As per Cognitive Market Research's latest published report, the Global Machine Learning market size was USD 24,345.76 million in 2021 and it is forecasted to reach USD 206,235.41 million by 2028. Machine Learning Industry's Compound Annual Growth Rate will be 42.64% from 2023 to 2030. Market Dynamics of Machine Learning Market

Key Drivers for Machine Learning Market

Explosion of Big Data Across Industries: The substantial increase in both structured and unstructured data generated by sensors, social media, transactions, and IoT devices is driving the demand for machine learning-based data analysis.

Widespread Adoption of AI in Business Processes: Machine learning is facilitating automation, predictive analytics, and optimization in various sectors such as healthcare, finance, manufacturing, and retail, thereby enhancing efficiency and outcomes.

Increased Availability of Open-Source Frameworks and Cloud Platforms: Resources like TensorFlow, PyTorch, and scalable cloud infrastructure are simplifying the process for developers and enterprises to create and implement machine learning models.

Growing Investments in AI-Driven Innovation: Governments, venture capitalists, and major technology companies are making substantial investments in machine learning research and startups, which is accelerating progress and market entry.

Key Restraints for Machine Learning Market

Shortage of Skilled Talent in ML and AI: The need for data scientists, machine learning engineers, and domain specialists significantly surpasses the available supply, hindering scalability and implementation in numerous organizations.

High Computational and Operational Costs: The training of intricate machine learning models necessitates considerable computing power, energy, and infrastructure, resulting in high costs for startups and smaller enterprises.

Data Privacy and Regulatory Compliance Challenges: Issues related to user privacy, data breaches, and adherence to regulations such as GDPR and HIPAA present obstacles in the collection and utilization of data for machine learning.

Lack of Model Transparency and Explainability: The opaque nature of certain machine learning models undermines trust, particularly in sensitive areas like finance and healthcare, where the need for explainable AI is paramount.

Key Trends for Machine Learning Market

Growth of AutoML and No-Code ML Platforms: Automated machine learning tools are making AI development more accessible, enabling individuals without extensive coding or mathematical expertise to construct models.

Integration of ML with Edge Computing: Executing machine learning models locally on edge devices (such as cameras and smartphones) is enhancing real-time performance and minimizing latency in applications.

Ethical AI and Responsible Machine Learning Practices: Increasing emphasis on fairness, bias reduction, and accountability is shaping ethical frameworks and governance in ML adoption.

Industry-Specific ML Applications on the Rise: Custom ML solutions are rapidly emerging in sectors like agriculture (crop prediction), logistics (route optimization), and education (personalized learning).

COVID-19 Impact:

Similar to other industries, the covid-19 situation has affected the machine learning industry. Despite the dire conditions and uncertain collapse, some industries have continued to grow during the pandemic. During covid 19, the machine learning market remains stable with positive growth and opportunities. The global machine learning market faces minimal impact compared to some other industries.The growth of the global machine learning market has stagnated owing to automation developments and technological advancements. Pre-owned machines and smartphones widely used for remote work are leading to positive growth of the market. Several industries have transplanted the market progress using new technologies of machine learning systems. June 2020, DeCaprio et al. Published COVID-19 pandemic risk research is still in its early stages. In the report, DeCaprio et al. mentions that it has used machine learning to build an initial vulnerability index for the coronavirus. The lab further noted that as more data and results from ongoing research become available, it will be able to see more practical applications of machine learning in predicting infection risk. What is&nbs...

Machine Learning Market size was valued at USD 53.49 Billion in 2023 poised to grow between USD 72.10 Billion in 2024 to USD 1233.02 Billion by 2032, growing at a CAGR of 34.8% in the forecast period (2025-2032).

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

The global machine learning market size surpassed USD 91.31 billion in 2025 and is projected to witness a CAGR of over 35.3%, crossing USD 1.88 trillion revenue by 2035, driven by Increasing Adoption of IoT and Automation

Machine Learning Market size was valued at USD 10.24 Billion in 2024 and is projected to reach USD 200.08 Billion by 2031, growing at a CAGR of 10.9% from 2024 to 2031.

