AI Training Dataset Market (By Type: Text, Audio, Image/Video; By Vertical: IT, Government, Automotive, Healthcare, Retail & E-commerce, BFSI, Others) - Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2023-2032

The global AI training dataset market size was exhibited at USD 2.19 billion in 2022 and is projected to hit around USD 10.37 billion by 2032, growing at a CAGR of 16.83% during the forecast period 2023 to 2032.

Key Pointers:

• North America generated more than 41% of the revenue share in 2022.
• By type, the text segment captured a maximum revenue share on around 31.80% in 2022.
• By vertical, the IT segment led the market and generated more than 35% of the revenue share in 2022.

AI Training Dataset Market Report Scope

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.

North America caters to a market share of 41% 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.

Some of the prominent players in the AI Training Dataset Market include:

• Google, LLC (Kaggle)
• Deep Vision Data
• Cogito Tech LLC
• Appen Limited
• Samasource Inc.
• Lionbridge Technologies, Inc.
• Microsoft Corporation
• Alegion
• Amazon Web Services, Inc.
• Scale AI Inc.

Segments Covered in the Report

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 2018 to 2032. For this study, Nova one advisor, Inc. has segmented the global AI Training Dataset market.

By Type

• Text
• Audio
• Image/Video

By Vertical

• IT
• Government
• Automotive
• Healthcare
• Retail & E-commerce
• BFSI
• Others

By Region

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East & Africa (MEA)