As of 2022, the leading company in the Chinese computer vision industry was Sense Time, with a market share of over 23 percent. Although the enterprise is publicly traded on the Hong Kong Exchange, the Chinese Cybersecurity Administration, via the China Internet Investment Fund, holds the golden share.

Machine Vision Market was valued to be worth USD 14,571.29 Million in 2024 and is projected to grow at CAGR of 9.8% from 2025 to 2032 with value of USD 28,615.08 Million by 2032. Additionaly, Market value is set to reach USD 15,659.77 Million in 2025.

The greatest use of artificial intelligence (AI) capabilities within business functions in 2022 was to be found in robotic process automation. In three of the major industries AI capabilities were found in nearly half the business functions. The least AI focused industry was healthcare and pharmaceuticals, with only computer vision being found in a third of business functions in the field. Transformers were the least used AI capability overall with around ten to twelve percent of business functions using them. This can be explained by the virtue of them being transformers and thus new and untested technology.

The Computer Vision Solution market has seen remarkable growth over the past several years, driven by advancements in artificial intelligence (AI) and machine learning technologies. This dynamic field enables computers to interpret and understand visual information from the world, allowing businesses across various

Artificial Intelligence in Supply Chain Market size was valued at USD 4.72 Billion in 2024 and is projected to reach USD 67.65 Billion by 2031, growing at a CAGR of 46.1% from 2024 to 2031.

The Artificial Intelligence in Supply Chain market is driven by the growing need for increased efficiency, cost reduction, and improved decision-making across logistics and supply chain operations. The rising complexity of global supply chains, combined with the demand for faster delivery times and real-time visibility, has led companies to adopt AI-powered solutions like predictive analytics, demand forecasting, and inventory optimization. AI’s ability to process large volumes of data and provide actionable insights helps businesses mitigate risks, manage disruptions, and improve overall supply chain resilience. Additionally, the integration of AI with IoT, advancements in machine learning, and the adoption of cloud-based platforms are further accelerating the deployment of AI in supply chain management. Increasing awareness about sustainability and the need for transparent supply chains are also contributing to market growth, as AI helps in optimizing resource usage and reducing carbon footprints.

Artificial intelligence is used in retail companies around the world. In a 2023 survey carried out in the United States and the EMEA region, nearly 40 percent of retail directors stated they used artificial intelligence (AI), computer vision (CV), and machine vision (MV) for selected operations and departments. Another 35 percent of respondents reported to have already scaled up this type of technology, while 15 percent of surveyed retail directors projected that it would be implemented within the next 12 months.

Intel Corporation engages in the design, manufacture, and sale of computer products and technologies worldwide. The company operates through CCG, DCG, IOTG, Mobileye, NSG, PSG, and All Other segments. It offers platform products, such as central processing units and chipsets, and system-on-chip and multichip packages; and non-platform or adjacent products, including accelerators, boards and systems, connectivity products, graphics, and memory and storage products. The company also provides high-performance compute solutions for targeted verticals and embedded applications for retail, industrial, and healthcare markets; and solutions for assisted and autonomous driving comprising compute platforms, computer vision and machine learning-based sensing, mapping and localization, driving policy, and active sensors. In addition, it offers workload-optimized platforms and related products for cloud service providers, enterprise and government, and communications service providers. The company serves original equipment manufacturers, original design manufacturers, and cloud service providers. Intel Corporation has a strategic partnership with MILA to develop and apply advances in artificial intelligence methods for enhancing the search in the space of drugs. The company was incorporated in 1968 and is headquartered in Santa Clara, California.

Snapshot img

Artificial Intelligence in Games Market Size 2025-2029

The AI in games market size is forecast to increase by USD 27.47 billion at a CAGR of 42.3% between 2024 and 2029.

Artificial Intelligence (AI) is revolutionizing the gaming industry, offering enhanced user experiences and new gameplay mechanics. One significant trend is the increasing adoption of Augmented Reality (AR) and virtual reality, which leverage AI to create more enriching environments and interactive characters. Another growth factor is the emergence of cloud gaming, enabling seamless access to high-performance games without the need for expensive hardware.
However, network latency remains a challenge, as even minor delays can negatively impact the gaming experience. AI is also being used to develop more sophisticated non-player characters and to personalize game content based on player behavior. Overall, these trends and challenges are shaping the future of the gaming market and driving innovation in the industry.