Key Market Drivers:

Increasing Data Volume and Complexity: The explosion of digital data is fueling ML adoption across industries. Organizations are leveraging ML to extract insights from vast, complex datasets. According to the European Commission, the volume of data globally is projected to grow from 33 zettabytes in 2018 to 175 zettabytes by 2025. For instance, on September 15, 2023, Google Cloud announced new ML-powered data analytics tools to help enterprises handle increasing data complexity.

Advancements in AI and Deep Learning Algorithms: Continuous improvements in AI algorithms are expanding ML capabilities. Deep learning breakthroughs are enabling more sophisticated applications. The U.S. National Science Foundation reported a 63% increase in AI research publications from 2017 to 2021. For instance, on August 24, 2023, DeepMind unveiled Graphcast, a new ML weather forecasting model achieving unprecedented accuracy.

The automated machine learning market had an estimated market share worth US$ 700 million in 2023, and it is predicted to reach a global market valuation of US$ 42.2 billion by 2034, growing at a steady CAGR of 44.9% from 2024 to 2034.

Report Attribute	Details
Estimated Market Value for 2023	US$ 700 million
Expected Market Value for 2024	US$ 1 billion
Projected Forecast Value for 2034	US$ 42.2 billion
Anticipated Growth Rate from 2024 to 2034	4 4.9% CAGR

Automated Machine Learning Market Historical Analysis from 2019 to 2023 vs. Forecast Outlook from 2024 to 2034

Historical CAGR from 2019 to 2023	48.2%
Forecast CAGR from 2024 to 2034	44.9%

Category-wise Insights

Solution Type	Standalone
CAGR from 2024 to 2034	44.7%

Automation Type	Feature Engineering
Market Share in 2024	44.5%

Region-wise Analysis

Countries	CAGR from 2024 to 2034
The United States	45%
The United Kingdom	46.1%
China	45.4%
Japan	46%
South Korea	47.2%

Report Scope

Report Attribute	Details
Growth Rate	CAGR of 44.9% from 2024 to 2034
Market value in 2024	US$ 1 billion
Market value in 2034	US$ 42.2 billion
Base Year for Estimation	2023
Historical Data	2019 to 2023
Forecast Period	2024 to 2034
Quantitative Units	US$ billion for value
Report Coverage	Revenue Forecast, Company Ranking, Competitive Landscape, Growth Factors, Trends, and Pricing Analysis
Segments Covered	Solution Automation Type End User Region
Regions Covered	North America Latin America Western Europe Eastern Europe South Asia and Pacific East Asia The Middle East & Africa
Countries Profiled	The United States Canada Brazil Mexico Germany The United Kingdom France Spain Italy Poland Russia Czech Republic Romania India Bangladesh Australia New Zealand China Japan South Korea GCC Countries South Africa Israel
Key Companies Profiled	Datarobot Inc. Amazon Web Services Inc. dotData Inc. IBM Corporation Dataiku SAS Institute Inc. Microsoft Corporation Google LLC H2O.ai Aible Inc.
Customization Scope	Available on Request

Snapshot img

Machine Learning Market Size 2024-2028

The machine learning market size is forecast to increase by USD 162.94 billion at a CAGR of 67.63% between 2023 and 2028. Market growth hinges on several factors, notably the rising adoption of cloud-based offerings, the integration of machine learning in customer experience management, and its application in predictive analytics. The scalability and flexibility of cloud solutions attract businesses seeking efficient operations and cost savings. Machine learning's role in enhancing customer experiences and predictive analytics drives demand, as companies strive to stay competitive in an increasingly data-driven landscape. This convergence of technologies not only drives innovation in machine learning chips but also reshapes business strategies, enabling organizations to harness data-driven insights for informed decision-making and sustainable growth in the dynamic market landscape.

What will be the Size of the Machine Learning Market During the Forecast Period?

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Machine Learning Market Segmentation

The market research report provides comprehensive data (region wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments.

