation and convenience. 

What will be the Size of the AI In Consumer Electronics Market during the forecast period?

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How is the AI In Consumer Electronics Market Segmented ?

The ai in consumer electronics 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.

Technology

  Machine learning
  Natural language processing
  Others


Application

  Personalized recommendations
  Predictive maintenance
  Enhanced security
  Energy management
  Others


Product

  Computing devices
  Home appliances
  Entertainment devices
  Communication devices
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    Australia
    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Technology Insights

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

Machine learning is a transformative force in the consumer electronics market, fueling the intelligence layer of modern devices and enabling them to learn from data, identify patterns, and adapt to user behavior. This segment powers a range of applications, from content recommendation engines in smart TVs to energy-efficient battery management systems in smartphones and wearables. Intel's December 2023 launch of Core Ultra processors, featuring integrated Neural Processing Units (NPUs), underscores the growing importance of on-device AI and machine learning. These NPUs accelerate local workloads, reducing reliance on cloud-based services and enhancing privacy. AI applications span from natural language processing and biometric authentication to computer vision systems and robotics process automation.

This growth is driven by advancements in explainable AI techniques, real-time data processing, and edge computing devices, among other factors. The integration of AI into consumer electronics continues to evolve, shaping the future of human-computer interaction, privacy, and user experiences.

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The Machine learning segment was valued at USD 32 billion in 2019 and showed a gradual increase during the forecast period.

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Regional Analysis

APAC is estimated to contribute 37% 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 Asia-Pacific region plays a pivotal role in the dynamic global the market, ser