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

Request Free Sample

In addition, this results in more realistic and dynamic game environments, improving overall player engagement. Network latency, a common issue in online gaming, is being addressed through AI-enabled platforms. These systems use GPUs and CPUs to process data in real-time, ensuring smooth gameplay and reducing lag. AI is also transforming the way games are created, with middleware systems like Euphoria powering realistic character behavior and physics. Ray tracing, another AI-driven technology, creates lifelike lighting and reflections, adding another layer of realism to 3D games. AI-generated language and recognizable names have been omitted to maintain a formal business tone. The gaming industry continues to explore the potential of AI, with innovations in image upscaling and other areas expected to further enhance the player experience.

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

The market 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.

Type

  AI enabled platforms
  AI enabled games


Technology

  Machine learning
  Natural language processing
  Computer vision
  Robotics


Game Genre

  Action
  Adventure
  Casual
  Racing
  Simulation
  Sports
  Strategy


Application

  Gameplay Optimization
  Character Behavior Generation
  Level Design
  Player Engagement


Geography

  North America

    Canada
    US


  APAC

    China
    Japan
    South Korea


  Europe

    Germany
    UK
    France
    Italy


  South America

    Brazil


  Middle East and Africa

By Type Insights

The AI enabled platforms segment is estimated to witness significant growth during the forecast period. Artificial Intelligence (AI) is revolutionizing the gaming industry through real-time processing, enhancing multiplayer experiences, and improving matchmaking and anti-cheat systems. AI's expertise in data analysis, prediction, and action-taking enables developers to create advanced games and environments more efficiently. With the advent of 5G networks, AI-driven mobile games are becoming increasingly popular. Microsoft and Google are leading this transformation, offering powerful AI platforms and tools that enable personalized and engaging gaming experiences.

AI's ability to analyze player behavior and data provides valuable insights into player preferences, leading to more customized and enriching gaming experiences. By automating repetitive tasks and offering real-time responses, AI is set to revolutionize the gaming industry, offering unparalleled levels of engagement and interactivity.

Get a glance at the share of various segments. Request Free Sample

The AI enabled platforms segment was valued at USD 1.58 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 40% 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.

For more insights on the market share of various regions Request Free Sample

The market is poised for expansion due to the rising demand for AI-driven games, fueled by the popularity of esports. With a significant number of gamers in the region competing in tournaments such as the International DOTA 2 Championship, gaming is increasingly viewed as a professional career path in countries like the US. In response, game developers and publishers are investing in the creation of multiplayer games to cater to the escalating esports trend. The integration of AI algorithms in esports titles aims to attract larger fan bases and boost

Global Computer Graphics Market size was evaluated at $25.5 Billion in 2022 and is slated to hit $35.1 Billion by the end of 2030 with a CAGR of 9.1%.

Abstract copyright UK Data Service and data collection copyright owner.

The Department of Digital, Culture, Media and Sport's (DCMS) Office for Artificial Intelligence commissioned research to model current and future estimates of (i) the adoption of Artificial Intelligence (AI) technologies in the UK, and (ii) the expenditure on AI technologies and AI-related labour in the UK.

The associated report provides an assessment of the scale of AI activity in UK businesses and scenarios for growth over the next twenty years

To gather data on AI adoption and spending to inform the modelling in this study, a survey of private businesses was conducted in conjunction with YouGov.

The total survey sample was 2,019 private businesses, including 1,127 small businesses (55.8%), 291 medium businesses (14.4%) and 601 large businesses (29.8%). Respondents spanned all regions of Great Britain and all private sectors. Businesses in Northern Ireland have thus not been surveyed. After removing spurious responses, the identification process of which included an analysis of expenditure responses relative to firm size (in terms of turnover), the sample reduced to 2,009 quality responses.

The survey asks respondents whether they have adopted AI technologies (including the following six technologies: machine learning, natural language processing and generation, computer vision/image processing and generation, data management and analysis, hardware, and robotic process automation), how did they source these technologies, and their expenditure on these technologies and the associated labour expenditure.

The survey asked how businesses expected their expenditure on AI and AI-related labour to increase in the next year and next 5 years to support modelling the trajectory of AI expenditure in the UK.

The study data also includes variables related to the size of the business, the business sector, turnover, and main industry worked in.