End-user Outlook

  BFSI
  Retail
  Telecommunications
  Healthcare
  Automotive
  Others





Deployment Outlook 

  Cloud-based
  On-premise





Region Outlook 

  North America

    The U.S.
    Canada





  Europe

    U.K.
    Germany
    France
    Rest of Europe





  APAC

    China
    India


  South America

    Chile
    Argentina
    Brazil





  Middle East & Africa

    Saudi Arabia
    South Africa
    Rest of the Middle East & Africa

By End-user

The market share growth by the BFSI segment will be significant during the forecast period. Machine learning, a subset of artificial intelligence and computer science, utilizes algorithms to enable computer systems to learn and improve from experience without being explicitly programmed. This technology is revolutionizing various industries, including finance, insurance, and services (BFSI), by reducing costs, enhancing customer relations, and improving risk management and decision-making processes. Machine learning is also transforming sectors like self-driving cars, cybersecurity, face recognition, social media platforms, e-commerce, and retail through chatbots and large enterprises' digital transformation. Cloud-based and cloud computing technologies facilitate machine learning's adoption by organizations, enabling scalability and agility.

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The BFSI segment was valued at USD 632.90 million in 2018 and continued to grow until 2022. Additionally, machine learning is essential in sectors like healthcare, big data, and cybersecurity, where it powers software programs, security analytics, and cyber specialists' work against cyber threats and supply chain attacks. The technology's expansion includes 5G wireless networking, edge computing, hybrid cloud, and AI technologies' integration in public sectors, financial services, IT and telecommunications, banking, automotive and transportation, advertising and media, energy and utilities, and market expansion. Responsible computing is a crucial aspect of machine learning's implementation to ensure ethical and unbiased use. Hence, such factors are fuelling the growth of this segment during the forecast period.

Regional Analysis

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North America is estimated to contribute 34% 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. This region is anticipated to be the major revenue contributor to the market during the forecast period. The demand for machine learning in North America is primarily due to the high adoption of cloud and machine learning and big data analytics to generate business insights. The region is also witnessing an increase in data generation from industries such as telecommunications, manufacturing, retail, and energy, driving demand for machine learning-based solutions. Hence, such factors are driving the market in North America during the forecast period.

Machine Learning Market Dynamics

In the dynamic realm of technology, machine learning (ML), a subset of artificial intelligence (AI), continues to revolutionize computer science through advanced algorithms. ML's applications span across various sectors, including self-driving cars in transportation, cybersecurity for securing computer systems in organizations, and face recognition in social medi

Machine Learning Market Outlook

The global machine learning market is projected to witness a remarkable growth trajectory, with the market size estimated to reach USD 21.17 billion in 2023 and anticipated to expand to USD 209.91 billion by 2032, growing at a compound annual growth rate (CAGR) of 29.2% over the forecast period. This extraordinary growth is primarily propelled by the escalating demand for artificial intelligence-driven solutions across various industries. As businesses seek to leverage machine learning for improving operational efficiency, enhancing customer experience, and driving innovation, the market is poised to expand rapidly. Key factors contributing to this growth include advancements in data generation, increasing computational power, and the proliferation of big data analytics.

A pivotal growth factor for the machine learning market is the ongoing digital transformation across industries. Enterprises globally are increasingly adopting machine learning technologies to optimize their operations, streamline processes, and make data-driven decisions. The healthcare sector, for example, leverages machine learning for predictive analytics to improve patient outcomes, while the finance sector uses machine learning algorithms for fraud detection and risk assessment. The retail industry is also utilizing machine learning for personalized customer experiences and inventory management. The ability of machine learning to analyze vast amounts of data in real-time and provide actionable insights is fueling its adoption across various applications, thereby driving market growth.

Another significant growth driver is the increasing integration of machine learning with the Internet of Things (IoT). The convergence of these technologies enables the creation of smarter, more efficient systems that enhance operational performance and productivity. In manufacturing, for instance, IoT devices equipped with machine learning capabilities can predict equipment failures and optimize maintenance schedules, leading to reduced downtime and costs. Similarly, in the automotive industry, machine learning algorithms are employed in autonomous vehicles to process and analyze sensor data, improving navigation and safety. The synergistic relationship between machine learning and IoT is expected to further propel market expansion during the forecast period.

