The Artificial Intelligence (AI) in Synthetic Data Market is expected to grow to $9.35 billion by 2030

The Business Research Company’s Artificial Intelligence (AI) in Synthetic Data Global Market Report 2026 – Market Size, Trends, And Forecast 2026-2035

LONDON, GREATER LONDON, UNITED KINGDOM, October 26, 2026 /EINPresswire.com/ — The artificial intelligence (AI) in synthetic data market is on track for remarkable growth, driven by advancements in AI technologies and increasing demand for data solutions that protect privacy while enabling innovation. As AI becomes integral to numerous industries, synthetic data is emerging as a critical component for safer, more efficient machine learning and AI model development. Let’s explore the market’s size, key players, segments, growth drivers, and future trends shaping this evolving landscape.

Forecasting the Artificial Intelligence in Synthetic Data Market Size and Growth
The AI in synthetic data market is expected to exceed $9 billion by 2030. Positioned within the much larger Information Technology sector, which is projected to be valued at $13,788 billion by the same year, the synthetic data market will represent roughly 0.1% of the overall IT industry. This highlights its emerging yet significant role in the broader tech ecosystem.

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North America’s Position as the Leading Region in AI Synthetic Data by 2030
By 2030, North America is anticipated to dominate the AI in synthetic data market, reaching a valuation of $3.2 billion. The market is forecasted to expand substantially from $0.7 billion in 2025, supported by an impressive compound annual growth rate (CAGR) of 36%. This rapid growth is driven by widespread adoption of generative AI technologies by enterprises, growing investments in AI infrastructure and cloud computing, heightened need for privacy-protecting datasets in machine learning, and the presence of top-tier AI research centers and companies. Additionally, synthetic data use is increasingly prominent in regulated sectors such as healthcare, finance, and defense.

United States as the Largest National Market Player in AI Synthetic Data
The USA is set to be the biggest individual country market within the global AI synthetic data space, with a projected worth of $2.8 billion in 2030. This figure represents a sharp rise from $0.6 billion in 2025, growing at a CAGR of 36%. Key growth contributors include heightened spending by enterprises on AI model development, the growing use of synthetic data to address issues like real-world data scarcity and bias, strong government and private sector support for responsible AI initiatives, widespread adoption of foundational AI models, and the need for scalable, high-quality datasets that accelerate innovation while meeting regulatory standards.

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Dominance of Software in the AI in Synthetic Data Market Segments
When divided by component, the AI synthetic data market separates into software and services. Software is expected to claim the largest share, accounting for 59% or $6 billion of the total market by 2030. This dominance is supported by the increasing use of AI-driven synthetic data generation platforms, demand for automated data creation and annotation tools, integration of synthetic data into enterprise AI workflows, ongoing improvements in generative AI algorithms to enhance data authenticity and scalability, and the growing adoption of software solutions designed for secure model training, testing, and validation across industries.

Diverse Data Type and Application Segmentation in the Market
The AI in synthetic data market is classified by data type into tabular data, image data, text data, and video data. In terms of applications, it covers areas such as data augmentation, model training and testing, data privacy and security, and fraud detection. This segmentation reflects the wide-ranging utility of synthetic data across various AI and machine learning tasks.

End-Users Driving Demand for AI Synthetic Data Solutions
Key end-user sectors benefiting from AI synthetic data include government, information technology (IT) and telecommunications, retail and e-commerce, automotive, healthcare, and banking, financial services, and insurance (BFSI). These industries rely increasingly on synthetic datasets to support AI development while navigating data privacy concerns and regulatory compliance.

Strong Annual Growth Rate Anticipated in the AI Synthetic Data Market
The market is expected to grow at a robust compound annual growth rate of 37% through 2030. This rapid expansion is fueled by several converging factors that boost generative AI adoption, enhance privacy-preserving data generation methods, and amplify the need for high-quality datasets to train AI models effectively across digital sectors.

Generative AI and Machine Learning Adoption Accelerating Market Expansion
One of the primary forces propelling market growth is the swift uptake of generative AI and machine learning technologies. The rise of large language models, computer vision systems, and autonomous AI applications is driving strong demand for scalable synthetic datasets that support ongoing model development. Organizations increasingly turn to AI-generated synthetic data to simulate complex or otherwise costly real-world scenarios, enabling faster experimentation, improved accuracy, and streamlined development cycles. This trend alone is expected to add about 1.5% to the market’s annual growth.

Increasing Importance of Privacy-Preserving Data Solutions
Another major growth driver is the escalating need for data solutions that safeguard privacy. Companies are adopting synthetic data as a secure means to share information among teams and partners without exposing sensitive or personally identifiable details. Maintaining statistical accuracy while minimizing privacy risks helps broaden the use of synthetic data, especially in highly regulated sectors. Furthermore, businesses are embedding synthetic data into their governance frameworks to promote responsible AI deployment and data management. This rising demand is projected to contribute roughly 1.0% to the yearly market growth.

Rising Demand for High-Quality Training Data as a Market Catalyst
The necessity for high-quality, well-labeled training data is also a key factor stimulating expansion. Developers of AI models require diverse and balanced datasets to improve predictive performance and reduce bias. Synthetic data generation enables the creation of focused datasets that include rare events, edge cases, and controlled environments often unattainable via traditional data collection methods. This capability supports accelerated AI deployment and more consistent testing across various scenarios, adding about 0.8% to the market’s annual growth rate.

Significant Growth Prospects in Software and Services Markets by 2030
The most promising opportunities for growth lie within the services and software segments. Together, these are expected to contribute more than $7 billion to the market by 2030. This surge will be driven by enterprises increasingly adopting synthetic data platforms, expanding AI development and deployment solutions, growing demand for scalable data generation in regulated industries, and ongoing innovation in synthetic data technologies that support advanced analytics and intelligent automation. These factors highlight synthetic data’s rising role in accelerating AI progress, improving data access, and facilitating secure digital transformation globally.