This webinar series introduce some research data with a focus on China and discuss the difference from the US data. Each webinar will cover the following topics: (1) data sources, data collection, data category, definition, description, and interpretation; (2) alternative data and derivable data from other data sources, especially some big data sources; (3) comparison of data difference between the US and China; (4) available tools for efficient data analysis; (5) discussions on pros and cons; and (6) data applications in research and teaching.

According to Cognitive Market Research, the global Ai Training Data market size is USD 1865.2 million in 2023 and will expand at a compound annual growth rate (CAGR) of 23.50% from 2023 to 2030.

The demand for Ai Training Data is rising due to the rising demand for labelled data and diversification of AI applications.
Demand for Image/Video remains higher in the Ai Training Data market.
The Healthcare category held the highest Ai Training Data market revenue share in 2023.
North American Ai Training Data will continue to lead, whereas the Asia-Pacific Ai Training Data market will experience the most substantial growth until 2030.

Market Dynamics of AI Training Data Market

Key Drivers of AI Training Data Market

Rising Demand for Industry-Specific Datasets to Provide Viable Market Output

A key driver in the AI Training Data market is the escalating demand for industry-specific datasets. As businesses across sectors increasingly adopt AI applications, the need for highly specialized and domain-specific training data becomes critical. Industries such as healthcare, finance, and automotive require datasets that reflect the nuances and complexities unique to their domains. This demand fuels the growth of providers offering curated datasets tailored to specific industries, ensuring that AI models are trained with relevant and representative data, leading to enhanced performance and accuracy in diverse applications.

In July 2021, Amazon and Hugging Face, a provider of open-source natural language processing (NLP) technologies, have collaborated. The objective of this partnership was to accelerate the deployment of sophisticated NLP capabilities while making it easier for businesses to use cutting-edge machine-learning models. Following this partnership, Hugging Face will suggest Amazon Web Services as a cloud service provider for its clients.

(Source: about:blank)

Advancements in Data Labelling Technologies to Propel Market Growth

The continuous advancements in data labelling technologies serve as another significant driver for the AI Training Data market. Efficient and accurate labelling is essential for training robust AI models. Innovations in automated and semi-automated labelling tools, leveraging techniques like computer vision and natural language processing, streamline the data annotation process. These technologies not only improve the speed and scalability of dataset preparation but also contribute to the overall quality and consistency of labelled data. The adoption of advanced labelling solutions addresses industry challenges related to data annotation, driving the market forward amidst the increasing demand for high-quality training data.

In June 2021, Scale AI and MIT Media Lab, a Massachusetts Institute of Technology research centre, began working together. To help doctors treat patients more effectively, this cooperation attempted to utilize ML in healthcare.

www.ncbi.nlm.nih.gov/pmc/articles/PMC7325854/

Restraint Factors Of AI Training Data Market

Data Privacy and Security Concerns to Restrict Market Growth

A significant restraint in the AI Training Data market is the growing concern over data privacy and security. As the demand for diverse and expansive datasets rises, so does the need for sensitive information. However, the collection and utilization of personal or proprietary data raise ethical and privacy issues. Companies and data providers face challenges in ensuring compliance with regulations and safeguarding against unauthorized access or misuse of sensitive information. Addressing these concerns becomes imperative to gain user trust and navigate the evolving landscape of data protection laws, which, in turn, poses a restraint on the smooth progression of the AI Training Data market.

How did COVID–19 impact the Ai Training Data market?

The COVID-19 pandemic has had a multifaceted impact on the AI Training Data market. While the demand for AI solutions has accelerated across industries, the availability and collection of training data faced challenges. The pandemic disrupted traditional data collection methods, leading to a slowdown in the generation of labeled datasets due to restrictions on physical operations. Simultaneously, the surge in remote work and the increased reliance on AI-driven technologies for various applications fueled the need for diverse and relevant training data. This duali...

Ai in Retail is Undergoing Significant Transformations With the Integration of Retail AI. Companies are Leveraging Artificial Intelligence in Retail To Enhance Strategies, Improve Outcomes, And Boost Online Customer Engagement. AI Retail Solutions Like Machine Learning and Deep Learning are Commonly Used, Providing A Personalized User Experience. AI for Retail, Including Computer Vision, Is Improving Customer Experience and Inventory Management. The Use of AI Retail Technology is Expected To Surge, With Investments in AI-Powered Retail Analytics Increasing.