Moreover, the rising investments in AI research and development by both public and private sectors are accelerating the advancement and adoption of machine learning technologies. Governments worldwide are recognizing the potential of AI and machine learning to transform industries, leading to increased funding for research initiatives and innovation centers. Companies are also investing heavily in developing cutting-edge machine learning solutions to maintain a competitive edge. This robust investment landscape is fostering an environment conducive to technological breakthroughs, thereby contributing to the growth of the machine learning market.

Supervised Learning, a subset of machine learning, plays a crucial role in the advancement of AI-driven solutions. It involves training algorithms on a labeled dataset, allowing the model to learn and make predictions or decisions based on new, unseen data. This approach is particularly beneficial in applications where the desired output is known, such as in classification or regression tasks. For instance, in the healthcare sector, supervised learning algorithms are employed to analyze patient data and predict health outcomes, thereby enhancing diagnostic accuracy and treatment efficacy. Similarly, in finance, these algorithms are used for credit scoring and fraud detection, providing financial institutions with reliable tools for risk assessment. As the demand for precise and efficient AI applications grows, the significance of supervised learning in driving innovation and operational excellence across industries becomes increasingly evident.

From a regional perspective, North America holds a dominant position in the machine learning market due to the early adoption of advanced technologies and the presence of major technology companies. The region's strong focus on R&D and innovation, coupled with a well-established IT infrastructure, further supports market growth. In addition, Asia Pacific is emerging as a lucrative market for machine learning, driven by rapid industrialization, increasing digitalization, and government initiatives promoting AI adoption. The region is witnessing significant investments in AI technologies, particu

The global machine learning market size reached USD 31.0 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 440.6 Billion by 2033, exhibiting a growth rate (CAGR) of 32.6% during 2025-2033. The escalating demand for advanced analytics and data-driven insights, the increasing volume and complexity of data generated by organizations, and the availability of scalable computing resources are some of the major factors propelling the market.

Report Attribute	Key Statistics
Base Year	2024
Forecast Years	2025-2033
Historical Years	2019-2024
Market Size in 2024	USD 31.0 Billion
Market Forecast in 2033	USD 440.6 Billion
Market Growth Rate (2025-2033)	32.6%

IMARC Group provides an analysis of the key trends in each segment of the global machine learning market report, along with forecasts at the global, regional, and country levels from 2025-2033. Our report has categorized the market based on component, deployment, enterprise size, and end use.

In 2024, the market size change in the 'Machine Learning' segment of the artificial intelligence market worldwide was modeled to stand at ***** percent. Between 2021 and 2024, the market size change dropped by ***** percentage points. The market size change is expected to drop by **** 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.

Snapshot img

Deep Learning Market Size 2024-2028

The deep learning market size is forecast to increase by USD 10.85 billion at a CAGR of 26.06% between 2023 and 2028.

Deep learning technology is revolutionizing various industries, including healthcare. In the healthcare sector, deep learning is being extensively used for the diagnosis and treatment of musculoskeletal and inflammatory disorders. The market for deep learning services is experiencing significant growth due to the increasing availability of high-resolution medical images, electronic health records, and big data. Medical professionals are leveraging deep learning technologies for disease indications such as failure-to-success ratio, image interpretation, and biomarker identification solutions. Moreover, with the proliferation of data from various sources such as social networks, smartphones, and IoT devices, there is a growing need for advanced analytics techniques to make sense of this data. Companies In the market are collaborating to offer comprehensive information services and digital analytical solutions. However, the lack of technical expertise among medical professionals poses a challenge to the widespread adoption of deep learning technologies. The market is witnessing an influx of startups, which is intensifying the competition. Deep learning services are being integrated with compatible devices for image processing and prognosis. Molecular data analysis is another area where deep learning technologies are making a significant impact.

What will be the Size of the Deep Learning Market During the Forecast Period?

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A subset of machine learning and artificial intelligence (AI), is a computational method inspired by the structure and function of the human brain. This technology utilizes neural networks, a type of machine learning model, to recognize patterns and learn from data. In the US market, deep learning is gaining significant traction due to its ability to process large amounts of data and extract meaningful insights. The market In the US is driven by several factors. One of the primary factors is the increasing availability of big data.
Moreover, with the proliferation of data from various sources such as social networks, smartphones, and IoT devices, there is a growing need for advanced analytics techniques to make sense of this data. Deep learning algorithms, with their ability to learn from vast amounts of data, are well-positioned to address this need. Another factor fueling the growth of the market In the US is the increasing adoption of cloud-based technology. Cloud-based solutions offer several advantages, including scalability, flexibility, and cost savings. These solutions enable organizations to process large datasets and train complex models without the need for expensive hardware.

