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AI Training Dataset Market, by Type (Text, Audio, Image & Video), End-use Industry, and Geography - Global Forecast to 2029
Report ID: MRICT - 104716 Pages: 200 Nov-2022 Formats*: PDF Category: Information and Communications Technology Delivery: 24 to 72 Hours Download Free Sample ReportThe fast growth of this market is attributed to the rapid growth of AI and machine learning and growing applications of training datasets across diversified industry verticals. However, the lack of technological adoption in developing regions is expected to restrain the growth of this market. In addition, the need for human-machine interaction is expected to create significant growth opportunities for the players in this market. The high installation cost of AI technologies poses challenges to the growth of this market.
The outbreak of the COVID-19 pandemic negatively impacted several economies and businesses across the globe. Lockdowns imposed to contain the pandemic resulted in severe losses across several industries, including manufacturing, oil & gas, construction, automotive & transportation. At the same time, some industries, such as healthcare, retail & E-commerce, recorded high growth during the COVID-19 pandemic.
In the healthcare industry, AI tools and techniques help policymakers, and the medical community understand the COVID-19 virus and accelerate research on treatments by rapidly analyzing large volumes of research data. AI text and data mining tools can uncover the virus’s history, transmission, diagnostics, management measures, and lessons from previous epidemics. AI tools can help identify virus transmission chains and monitor broader economic impacts. AI technologies have demonstrated their potential to infer epidemiological data more rapidly than traditional health data reporting. Institutions such as Johns Hopkins University, a private research university in Baltimore, Maryland and the OECD (France) (Organization for Economic Co-operation and Development) have also made available interactive dashboards that track the virus’ spread through live news and real-time data on confirmed coronavirus cases, recoveries, and deaths.
The oil & gas, construction, automotive & transportation industries have been severely impacted due to shortages in raw materials & workforce, supply chain disruption, and restrictions on operating capacities. The survey report conducted by the National Association of Manufacturers (NAM) stated that around 78.0% of manufacturers anticipated a financial impact, and 35.5% faced supply chain disruptions due to COVID-19. These factors led manufacturing companies to deprioritize their digital transformation strategies, including the equipment of their production units with AI. Hence, several AI and automation experts have suggested increasing investments in advanced technologies, such as AI, to create remote operating capabilities, such as process automation, industrial robots, predictive maintenance & machinery inspection, and autonomous material movement to decrease worker density. Therefore, the pandemic proved to be a positive and negative turning point for the various industries that used AI for their operating functions and applications.
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Machine learning is a subset of artificial intelligence. It grants AI the ability to learn and make decisions using data. This process happens without any explicit programming in the systems. The emergence of big data is anticipated to fuel the expansion of the AI market since it necessitates the recording, storing, and analyzing of a significant amount of data.
Due to the rapid adoption of AI technology, the need for AI datasets is rising exponentially. Various end-use industries are searching for ways to define procedures to make remote work as favorable & efficient as working from the office and also focused on the need for monitoring systems and enhancing the computational models. According to an industry expert, 52% of companies accelerated their AI adoption plans because of the COVID-19 pandemic crisis, from which around 86% of companies declared that AI is becoming a “mainstream technology” at their company in 2021.
To make the technology more versatile and accurate with its assumptions and predictions, various companies are entering the market by releasing various datasets operating across different use cases to train the machine learning algorithm. Additionally, leading market players are adopting various growth strategies to expand their product offerings and global footprints and augment their market shares. For instance, in July 2021, Amazon Web Services, Inc. (U.S.) partnered with Hugging Face, Inc. (U.S.), an open-source provider of natural language processing (NLP) technologies. This partnership aimed to make it easier for enterprises to use State of Art Machine Learning models and ship cutting-edge NLP features more quicker. Following this partnership, Hugging Face would use Amazon Web Services as its Preferred Cloud Provider to provide services to its users. In September 2021, Amazon launched a new dataset of commonsense dialogue to aid research in open-domain conversation.
Such factors and developments by the major market players help are expected to support the rapid growth of AI and machine learning during the forecast period.
Image & Video Segment to Register the Highest CAGR During Forecast Period
Based on type, the global AI datasets market is segmented into text, audio, and image & video. The image & video segment is slated to register the highest CAGR during the forecast period. This segment's fast growth is attributed to the rising focus of key players to launch new datasets with a rising number of applications.
Retail & E-commerce Segment to Register the Highest CAGR During Forecast Period
Based on end-use industry, the global AI training dataset market is segmented into automotive, transport & logistics, information technology, healthcare, banking, financial services and insurance (BFSI), retail & e-commerce, and other end-use industries. The retail & e-commerce segment is slated to register the highest CAGR during the forecast period. The fast growth of this segment is attributed to AI leading to more personalized experiences for shoppers, increased efficiency for businesses, and a whole new set of dimensions for marketers.
Asia-Pacific to be the Fastest-growing Regional Market
Based on geography, the market is segmented into North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa. Asia-Pacific is slated to register the highest CAGR during the forecast period. Organizations in developing nations are significantly boosting the adoption rate of innovative technologies to modernize their enterprises. Additionally, several significant players are concentrating on growing their impact in Asia-Pacific. These factors will lead to the high deployment of AI datasets in the APAC region
Key Players
The key players operating in the AI training dataset market are Appen Limited (Australia), Google LLC (U.S.), Cogito Tech LLC (U.S.), Lionbridge Technologies, Inc. (U.S.), Microsoft Corporation (U.S.), Amazon Web Services, Inc. (U.S.), Scale AI, Inc. (U.S.), Alegion plc (Ireland), Kinetic Vision, Inc. (U.S.) Samasource Impact Sourcing, Inc. (U.S.), and Superb AI, Inc. (U.S.).
Scope of the Report:
AI Training Dataset Market, by Type
AI Training Dataset Market, by End-use Industry
AI Training Dataset Market, by Geography
Key questions answered in the report:
The global AI training dataset market is slated to register a CAGR of 24.7% to reach $9.35 billion during the forecast period 2022–2029.
In 2022, the type segment is estimated to account for the largest share of the global AI datasets market.
The growth of this market is attributed to the rapid growth of AI and machine learning and growing applications of training datasets across diversified industry verticals. The rise in the need for human-machine interaction is expected to create significant growth opportunities for the players operating in this market.
The key players operating in the AI training dataset market are Appen Limited (Australia), Google LLC (U.S.), Cogito Tech LLC (U.S.), Lionbridge Technologies, Inc. (U.S.), Microsoft Corporation (U.S.), Amazon Web Services, Inc. (U.S.), Scale AI, Inc. (U.S.), Samasource Impact Sourcing, Inc. (U.S.), Alegion plc (Ireland), Kinetic Vision, Inc. (U.S.), and Superb AI, Inc. (U.S.).
Published Date: Oct-2024
Published Date: Oct-2024
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Published Date: Jul-2024
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