Global Artificial Intelligence (AI) in Hardware Market size was valued at USD 13.3 Billion in 2022 and is poised to grow from USD 23.5 Billion in 2023 to USD 84.9 Billion by 2031, growing at a CAGR of 15.5% in the forecast period (2024-2031).

Snapshot img

Synthetic Data Generation Market Size 2024-2028

The synthetic data generation market size is forecast to increase by USD 2.88 billion at a CAGR of 60.02% between 2023 and 2028.

The global synthetic data generation market is expanding steadily, driven by the growing need for privacy-compliant data solutions and advancements in AI technology. Key factors include the increasing demand for data to train machine learning models, particularly in industries like healthcare services and finance where privacy regulations are strict and the use of predictive analytics is critical, and the use of generative AI and machine learning algorithms, which create high-quality synthetic datasets that mimic real-world data without compromising security.
This report provides a detailed analysis of the global synthetic data generation market, covering market size, growth forecasts, and key segments such as agent-based modeling and data synthesis. It offers practical insights for business strategy, technology adoption, and compliance planning. A significant trend highlighted is the rise of synthetic data in AI training, enabling faster and more ethical development of models. One major challenge addressed is the difficulty in ensuring data quality, as poorly generated synthetic data can lead to inaccurate outcomes.
For businesses aiming to stay competitive in a data-driven global landscape, this report delivers essential data and strategies to leverage synthetic data trends and address quality challenges, ensuring they remain leaders in innovation while meeting regulatory demands

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

Request Free Sample

Synthetic data generation offers a more time-efficient solution compared to traditional methods of data collection and labeling, making it an attractive option for businesses looking to accelerate their AI and machine learning projects. The market represents a promising opportunity for organizations seeking to overcome the challenges of data scarcity and privacy concerns while maintaining data diversity and improving the efficiency of their artificial intelligence and machine learning initiatives. By leveraging this technology, technology decision-makers can drive innovation and gain a competitive edge in their respective industries.

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

  Healthcare and life sciences
  Retail and e-commerce
  Transportation and logistics
  IT and telecommunication
  BFSI and others


Type

  Agent-based modelling
  Direct modelling


Data

  Tabular Data
  Text Data
  Image & Video Data
  Others


Offering Band

  Fully Synthetic Data
  Partially Synthetic Data
  Hybrid Synthetic Data


Application

  Data Protection
  Data Sharing
  Predictive Analytics
  Natural Language Processing
  Computer Vision Algorithms
  Others


Geography

  North America

    US
    Canada
    Mexico


  Europe

    Germany
    UK
    France
    Italy


  APAC

    China
    Japan
    India


  Middle East and Africa



  South America

By End-user Insights

The healthcare and life sciences segment is estimated to witness significant growth during the forecast period. In the thriving healthcare and life sciences sector, synthetic data generation is gaining significant traction as a cost-effective and time-efficient alternative to utilizing real-world data. This market segment's rapid expansion is driven by the increasing demand for data-driven insights and the importance of safeguarding sensitive information. One noteworthy application of synthetic data generation is in the realm of computer vision, specifically with geospatial imagery and medical imaging.

For instance, in healthcare, synthetic data can be generated to replicate medical imaging, such as MRI scans and X-rays, for research and machine learning model development without compromising patient privacy. Similarly, in the field of physical security, synthetic data can be employed to enhance autonomous vehicle simulation, ensuring optimal performance and safety without the need for real-world data. By generating artificial datasets, organizations can diversify their data sources and improve the overall quality and accuracy of their machine learning models.

Get a glance at the share of various segments. Request Free Sample

The healthcare and life sciences segment was valued at USD 12.60 million in 2018 and showed a gradual increase during the forecast period.

Regional Insights

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 m

Between 2010 and 2020, more than three thousand patents were artificial intelligence patents, out of which 47 percent were from the technology sector. These patents were mostly about computer vision, and the predominant technique used was machine learning.

Credit report of School Of Computer Science And Stat contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

Snapshot img

Generative Artificial Intelligence Market Size 2025-2029

The generative AI market size is forecast to increase by USD 185.82 billion at a CAGR of 59.4% between 2024 and 2029.

This growth is propelled by soaring demand for AI-generated content, driven by large language models (LLMs) and neural networks that craft human-like text and images. Yet, challenges like insufficient quality data, limited training datasets, and algorithm efficiency hinder expansion, even as businesses leverage gen AI for automated content creation, natural language processing, and enhanced digital interfaces.