How is this Industry segmented and which is the largest segment?

The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Application

  Image recognition
  Voice recognition
  Video surveillance and diagnostics
  Data mining


Type

  Software
  Services
  Hardware


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  APAC

    China


  South America



  Middle East and Africa

By Application Insights

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

In the realm of artificial intelligence (AI), image recognition holds significant value, particularly in sectors such as banking and finance (BFSI). This technology's ability to accurately identify and categorize images is invaluable, as extensive image repositories In these industries cannot be easily forged. BFSI firms utilize AI image recognition for various applications, including personalizing customer communication, maintaining a competitive edge, and automating repetitive tasks to boost productivity. For instance, social media platforms like Facebook employ this technology to correctly identify and assign images to the right user account with an impressive accuracy rate of approximately 98%. Moreover, AI image recognition plays a crucial role in eliminating fraudulent social media accounts.

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The image recognition segment was valued at USD 1.05 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 36% 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 Automated Machine Learning Market Report Segments the Industry Into Solution (On-Premise and Cloud), Automation Type (Data Processing, Feature Engineering, Modeling, and Visualization), Organization Size (Large Enterprises and Small and Medium Enterprises [SMEs]), End User (BFSI, Retail and E-Commerce, Healthcare, Manufacturing, and Other End-Users) and Geography.

Machine Learning Market is predicted to reach $407.72 billion by 2030 with a CAGR of 45.29% from 2023 to 2030

The Machine Learning Market size was valued at USD 52.02 billion in 2023 and is projected to reach USD 420.73 billion by 2032, exhibiting a CAGR of 34.8 % during the forecasts period. This remarkable growth is driven by the increasing demand for data-driven decision-making, coupled with the advent of advanced algorithms. Moreover, the burgeoning adoption of cloud computing and Artificial Intelligence (AI) solutions further fuels market expansion. Machine learning is a subfield of artificial intelligence where data provides an intentionally programmed pattern, and an algorithm modifies its actions based on usage. It allows the computer to process large data sets and makes it possible for the computer to solve problems, make decisions or derive conclusions from these data. These are supervised learning, also identified as pattern recognition, where the computer is trained on given examples; unsupervised learning, where the computer searches for patterns within a given data set when the data is not marked; and reinforcement learning where the computer learns by trial and error. Its uses cut across various industries including banking, the medical sector, as well as managerial tasks in enhancing automation in executing tasks as well as analyzing information. Machine learning progresses in and optimized as the volumes increase exponentially, thus realigning and revolutionizing sectors across the globe.

Artificial Intelligence in Machine Learning Market Outlook

The global market size for Artificial Intelligence in Machine Learning is projected to experience significant growth, expanding from approximately USD 21 billion in 2023 to an estimated USD 124 billion by 2032, at a robust CAGR of 22%. This remarkable growth is driven by several factors, including technological advancements, increased adoption across various industries, and the growing importance of data-driven decision-making.

One of the primary growth factors for the AI in Machine Learning market is the rapid advancement in computational power and technology. The continuous evolution of processing capabilities, including the development of specialized AI chips and improvements in cloud computing, has enabled the efficient handling and analysis of vast amounts of data. These technological advancements have made it feasible for organizations to implement machine learning algorithms and AI models at scale, resulting in increased productivity and operational efficiency.

Another contributing factor to the market growth is the widespread adoption of AI and machine learning across various sectors. Industries such as healthcare, finance, retail, and manufacturing are increasingly leveraging these technologies to enhance their services, improve customer experiences, and streamline operations. In healthcare, for instance, AI-driven machine learning models are being used for predictive analytics, personalized medicine, and diagnostics, leading to improved patient outcomes and cost reduction. Similarly, in finance, machine learning algorithms aid in fraud detection, risk management, and automated trading, contributing to enhanced financial services.

