Global Synthetic Data Services Market Size (2023-2030)

The Global Synthetic Data Services Market was estimated to be worth USD 463.8 Million in 2022 and is anticipated to reach a value of USD 9,680.77 Million by 2030, growing at a fast CAGR of 46.2 % during the outlook period 2023-2030.

Computer-generated data, or synthetic data, is quickly replacing actual data. Computer algorithms produce synthetic data, which is not derived from actual documentation. As more sophisticated AI applications are created, businesses are finding it challenging to obtain huge amounts of high-quality datasets for ML model training. To overcome these obstacles and create extremely trustworthy ML models, synthetic data is aiding data scientists and developers. Such progress offers the market expansion in the future year significant chances. Contrarily, to train and create accurate ML models, engineers frequently need highly quantitative accurate, and diverse datasets. The price of data collecting and data labelling is decreased with the aid of synthetic data. Synthetic raw data can alleviate privacy concerns related to sensitive real-world data in addition to reducing costs. Additionally, because the developer has control over how the synthetic data is distributed, bias is reduced in comparison to real data. By integrating abnormalities that are difficult to find in reliable data, it can offer greater diversity. During the anticipated time, these advantages generate a wide range of potential for market expansion.

The advancement of data testing and sharing capabilities, both within and internationally with other government departments, academia, and other industries, is one of the major advantages that synthetic data may offer. The collaboration will be facilitated by reducing friction between services, which will ultimately help to improve services for customers. Additionally, the use of synthetic data will aid to advance data literacy and comprehension. Quick dashboards that can be created on this accurate reproduction will be beneficial. Businesses can then use this data literacy to make better decisions. Additionally, it might pave the way for increased data sharing and cross-sector collaboration, utilising the advantages of crowdsourcing innovation and collaborating with businesses and academic institutions. Given the current environment, these prospects may be extremely scarce and labour-intensive to realise, presumably fueling the market's expansion.

Global Synthetic Data Services Market Drivers:

• Development in the automotive sector and driver safety systems is bolstering growth in the Synthetic Data Services Market.

AI systems for computer vision and autonomous driving already rely heavily on developing technology. To create realistic datasets and simulated landscapes at scale without using actual roads, automobile manufacturers are turning to synthetic data, which blends techniques from the gaming and film industries (simulation, CGI) with generative neural networks (GANs, VAEs). Manufacturers might concentrate on certain items of interest by using synthetic data. Additionally, market trends for the development of synthetic data are becoming more and more crucial for manufacturers to meet the requirements of the in-cabin driver safety monitoring system without using the data from actual drivers. Synthetic data can improve driver safety without compromising privacy as privacy concerns among consumers grow.

• Increasing demand for data privacy and compliance is increasing demand in the Synthetic Data Services Market.

Organizations must manage personal data with the utmost care due to the growing significance of data privacy and compliance rules, including GDPR and CCPA. A solution is provided by synthetic data services, which enables businesses to provide accurate data while upholding privacy and legal standards. The market for synthetic data production is being driven by the rising demand for data protection and compliance. Companies are looking for ways to safeguard customer information and follow strict privacy laws. By enabling the use of artificially created data that resembles actual data while protecting privacy, synthetic data services offer a solution. It assists businesses in reducing hazards. sustain ethical and open data practices and assure compliance. Additionally, access to limited or scarce data is made possible through synthetic data production, enabling industries to progress while abiding by privacy laws and data availability restrictions. The adoption of synthetic data creation as a privacy-preserving solution for various data-intensive tasks is generally driven by the desire for data privacy and compliance.

Global Synthetic Data Services Market Challenges:

The business of creating synthetic data is still in its infancy, but it is projected to expand dramatically over the next few years. This is because synthetic data has advantages over real data, such as privacy, affordability, accuracy, and flexibility. Before the market realises its full potential, several issues, including a lack of norms, trust, and awareness, must be resolved. Creating standards for the development of synthetic data, fostering confidence in synthetic data, and raising knowledge of the advantages of synthetic data are some actions that can be taken to address these issues.

Global Synthetic Data Services Market Opportunities:

Complex neural networks called LLMs can produce text. They support systems like Google's LaMDA (conversational dialogue) and OpenAI's GPT-3 (text), and they served as inspiration for OpenAl's DALL-E and Midjourney (text-to-image). LLMs have been growing in size and sophistication by an average of 10 times a year. As a result, Modern Al is capable of producing content on par with human standards, whether it be text, visual, audio, code, data, or multimedia.

The Al sector is seeing advancements migrate to downstream activities and multi-modal models as large language models get better. These models can accept various input modalities (such as pictures, text, and audio) and generate various output modalities. A youngster reading a picture book uses both the text and the drawings to visualise the tale, which is similar to how humans think. Language model improvements are becoming increasingly the cognitive framework of real-world Al, and organisations are poised for a potential network impact.

