According to the new research report on "AI Data Management Market Size and Forecast (2021-2031), Global and Regional Share, Trends, and Growth Opportunity Analysis," published by The Insight Partners, the AI data management market is expected to reach US$ 114.99 billion by 2031 and register a CAGR of 22.3% from 2023 to 2031.

The BFSI is rapidly expanding worldwide; for instance, according to Invest India, the growth of new bank branches opened by state cooperative banks (SCBs) increased by 4.6% during FY 2022 in Tier 4, Tier 5, and Tier 6 centers. These new branches are utilizing digital tools to advance and boost their monetary and nonmonetary transactions. BFSIs use AI data management software to improve client experiences, expedite processes, reduce risks, and stimulate strategic decision-making. Computers analyze large-scale databases to identify fraudulent activity, improve investment strategies, and automate repetitive processes.

The number of financial transactions is growing across the globe. For instance, according to The Capgemini Research Institute's 2023 World Payments Report published on September 2023, non-cash transaction volume was recorded to be 1.3 trillion in 2023 and is expected to reach 2.3 trillion by 2027 with a yearly growth of 15%. To manage large volumes of data and financial transactions, AI data management software is widely used in the BFSI industry. BFSI uses AI data management software for predictive analytics to manage numerous repetitive tasks such as loan approvals, processing insurance claims, and customizing consumer services. Furthermore, AI data management software is used for guaranteeing data confidentiality, privacy, and correctness and navigating complex regulatory frameworks such as Anti-Money Laundering (AML) and Know Your Customer (KYC), which help organizations comply with strict rules. Additionally, the BFSI industry heavily relies on AI data management to promote innovation, enhance operational effectiveness, and preserve competitiveness in digitalization and a data-centric economy. Thus, the expansion of the BFSI industry and the rise in financial transactions boost the AI data management market.

The market in China is anticipated to expand at a significant pace during the forecast period due to growing investments in cloud technologies. According to a survey conducted by Alibaba Group, ~84% of existing cloud service users have invested in cloud technology in 2023 that supports companies to manage data pipelines efficiently and effectively, including data quality, data integration, and metadata management. Moreover, in the second half of 2023, the Asia Society Policy Institute's Center for China Analysis (CCA) sponsored a three-part webinar series on China's generative AI and AI technological landscape, AI's impact on the Chinese economy, and AI's position in the US-China competition. The webinar highlighted China's focus is increasingly shifting to the hardware and infrastructure required for AI advancement. The development of AI infrastructure allows businesses to faster training of complex models, management of larger datasets, and efficient model deployment.

Key Findings of Study:

Based on deployment, the AI data management market is segmented on-premise and cloud. Cloud-based solutions are becoming essential to achieve scalability and efficient deployment of AI applications. Businesses are focused on investing in cloud technology to streamline their operations and secure data from cyber threats. For instance, according to Infosys Limited, 67% of companies will increase their cloud spending in 2023, and 80% are planning to raise their cloud spending to manage and protect their customer's data from theft effectively. Also, by utilizing cloud infrastructure, businesses can effectively store and manage enormous volumes of data, supplying the processing power needed for the implementation of intricate AI algorithms. AI data management cloud services are flexible, allowing companies to adjust their resource levels in response to demand while minimizing expenses. Additionally, cloud platforms facilitate easy team collaboration by offering an environment for data sharing, analysis, and storage that is accessible and cooperative. The cloud sector helps businesses stay relevant in the developing field of AI data management by facilitating the integration of cutting-edge technology and improving the agility of AI implementation.




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