The growing importance of data-driven decision-making is also propelling the market. Organizations are recognizing the value of data as a strategic asset and are investing heavily in AI and machine learning technologies to extract actionable insights. This shift towards data-centric business strategies is fostering the adoption of machine learning solutions that can analyze large datasets, identify patterns, and make accurate predictions. Consequently, businesses can make informed decisions, optimize processes, and gain a competitive edge in the market.

The integration of Cloud Machine Learning is revolutionizing how businesses approach data-driven decision-making. By leveraging the cloud, organizations can access powerful machine learning tools and resources without the need for substantial on-premises infrastructure. This flexibility allows companies to scale their machine learning initiatives efficiently, adapting to changing business needs and data volumes. Cloud Machine Learning also facilitates collaboration across teams and geographies, enabling seamless sharing of insights and models. As a result, businesses are better equipped to harness the full potential of their data, driving innovation and gaining a competitive edge in the market.

Regionally, North America is expected to dominate the AI in Machine Learning market due to the presence of major technology companies, a robust startup ecosystem, and significant investments in research and development. The region's well-established infrastructure and favorable regulatory environment further support the adoption of AI and machine learning technologies. Europe and Asia Pacific are also anticipated to witness substantial growth, driven by increased government initiatives, a growing number of AI-focused startups, and rising awareness about the benefits of AI and machine learning across various industries.

Component Analysis

The AI in Machine Learning market can be segmented by component into software, hardware, and services. Each of these components plays a crucial role in the deployment and functioning of AI and machine learning systems. The software segment encompasses machine learning frameworks, development platforms, and analytics tools that facilitate the creation, training, and deployment of AI models. This segment is expected to hold the largest market share due to the increasing demand for advanced analytics and predictive modeling tools across industries.

In contrast, the hardware segment includes specialized AI chips, servers, and storage devices designed to support the high computational requirements of machine learning applications. The growing need for powerful and efficient hardware to process large datasets and execute complex al

Artificial Intelligence & Advanced Machine Learning Market size valued $137.93 Bn in 2023 & expected to reach $1790.43 Bn by 2032, at CAGR 29.2% from 2024-2032.

AI and Machine Learning Market is expected to reach USD 1087.0 billion by 2034, growing at a CAGR of 35.8%, fueled by automation, data analytics, and digital transformation.

Global Machine Learning market size is expected to reach $325.8 billion by 2029 at 36.5%, segmented as by hardware, graphics processing units (gpus), application-specific integrated circuits (asics), field programmable gate arrays (fpgas)

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 automated machine learning market is surging, with a market size valued at USD 3501.6 million in 2025 and projected to reach a whopping USD 674504.7 million by 2033, exhibiting a remarkable CAGR of 42.2% during the forecast period of 2025-2033. The growing adoption of artificial intelligence (AI) and machine learning (ML) technologies, combined with the increasing volume and complexity of data, are key drivers fueling this growth. Key trends shaping the automated machine learning market include the rise of cloud-based solutions, the integration of AI and ML into various business processes, and the increasing adoption of automated machine learning in diverse industry verticals such as BFSI, retail, healthcare, manufacturing, and IT & telecommunications. However, factors such as the lack of skilled professionals and data security concerns may pose as challenges to the market's growth. Prominent companies operating in this market include IBM, Oracle, Microsoft, ServiceNow, Google LLC, Baidu Inc., AWS, Alteryx, Salesforce, and Altair, among others. Recent developments include: In May 2024, Leveraging over two decades of collaboration, IBM and Adobe are providing clients with the expertise and technology to fully utilize Generative AI in marketing, content creation, and brand management. This is accomplished through a distinctive partnership that encompasses both technology solutions and consulting services, fostering collaborative innovation across hybrid cloud infrastructure, data utilization, applications, and a diverse Generative AI strategy. , In April 2024, IBM on its WatsonX AI and data platform has launched Meta Llama 3, the latest iteration of Meta's open-source large language model. This extension enhances IBM's watsonx.ai model repository, facilitating enterprise innovation with its Granite series models, alongside offerings from top model providers such as Meta. .