COVID-19 Impact on Global Synthetic Data Services Market:

Pre-COVID-19 projections are expected to be higher than the present projection for 2030. Businesses around the world have been seriously impacted by the global COVID-19 outbreak. The lockdown imposed by many governments has favourably impacted the use of synthetic data-generating solutions. After COVID-19, businesses are focused on cutting-edge technology to undertake contactless operations, including artificial intelligence (AI), machine learning (ML), computing technology, and analytics across industries like BFSI, healthcare, IT, and telecom. This element also increases demand for models of synthetic data production that are AI-driven, which propels the synthetic data services market's acceptance on a global scale.

Additionally, the pandemic has created significant difficulties for businesses that are trying to execute crucial processes, report accurately with data dispersed across numerous locations, run complex systems, and effectively collaborate with partners; particularly where such processes lack the necessary infrastructure. As a result, more businesses are investing in the creation of synthetic data. Synthetic data production offers endless scalability and ongoing functional improvement, which are essential in achieving digital transformation and supporting the market's growth post-pandemic. For example, the Medicines and Healthcare Products Agency (MHRA) has announced the establishment of two novel synthetic datasets that would aid in the construction of state-of-the-art medical technology to combat the coronavirus (COVID-19) and cardiovascular disease. These datasets were created to replicate the signs, findings, and therapies seen in real patients. These types of generated datasets are useful for developing and testing machine learning and artificial intelligence (AI) algorithms in medical devices used for disease diagnosis, condition monitoring, and health improvement. Such improvement offers the market projection for synthetic data production an attractive chance.

Global Synthetic Data Services Market Recent Developments:

• In May 2023, Databricks purchased Okera, a platform for data governance with an emphasis on Al. Through the acquisition, Databricks will be able to provide more APIs, which its data governance partners can utilize to offer services to their clients.
• In January 2023, Microsoft and OpenAl signed a multi-billion dollar partnership agreement to hasten the advancement of Al technology. Through the relationship, Al will become more inclusive and democratic. Impressive outcomes from the collaboration have already been achieved, including the creation of GPT-3.
• In December 2022, AWS and Stability Al worked together to create its open-source tools and models. To construct and scale its Al models for the creation of the image, language, audio, video, and 3D material, Stability Al, a community-driven, open-source artificial intelligence (AI) firm, chose AWS as its primary cloud provider. To speed its development on open-source generative All models, Stability Al will utilize Amazon SageMaker (AWS's end-to-end machine learning service), as well as AWS's dependable computing infrastructure and storage.
• In April 2022, To create synthetic data for computer vision AI, Synthesis AI raised USD 17 million in Series A funding, bringing the total funding to over USD 24 million.
• In October 2021, Facebook revealed that it has acquired AI Reverie, a top platform for creating synthetic data that intends to assist companies in enhancing and scaling their machine learning algorithms.

SYNTHETIC DATA SERVICES MARKET REPORT COVERAGE:

Global Synthetic Data Services Market Segmentation:

Global Synthetic Data Services Market Segmentation: By Deployment Mode

• On-Premise
• Cloud

In 2022, the on-premise segment accounted for the greatest share of the synthetic data creation market, and it is anticipated that this pattern will hold throughout the forecast period. This is explained by the many benefits that an on-premise deployment provides, including a high level of data protection and safety. Industries like on-premise deployment models because they offer greater data security and are less likely to experience data breaches than cloud-based deployment models, which further increases demand for on-premise deployment models within the sectors. However, during the projected period, the cloud segment is anticipated to increase at the greatest rate. The market is expanding as a result of an increase in the usage of cloud-based synthetic data production due to its lower cost and simpler maintenance. Additionally, it offers scalability & flexibility to improve company processes, which accelerates the growth of the synthetic data services market.

Global Synthetic Data Services Market Segmentation: By Data Type

• Tabular Data
• Text Data
• Image & Video Data
• Others (Audio, Time Series, etc.)

The tabular data category had the highest revenue share in 2022—more than 38%. Stakeholders anticipate that the tabular data sector will account for a sizeable portion of the global market, mostly due to researchers' strong demand.

Users would receive data for their projects in table and time series formats, according to the researchers. Additionally, conditional tabular GAN (CTGAN) was developed in 2019 to improve the training process using mode-specific normalisation and handle data imbalance, among other things. Due to researchers' emphasis on tabular data, end-user industries will probably rely on artificial data to secure their customers' personal information.

Based on soaring demand to strengthen the database, the image and video data segment is predicted to significantly contribute to the market share for synthetic data services. Furthermore, both developing and developed nations have started to use synthetic media as a direct replacement for the original data. Synthetic images and films, in particular, have become quite popular in the car industry.

Global Synthetic Data Services Market Segmentation: By Modelling Type

• Direct Modelling
• Agent-based Modelling

The agent-based modelling market accounted for the biggest revenue share in 2022 at 60%. A physical representation of real-world data can be created using agent-based modelling (ABM), and that model can then be used to replicate the data. In the financial industry, agent-based modelling has recently surpassed conventional models in popularity.

It has grown to be very popular for use as a source of business transactions for creating and testing fraud detection systems. Participants in the industry can rely on ABMs to take advantage of network modelling for various types of networks. ABMs are now widely used to simulate customer interactions, innovations, vehicles, and traffic patterns.

