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AI Data Management Market Growth, Opportunities Business Scenario, Share, Growth Size, Scope, Key Segments and Forecast to 2028

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AI Data Management Market Growth, Opportunities Business Scenario, Share, Growth Size, Scope, Key Segments and Forecast to 2028

January 22
15:05 2024
AI Data Management Market Growth, Opportunities Business Scenario, Share, Growth Size, Scope, Key Segments and Forecast to 2028
Microsoft (US), AWS (US), IBM (US), Google (US), Oracle (US), Salesforce (US), SAP (Germany), SAS Institute (US), HPE (US), Snowflake (US), Teradata (US), Informatica (US), Databricks (US), TIBCO Software (US), Qlik (US), Collibra (US), Dataiku (US), Alteryx (US), Datamatics Business Solutions (US), Accenture (Ireland), Ataccama (Canada), Reltio (US)..
AI Data Management Market by Offering (Platform, Software tools, and Services), Data Type, Technology (ML, NLP, Computer Vision, Context Awareness), Application (Process Automation, Data Augmentation), Vertical and Region – Global Forecast to 2028

The AI Data Management Market is expected to grow from USD 25.1 billion in 2023 to USD 70.2 billion in 2028, at a CAGR of 22.8%  during the forecast period. The AI data management market is driven by various factors, such as the AI-powered data fabric solutions and automated integration fueling the market expansion, the evolution in cloud technology and the rapid advancements in AI and ML to propel the adoption of transformative data management solutions.

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Services segment to account for higher CAGR during the forecast period.

The services segment within the AI data management market encompasses a wide array of such as consulting services providing strategic guidance and advisory support, system integration & implementation to ensure smooth incorporation of AI solutions into existing frameworks, and support & maintenance for ongoing assistance and issue resolution. Data migration services aid in the seamless transfer of information to AI-enabled platforms, while AI change management and adoption services focus on organizational readiness and user adoption. Moreover, AI platform administration services are instrumental in managing and optimizing the functionality of AI systems, ensuring they operate at their full potential. This comprehensive suite of services forms the backbone for enterprises aiming to leverage AI for data management, enabling them to harness its transformative power effectively.

Cloud segment is expected to hold the largest market size for the year 2023.

Cloud-based solutions have become integral to the effective deployment and scalability of AI applications. Leveraging cloud infrastructure allows organizations to store and process vast amounts of data efficiently, providing the computational power required for complex AI algorithms. Cloud services in AI data management offer flexibility, enabling businesses to scale resources up or down based on demand, optimizing costs. Moreover, cloud platforms provide a collaborative and accessible environment for data storage, sharing, and analysis, fostering seamless collaboration among teams. The Cloud segment not only enhances the agility of AI implementation but also facilitates the integration of cutting-edge technologies, enabling organizations to stay at the forefront of innovation in the rapidly evolving field of AI data management.

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Unique Features in the AI Data Management Market:

AI-driven data management solutions provide automatic data curation by classifying, cleaning, and organising data using machine learning algorithms to guarantee its relevance and quality.

Constructing intelligent metadata with the application of AI in cognitive data catalogues will facilitate users’ ability to find, comprehend, and use data assets inside an organisation.

Artificial intelligence (AI) is used to improve data quality by finding and fixing flaws, inconsistencies, and inaccuracies in big datasets, guaranteeing the accuracy of the data used for analytics and decision-making.

By enforcing rules, monitoring compliance, and controlling access permissions, AI enables automated data governance procedures. This lowers the need for manual intervention and increases the effectiveness of governance overall.

Algorithms driven by artificial intelligence (AI) facilitate intelligent data matching and connection between dissimilar datasets, enhancing data integration and guaranteeing a thorough and precise representation of information.

Major Highlights of the AI Data Management Market:

For automated data curation, cleaning, and quality assurance—that is, making sure datasets are correct, consistent, and prepared for advanced analytics—AI-driven solutions are being utilised more and more.

AI is essential to more effective and safe data management because it automates data governance procedures, enforces regulations, guarantees compliance, and manages access controls.

AI-driven dynamic data masking has emerged as a crucial function, giving businesses the capacity to automatically hide sensitive data according to contextual guidelines, improving data security and privacy.

Intelligent artificial intelligence (AI) is used by sophisticated master data management systems to adjust and learn from data changes, automatically updating master records to preserve correctness and consistency throughout the enterprise.