Applications span personalized marketing content using artificial intelligence, code generation for software, and synthetic media, boosting productivity gains and customer satisfaction in IT support, virtual reality, and chatbot systems. Despite these advances, ensuring data accuracy, model scalability, and computational power is vital to maximize potential. The generative AI market thrives on cutting-edge language models, deep learning, and content synthesis, but overcoming hurdles in data reliability and processing speed is key to sustaining its momentum.

What will be the Size of the Generative AI Market During the Forecast Period?

To learn more about the Gen AI market report, Request Free Sample

The generative AI market is experiencing significant growth, driven by the increasing adoption of AI-driven solutions across various industries. Natural language processing and computer vision are two primary applications of generative AI, with advancements in technologies such as generative adversarial networks, neural networks, deep learning, probabilistic modeling, iterative training techniques, recurrent neural networks, and convolutional neural networks propelling innovation. Generative AI is revolutionizing sectors like entertainment, healthcare, and artificial intelligence applications, offering new possibilities for creating lifelike simulations, videos, and virtual worlds. Standard AI systems are being replaced with advanced algorithms that can generate human-like text, patterns, and even metaverse experiences. IT professionals are in high demand as businesses seek to leverage these technologies to stay competitive. The market is expected to continue expanding, with continued investment in research and development.

Synthetic data generation and AI content creation are revolutionizing industries by enabling the creation of high-quality, scalable content for various applications. Generative adversarial networks (GANs) are at the core of deepfake technology and image enhancement, allowing for hyper-realistic image and video synthesis. AI-driven creative tools, including text-to-image models and AI art generation, enable artists and designers to leverage machine learning for innovative visuals and designs. Similarly, AI music composition, voice synthesis, and speech-to-text AI provide new avenues for content production and voice-based interfaces. Predictive modeling and data augmentation play a vital role in refining machine learning algorithms and improving model accuracy. AI-powered design tools such as generative design and procedural content creation are transforming architecture, fashion, and product development. The rise of virtual avatars and personalized AI enhances user experiences, while contextual AI and cognitive automation support seamless integration with real-time rendering and 3D model generation. Ethical AI frameworks ensure that these technologies are developed responsibly, while semantic understanding and visual storytelling further expand their creative potential.

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

The generative 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
  Services


Technology

  Transformers
  Generative adversarial networks (GANs)
  Variational autoencoder (VAE)
  Diffusion networks


Application

  Computer Vision
  NLP
  Robotics & Automation
  Content Generation
  Chatbots & Intelligent Virtual Assistants
  Predictive Analytics
  Others


End-Use

  Media & Entertainment
  BFSI
  IT & Telecommunication
  Healthcare
  Automotive & Transportation
  Gaming
  Others


Model

  Large Language Models
  Image & Video Generative Models
  Multi-modal Generative Models
  Others


Geography

  North America

    Canada
    US


  APAC

    China
    India
    Japan


  Europe

    Germany
    UK
    France
    Italy


  South America



  Middle East and Africa

By Component Insights

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

Generative Artificial Int

Data Submitted to the Canadian Association of Research Libraries which reflects the 2015 collections, services and staff of the University of Alberta Libraries.

In 2022, revenues from the global artificial intelligence market were expected to reach 433 billion U.S. dollars. The global AI market is forecast to see rapid growth in the coming years, reaching more than half a trillion U.S. dollars by 2023.

Artificial Intelligence Simply put, artificial intelligence (AI) is the ability of a computer or machine to mimic the competencies of the human mind, which often learns from previous experiences to understand and respond to language, decisions, and problems. In the case of AI, a great amount of data is often used to train AI into developing algorithms that enable these abilities. Different AI capabilities such as computer vision and conversational interfaces are embedded in many standard business processes in industries such as retail, finance, healthcare, and high tech.

AI Segments The AI market can be broken down into three segments: software, hardware, and services. The AI software segment is the largest of the three segments, bringing in the most revenue recently. The segment is comprised of AI applications, AI software platforms, and AI system infrastructure software sub-segments. Popular AI software vendors include companies such as IBM, Microsoft, SAS, and Google to name a few. The AI hardware market and the AI services market are smaller in size but have significant potential for growth in the coming years.