Due to their strong penetration in traffic control and management, market players have given ABMs priority. For instance, agent-based modelling has gained more popularity as a way to highlight ridesharing or route selection and develop new systems and methods. Additionally, psychological traits have made progress to support agent models. Sharing mobility research has also given agent-based simulation a boost for information-transfer procedures and provided useful feedback.

Global Synthetic Data Services Market Segmentation: By Offering

• Fully Synthetic Data
• Partially Synthetic Data
• Hybrid Synthetic Data

With the biggest revenue share of 35% in the synthetic data services market in 2022, the fully synthetic data segment was the market leader. During the forecast period, the hybrid synthetic data segment is expected to register a significant CAGR. The higher growth trend is mostly related to the preservation of privacy with enhanced value as it provides the benefits of fully and partially synthetic data. While hybrid synthetic data will increasingly be used across all end-use industries, the potential need for more processing time may limit market expansion.

The participants predict that the fully synthetic data segment will greatly increase the market value globally. In both emerging and developed countries, there is a growing demand for enhanced privacy, which contributes to the upward growth trajectory. Leading businesses have increased their investments in fully synthetic to increase their market share in the automobile sector.

Global Synthetic Data Services Market Segmentation: By Application

• Data Protection
• Data Sharing
• Predictive Analytics
• Natural Language Processing
• Computer Vision Algorithms
• Others

In 2022, the natural language processing market had a significant revenue share of over 26%. As it supports the launch of new languages, the usage of synthetic data in natural language processing has increased exponentially.

To expedite and finish the training data for its natural language understanding (NLU) systems, the corporation has expanded its emphasis on synthetic data. Recent developments in NLP will accelerate the need for synthetic data to enable businesses to act more quickly.

A viable application area for predictive analytics has also emerged, supported by strong demand from the BFSI industry. Predictive analytics for fraud detection is anticipated to be used by banks and the financial sector. The business creates synthetic financial data that mimics credit card transactions using generative adversarial networks to detect credit card fraud. Additionally, the insurance industry has demonstrated success in using predictive analytics to increase sales and reduce underwriting costs. To better understand consumer wants and requests and increase customer satisfaction, end users are likely to use artificial data in predictive analytics.

Global Synthetic Data Services Market Segmentation: By End Use

• BFSI
• Healthcare & Life Sciences
• Transportation & Logistics
• IT & Telecommunication
• Retail and E-commerce
• Manufacturing
• Consumer Electronics
• Others

The segment for healthcare and life sciences had the biggest revenue share in 2022 with 22%. Healthcare and life science are expected to exhibit strong demand for synthetic data that protects privacy. Patient privacy, legal frameworks, distinct data sources, and technologies for artificial data production have all acquired considerable traction in the face of hazards associated with data breaches.

For example, Anthem Inc. said in May 2022 that it will join Alphabet Inc.'s Google Cloud to produce 1.5 to 2 petabytes of synthetic data for improved fraud detection and customised services. Leading firms will continue to benefit from the high potential of synthetic data in healthcare for increased agility and privacy regulations.

The retail and e-commerce industries have benefited from the use of artificial data to train AI models and hasten data exchange both inside and outside the firm. Synthetic data is used by brands and retailers to speed up data exchange with suppliers and advance advertising and promotions.

Additionally, retailers profit from IT companies' use of fictitious company data for analytics and training. Artificial data has recently acquired a popularity for effective inventory and warehouse management. The e-commerce players might further encourage investment in synthetic data-generating tools with an increase in online sales.

Global Synthetic Data Services Market Segmentation: By Region

• North America
• Europe
• Asia Pacific
• Middle East and Africa
• South America

In 2022, North America had the largest revenue share (35%). Due to end-use sectors' growing interest in fraud detection, NLP, and image data, the United States and Canada have emerged as profitable locations. Several businesses have increased their investments in synthetic data, including J.P. Morgan, American Express, Amazon, and Google's Waymo.

For example, Amazon launched Amazon SageMaker Ground Truth in June 2022 to create labelled synthetic image data. These market participants will exhibit a preference for artificial data to train machine learning, payment data to detect fraud, and anti-money laundering behaviours. The prediction for the North American synthetic data production business also predicts success for computer vision's growing presence. Physical security, geospatial imagery, and manufacturing have all gained significant interest.

Additionally, simulation data across the region has benefited from the rising popularity of autonomous vehicles. With the help of simulation data, autonomous vehicles have advanced, allowing businesses to test edge cases and reduce the likelihood of accidents. For demanding training requirements and the development of self-driving cars, advanced economies like the U.S. has strengthened the autonomous simulation platform.

Global Synthetic Data Services Market Key Players:

1. Mostly AI
2. Synthesis AI
3. Statice
4. YData
5. Ekobit d.o.o.
6. Hazy
7. Kinetic Vision, Inc.
8. Kymera-labs
9. MDClone
10. Neuromation
11. TwentyBN
12. DataGen Technologies
13. Informatica Test Data Management