By enabling natural language commands and inquiries, the integration of NLP in AI data management solutions has simplified user engagement with data and enhanced user interactivity.

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Top Key Companies the AI Data Management Market:

Key players operating in the AI data management market across the globe are Microsoft Corporation (Microsoft), IBM Corporation (IBM),  Amazon Web Services, Inc. (AWS), Alphabet Inc. (Google), Oracle Corporation (Oracle), Salesforce, Inc. (Salesforce), SAP SE (SAP), SAS Institute Inc. (SAS Institute), Hewlett Packard Enterprise (HPE), Snowflake Inc. (Snowflake), Teradata Corporation (Teradata),  Informatica Inc. (Informatica),  Databricks, Inc. (Databricks), TIBCO Software Inc. (TIBCO Software), QlikTech International AB (Qlik),  Collibra (Collibra), Dataiku (Dataiku), Alteryx (Alteryx), Datamatics Business Solutions Ltd. (DBSL) (Datamatics Business Solutions), Accenture (Accenture), Ataccama Corporation(Ataccama),  Reltio (Reltio), Tamr, Inc. (Tamr, Inc.), ThoughtSpot, Inc. (ThoughtSpot), AtScale (AtScale), Alation, Inc. (Alation),  Clarifai, Inc. (Clarifai), DataDirect Networks, Inc. (DDN Storage), Dataloop Ltd. (Dataloop AI), Astera Software (Astera). These companies employ various approaches, both organic and inorganic, including introducing new products, forming strategic partnerships and collaborations, and engaging in mergers and acquisitions, to expand their presence and offerings within the AI data management market.

IBM offers a comprehensive suite of solutions and services that leverage artificial intelligence and advanced analytics. With offerings like IBM Cloud Pak for Data, the company provides a modular and integrated platform for data analysis, organization, and management. IBM’s expertise extends to master data management, where solutions like IBM InfoSphere Master Data Management empower organizations to maintain a unified and accurate view of critical data entities. The company’s commitment to AI-driven data management is further exemplified by products such as IBM Knowledge Catalog, which facilitates intelligent, self-service discovery of data and models. IBM’s strategic initiatives, such as acquisitions and collaborations, underscore its dedication to staying at the forefront of the rapidly evolving AI data management landscape. As organizations increasingly recognize the importance of harnessing the power of data, IBM continues to play a pivotal role in providing innovative solutions to address the complex challenges of data governance, quality, and analytics in the AI era.

Oracle is a cloud technology company that provides organizations around the world with computing infrastructure and software to help innovate, tap efficiencies and become more effective. With a strong foundation in database management systems and enterprise software, Oracle has strategically integrated AI capabilities into its offerings to help businesses unlock the potential of advanced analytics and NLP.  The company has created the world’s first and only autonomous database to help secure and organize customers’ data. Oracle’s cloud infrastructure (OCI) provides AI-powered services and tools for data science, image recognition, chatbots, and language translation. OCI offers higher security, performance, and cost savings. It is designed so businesses can move workloads easily from on-premises systems to the cloud and between on-premises and cloud and other clouds. Oracle Cloud applications provide business leaders with modern applications that help innovate, attain sustainable growth, and become more resilient. With a focus on empowering businesses with advanced analytics, automation, and intelligent decision-making, Oracle aims to leverage its extensive software portfolio and AI technologies to drive innovation and provide value across industries in the market.

Informatica, an Enterprise Cloud Data Management leader, focuses on unlocking the potential of vital assets through data and AI. Pioneering a novel software category, the Informatica Intelligent Data Management Cloud (IDMC), the company offers an end-to-end data management platform fueled by CLAIRE AI. This platform seamlessly connects, orchestrates, and harmonizes data across diverse multi-cloud or hybrid systems. Informatica democratizes access to data, empowering enterprises to revamp and propel their business strategies. With a global presence spanning over 100 countries, Informatica caters to a diverse clientele, including 85 of the Fortune 100 companies. This widespread trust signifies the company’s pivotal role in driving data-centric digital transformations for some of the world’s leading organizations. Informatica’s product offerings encompass a comprehensive suite of data management solutions within the Intelligent Data Management Cloud. The platform facilitates data integration, governance, and analytics, underpinned by AI-driven insights.

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