AI Training Dataset Market Size, Share and Trends Analysis Report, By Type (Text, Image/Video, Audio), By Vertical (IT, Automotive, Government, Healthcare, BFSI), By Regions, And Segment Forecasts, 2023 - 2030

Report Overview

The global AI training dataset market was valued at USD 1.73 billion in 2022 and is anticipated to expand at a CAGR of 22.1% from 2023 to 2030. AI is gaining significant importance in various industrial applications such as manufacturing, IT, BFSI, retail & e-commerce, and healthcare. The growing demand for application-specific training data is also opening opportunities for new entrants. Artificial Intelligence (AI) is becoming vital to big data as the technology allows the extraction of high-level and complex abstractions using a hierarchical learning process leading to the need for mining and extracting meaningful patterns from voluminous data.

AI enables machines to learn from experience, perform human-like tasks, and adjust to new inputs. These machines are trained to process massive data and determine patterns to accomplish a specific task. In order to train these machines, certain datasets are required. Hence, the demand for AI training datasets is increasing to cater to this requirement.

The working of machines entirely depends on the dataset provided. Thus, it becomes essential to provide high-quality datasets for training. This high-quality dataset enhances the performance of AI. It also helps in reducing the time required to prepare data and increases the accuracy of predictions. Thus, vendors in the market are also focusing on acquiring companies that can help them to enhance the quality of data. For instance, In March 2020, Appen Limited, a specialized dataset provider, announced the acquisition of Figure Eight Inc., a provider of the machine learning platform. The latter company creates high-quality data by transforming unlabeled data with the help of automated tools. This acquisition will help the former company to increase the creation speed of a high-quality dataset. It will also help in enhancing the quality of data.

Technological advancement and Innovation in AI is augmenting the market growth of AI training dataset. For instance, one of the prominent technological innovations is ChatGPT by Open AI, which has the ability to reduce the time and resources required to manually construct huge datasets. ChatGPT can significantly reduce the time and resources needed to create a large dataset for training an NLP model. ChatGPT can produce human-like writing that can be utilized as training data for NLP applications because it is a sizable, unsupervised language model that was trained using GPT-3 technology. This makes it possible for it to rapidly and simply construct a vast and diverse dataset without the need for manual curation or the knowledge needed to create a dataset that includes a wide range of scenarios and situations.

Type Insights

The text segment caters to the market share of 31.2% in 2022. This is due to the high use of text datasets in the IT sector for various automation processes such as speech recognition, text classification, caption generation, and others. The audio segment is expected to cater to a moderate share due to the availability of a wide range of audio datasets. These include music datasets, speech datasets, speech commands datasets, Multimodal Emotion Lines Dataset (MELD), environmental audio datasets, and many others.

The image/video type segment is expected to cater to the highest CAGR in the forecast period. This is due to the rising focus of key players to launch new datasets with a rising number of applications. For instance, In May 2020, Google LLC, a multinational technology company, announced the launch of a new AI training dataset named Google-Landmarks-v2 that contains millions of images and thousands of landmarks. The company also launched two challenges on Kaggle, landmark retrieval 2020 and namely landmark recognition 2020. These datasets were launched for image retrieval and instance recognition and to train better and more robust systems.

Vertical Insights

The IT segment caters to a market share of 32.8% in 2022. Based on vertical, the market is segmented into it, automotive, government, healthcare, BFSI, retail & e-commerce, and others. AI in healthcare offers various opportunities in therapy areas such as lifestyle and wellness management, diagnostics, virtual assistants, and wearables. Apart from this, AI finds application in a voice-enabled symptom checker and improves organizational workflow. All these applications require an extensive dataset to provide accurate results. Thus, the use of datasets will rise thereby leading to a high CAGR in the forecast period.  

Various technology companies in the market are using machine learning technology to deliver enhanced user experience and develop innovative products. To be efficient, machine learning technology requires high-quality training data to make sure that ML algorithms are continuously optimized. Apart from this, high-quality datasets help IT companies to enhance various solutions such as computer vision, crowdsourcing, data analytics, virtual assistants, and others. Such factors are contributing to the high usage of training datasets in the sector. For instance, In June 2021 Amazon released a large scaled dataset called Amazon Berkeley Objects to help enable new efficient AI models for image-based shopping.

Regional Insights

North America caters to a market share of 37.2% in 2022. Vendors in the North American market are focusing on releasing new datasets to accelerate the adoption of artificial intelligence technology in emerging sectors in North America. For instance, Waymo LLC, a Google LLC company, released a new dataset for autonomous vehicles in September 2020. This dataset comprises sensor data that has been collected from camera sensors and LiDAR under various driving conditions such as cyclists, pedestrians, signage, and others. Such developments are driving the adoption of datasets in the market, thereby catering to a high share of the market. 

The adoption rate of emerging technologies is continuously growing as business organizations in India are strategizing to transform their businesses. Also, various key players are focusing on expanding their presence in the Asia Pacific. For instance, in July 2020, Microsoft launched a dataset called Indoor Location Dataset to collect various information such as the geomagnetic field, indoor signature of wi-fi, etc. in buildings located in Chinese cities. These datasets are supposed to help in the research and development of navigation, indoor spaces, and localization. Along with Microsoft, various other leading players are expanding their presence in this region. These factors are anticipated to boost dataset usage in the region, thereby leading to a high growth rate in the projected period. The European market is anticipated to grow moderately with a high share in the market.

Key Companies & Market Share Insights

The industry is perceiving growing market consolidations through strategic initiatives such as mergers, collaborations, and acquisitions. Key market participants are also focusing on launching new datasets. For instance, In January 2021, Vector Space AI, a datasets provider, entered into a collaboration with Elasticsearch B.V., a search company. The former company will be providing AI datasets to its users that are built in collaboration with the latter company. Vectorspace AI launched datasets that will power AI, ML, and data engineering.

Similarly, Comet ML Inc. has developed a platform for machine learning that assists data scientists to keep track, contrasting, deriving meaning from, and optimizing experiments and models over the model's full lifecycle, from training to production. Data scientists can register code changes, datasets, experimentation models, and history for experiment tracking. Some prominent players in the global AI training dataset market include:

• Google, LLC (Kaggle)

• Appen Limited

• Cogito Tech LLC

• Lionbridge Technologies, Inc.

• Amazon Web Services, Inc.

• Microsoft Corporation

• Scale AI Inc.

• Samasource Inc.

• Alegion

• Deep Vision Data

AI Training Dataset Report Scope

Global AI Training Dataset Market Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2017 to 2030. For this study, Grand View Research has segmented the global AI training dataset market report based on type, vertical, and region.

• Type Outlook (Revenue, USD Million, 2017 - 2030)

  • Text

  • Image/Video

  • Audio

• Vertical Outlook (Revenue, USD Million, 2017 - 2030)

  • IT

  • Automotive

  • Government

  • Healthcare

  • BFSI

  • Retail & E-commerce

  • Others

• Regional Outlook (Revenue, USD Million, 2017 - 2030)

  • North America

    • U.S.

    • Canada

    • Mexico

  • Europe

    • Germany

    • U.K.

    • France

  • Asia Pacific

    • China

    • Japan

    • India

  • South America

    • Brazil

  • Middle East and Africa