Projected Expansion of Services and Software Segments Over Five Years
Between 2025 and 2030, the services segment is forecasted to expand by $3 billion, while software is expected to grow by $4 billion. The market is characterized by a mix of global AI technology giants and specialized synthetic data platform developers. Companies are focusing on enhancing generative AI models, privacy-preserving data methods, multimodal synthetic datasets, scalable cloud-based platforms, and automated data labeling to meet evolving enterprise needs. Priorities such as data privacy compliance, improved model accuracy, bias mitigation, domain-specific dataset creation, and seamless integration with machine learning pipelines remain central to competitive differentiation.

Leading Company Driving Innovation in AI Synthetic Data Market
NVIDIA Corporation stands out as a market leader, holding a 2% share in global sales in 2025. Their portfolio, which includes AI software and accelerated computing solutions, supports extensive synthetic data generation, simulation platforms, generative AI frameworks, and GPU-accelerated computing. These capabilities facilitate high-quality dataset creation, scalable AI model development, and enterprise-level AI deployment across various industries.

Major Industry Players Shaping the AI Synthetic Data Market
Key companies in this space include NVIDIA Corporation, Mostly AI GmbH, Tonic.ai, Gretel.ai, Parallel Domain Inc., Datagen Technologies Inc., Synthesis AI Inc., Rendered.ai Inc., GenRocket Inc., Cognata Ltd., Cvedia Inc., YData Ltd., Syntho B.V., MDClone Ltd., Anyverse AI, Sky Engine Ltd., Kinetic Vision Inc., Epistemix Inc., Neurolabs Inc., Shaip Inc., Coohom Cloud Inc., Betterdata Inc., AI.Reverie, and Zumo Labs Inc. This diverse group offers a range of synthetic data generation platforms and AI technologies tailored to various industrial applications.

Market Fragmentation and Competitive Dynamics
The AI in synthetic data market remains fragmented, with the top 10 companies accounting for just 7% of total market revenue in 2025. This reflects ongoing technological innovation and evolving competition driven by advances in generative AI, growing enterprise demand for privacy-compliant datasets, expanding AI model development, and the need for scalable synthetic data platforms. Leading firms like NVIDIA Corporation, Mostly AI GmbH, Tonic.ai, Gretel.ai, Parallel Domain Inc., Datagen Technologies Inc., Synthesis AI Inc., Rendered.ai Inc., GenRocket Inc., and Cognata Ltd. maintain significant market shares through proprietary technologies, cloud deployment capabilities, and investments in data simulation. As AI adoption grows across autonomous vehicles, healthcare, finance, manufacturing, and enterprise sectors, strengthened partnerships and ecosystem expansions will further shape competitive positioning.

Raw Material Suppliers Supporting AI Synthetic Data Market Growth
Key raw material and technology suppliers include NVIDIA Corporation, Advanced Micro Devices, Intel Corporation, Amazon Web Services, Microsoft Azure, Google Cloud, Oracle Corporation, Dell Technologies, Hewlett Packard Enterprise, Super Micro Computer, Micron Technology, Samsung Electronics, SK hynix, Western Digital, Pure Storage, Broadcom, Cisco Systems, Red Hat, and Canonical. These companies provide essential hardware, cloud infrastructure, and software resources that underpin synthetic data generation and AI development.

Key Wholesalers and Distributors in the AI Synthetic Data Ecosystem
The distribution network for AI synthetic data solutions features major players such as TD SYNNEX, Ingram Micro, Arrow Electronics, Avnet, Carahsoft Technology, Exclusive Networks, Westcon-Comstor, Crayon Group, SoftwareONE, Insight Enterprises, CDW Corporation, SHI International, Softcat, Computacenter, Bechtle AG, Presidio, Bytes Technology Group, and ePlus. These companies facilitate the delivery and deployment of technologies across markets worldwide.

Leading End Users Driving Demand for Synthetic Data Technologies
Prominent end users of AI in synthetic data include Tesla, Waymo, BMW Group, Mercedes-Benz Group, Siemens, GE HealthCare, Pfizer, JPMorgan Chase, Mastercard, PayPal, Airbus, Lockheed Martin, Walmart, Amazon, Meta Platforms, OpenAI, Uber Technologies, Bosch, and Continental. Their investments and applications in autonomous systems, healthcare, finance, and retail significantly fuel market growth.

Competitive Trends Shaping the AI Synthetic Data Industry
Strategic acquisitions are playing a key role in expanding capabilities and market reach. For example, in March 2025, NVIDIA Corporation acquired Gretel, a synthetic data platform provider, enhancing its synthetic data portfolio and generative AI ecosystem. This acquisition integrates Gretel’s expertise in producing high-quality synthetic tabular, time-series, and text datasets, enabling scalable AI model development, improved data privacy, and more efficient training of large language models for enterprise applications.

Business Strategies Ensuring Market Leadership
To stay competitive, companies are focusing on adopting privacy-preserving synthetic data generation platforms, developing multimodal synthetic datasets to improve generative AI training, integrating synthetic data workflows into autonomous AI development, forming strategic partnerships to broaden synthetic data ecosystems and cloud deployments, and innovating products that advance domain-specific AI simulation and data generation. These approaches are essential for capitalizing on the expanding AI synthetic data market.

What’s new in our 2026 market reports:

• Market attractiveness scoring and analysis
• Total addressable market (TAM) analysis
• Company scoring matrix graphics and tables
• Excel dashboards
• Market hotspots infographics
• Key technologies and future trends
• Updated graphics and tables

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