Synthetic Test Data for Artificial Intelligence (AI) Global Market Report 2025

The synthetic test data for artificial intelligence (AI) market size has grown exponentially in recent years. It will grow from $1.81 billion in 2024 to $2.46 billion in 2025 at a compound annual growth rate (CAGR) of 35.7%. The growth in the historic period can be attributed to increasing regulatory pressure on personal data usage, lack of real world datasets in regulated sectors, rising complexity of AI models, and digitization supported by agile or devops workflows.

The synthetic test data for artificial intelligence (AI) market size is expected to see exponential growth in the next few years. It will grow to $8.24 billion in 2029 at a compound annual growth rate (CAGR) of 35.3%. The growth in the forecast period can be attributed to rising multi modal synthetic data generation, adoption of hybrid cloud and on premises deployment, cost efficiency and scalability, and stronger international data sovereignty. Major trends in the forecast period include adoption of AI generated synthetic data, improved privacy preserving data generation methods, integration of real-time and dynamic data simulation, enhanced data diversity and quality for model training, growth of industry specific synthetic datasets, and development of regulatory compliant synthetic data solutions.

The increasing adoption of artificial intelligence (AI) is expected to propel the growth of the synthetic test data for artificial intelligence (AI) market going forward. Artificial intelligence (AI) is the branch of computer science that enables machines to mimic human intelligence, allowing them to learn, reason, solve problems, and make decisions. The adoption of artificial intelligence (AI) is rising due to its ability to automate complex tasks and enhance decision making efficiency across industries. Artificial intelligence (AI) adoption enhances synthetic test data for AI by enabling the automated generation of realistic and diverse datasets, reducing reliance on sensitive real world data. It improves data quality and scenario coverage, accelerates model training and testing, and ensures privacy compliant, robust AI development. For instance, according to the Stanford Institute for Human Centered Artificial Intelligence (HAI), a US based research institute, in 2024, 78 percent of organizations were using AI, marking a significant increase from 55 percent in 2023. Therefore, the increasing adoption of artificial intelligence (AI) is driving the growth of the synthetic test data for artificial intelligence (AI) market.

Major companies operating in the synthetic test data for artificial intelligence (AI) market are focusing on developing advanced solutions such as end to end data generation solutions to accelerate AI model development, ensure data privacy, improve model robustness, and reduce dependency on real sensitive datasets. End to end data generation solutions are platforms that create, validate, and deploy synthetic data for AI, ensuring realistic, privacy compliant datasets without using real sensitive data. For instance, in October 2023, K2view, a US based data management and orchestration company, launched its Synthetic Data Management solution. This end to end data generation solution generates synthetic data on demand from within its data product platform, creating a private, secure data sandbox for each development team. It includes data masking and subsetting capabilities, enabling the use of realistic, compliant data for testing and development without compromising sensitive information.

In March 2025, Nvidia Corporation, a US based technology company, acquired Gretel Labs Inc. for $320 million. With this acquisition, Nvidia aims to strengthen its generative AI ecosystem and enhance its synthetic data capabilities to support the development and training of large language models and other AI applications. Gretel Labs Inc. is a US based company that provides synthetic data for AI, enabling safe model training and testing without using real sensitive data.

Major players in the synthetic test data for artificial intelligence (ai) market are Amazon.com Inc., Microsoft Corporation, Accenture plc, International Business Machines Corporation, Parallel Domain Inc., Gretel Labs Inc., DataGen Technologies Inc., Synthesis AI Limited, MDClone Ltd., OneView Data Solutions Inc., Cvedia AB, Fairgen Technologies Ltd., Mostly AI GmbH, Tonic Software Inc., Hazy Limited, YData SAS, Mirage Technologies Ltd., Zeblok Computational Inc., GenRocket Inc., and DATPROF B.V.

North America was the largest region in the synthetic test data for artificial intelligence (AI) market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in synthetic test data for artificial intelligence (AI) report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the synthetic test data for artificial intelligence (AI) market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the information technology sector, particularly in hardware manufacturing, data infrastructure, and software deployment. Higher duties on imported semiconductors, circuit boards, and networking equipment have raised production and operational costs for tech firms, cloud service providers, and data centers. Companies relying on globally sourced components for laptops, servers, and consumer electronics are facing longer lead times and increased pricing pressures. In parallel, tariffs on specialized software tools and retaliatory measures from key international markets have disrupted global IT supply chains and reduced overseas demand for U.S.-developed technologies. To navigate these challenges, the sector is accelerating investments in domestic chip fabrication, diversifying supplier bases, and adopting AI-driven automation to enhance operational resilience and cost efficiency.

The synthetic test data for artificial intelligence (AI) market research report is one of a series of new reports that provides synthetic test data for artificial intelligence (AI) market statistics, including the synthetic test data for artificial intelligence (AI) industry global market size, regional shares, competitors with the synthetic test data for artificial intelligence (AI) market share, detailed synthetic test data for artificial intelligence (AI) market segments, market trends, and opportunities, and any further data you may need to thrive in the synthetic test data for artificial intelligence (AI) industry. This synthetic test data for artificial intelligence (AI) market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

Synthetic test data for artificial intelligence (AI) refers to artificially generated datasets that imitate real world data patterns without using sensitive or proprietary information. It is produced through algorithms, simulations, or generative models to represent patterns and scenarios without revealing actual sensitive or private data. It is used to safely train, validate, and test AI models, ensuring strength and reliability.

The main components of synthetic test data for artificial intelligence (AI) are software and services. Software includes tools, platforms, and applications created to generate, manage, and validate synthetic test data for AI and machine learning. The various data types handled can be structured data, unstructured data, and semi structured data, and it is deployed through modes such as on premises and cloud. Its applications include model training, model testing and validation, data privacy and security, data augmentation, and others, while end users include sectors such as banking, financial services, and insurance (BFSI), healthcare, retail and e commerce, automotive, information technology (IT) and telecommunications, government, and others.

The synthetic test data for artificial intelligence (AI) market consists of revenues earned by entities by providing services such as data generation, data anonymization, model training support, data augmentation, scenario simulation, data validation and testing, privacy preservation, and AI model performance optimization. The market value includes the value of related goods sold by the service provider or included within the service offering. The synthetic test data for artificial intelligence (AI) market also includes sales of data generation platforms, data anonymization tools, simulation software, synthetic image and video generators, text and speech synthesis solutions, and AI model testing and validation tools. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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