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

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 global AI data management market is valued at USD 25.1 billion in 2023 and is estimated to reach USD 70.2 billion by 2028, registering a CAGR of 22.8% during the forecast period. The advent and widespread adoption of cloud computing have redefined the way organizations store, process, and access data. Cloud technologies provide a scalable and flexible foundation, enabling businesses to efficiently manage their ever-growing volumes of data without the constraints of traditional on-premises infrastructure. The shift towards cloud-based platforms is instrumental in driving the demand for AI data management solutions. Cloud environments offer the agility required to adapt to dynamic business needs, allowing organizations to scale their data management capabilities seamlessly. AI-driven data management tools designed for the cloud are inherently more scalable, enabling businesses to handle diverse datasets and increasing workloads effectively. This scalability is particularly crucial as the sheer volume and variety of data continue to expand exponentially.

“By offering, the platform segment is projected to hold the largest market size during the forecast period.”

Platforms in AI data management serve as comprehensive ecosystems that facilitate the collection, storage, processing, analysis, and utilization of data using artificial intelligence technologies. These platforms integrate various tools, algorithms, and functionalities that enable organizations to manage their data efficiently and derive actionable insights. They often feature components for data ingestion, cleansing, and transformation, along with AI-driven analytics and visualization tools that help in extracting valuable patterns and trends from complex datasets.

“By data type, Text Data segment is registered to grow at the highest CAGR during the forecast period.”

AI data management for text data involves the structured organization, analysis, and utilization of unstructured textual information using artificial intelligence techniques. Text data presents unique challenges due to its unstructured nature, varying formats, and nuances in language. AI-based natural language processing (NLP) and text analytics are pivotal in this domain, allowing systems to comprehend, categorize, extract insights, and derive meaning from vast volumes of text. Techniques like sentiment analysis, named entity recognition, topic modeling, and language translation enable the extraction of valuable information, sentiment trends, and contextual understanding from text data. AI-driven text data management finds applications in customer feedback analysis, content categorization, document summarization, chatbots, and information retrieval systems, revolutionizing how organizations harness the wealth of unstructured textual information to make informed decisions and enhance user experiences.

“Asia Pacific is projected to witness the highest CAGR during the forecast period.”

Asia Pacific region has witnessed remarkable growth and evolution in AI data management. With a surge in technological advancements, increased digitalization, and a burgeoning tech ecosystem, countries within the APAC region have been actively embracing AI-driven data management solutions. Countries like China, India, Japan, South Korea, and Singapore have emerged as key players in advancing AI technologies for data management. China, for instance, has heavily invested in AI research and development, fostering innovation in data-driven technologies. India, known for its IT expertise, has been rapidly adopting AI in various sectors, especially in data-intensive industries like finance, healthcare, and e-commerce. Japan and South Korea have been focusing on leveraging AI for precision manufacturing and robotics, while Singapore has been actively promoting itself as a hub for AI development and deployment in the region. The diverse economies and industries across the APAC region have driven a growing demand for AI data management solutions.

Breakdown of primaries

In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the AI data management market.

By Company: Tier I: 35%, Tier II: 45%, and Tier III: 20%

By Designation: C-Level Executives: 35%, Directors: 25%, and Others: 40%

By Region: North America: 45%, Europe: 20%, Asia Pacific: 30%, RoW: 5%

Major vendors offering AI data management platform, software/tools and services across the globe are 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), Tamr (US), ThoughtSpot (US), AtScale (US), Alation (US), Clarifai (US), DDN Storage (US), Dataloop AI (US) Astera Software (US).

Research Coverage

The market study covers AI data management across segments. It aims at estimating the market size and the growth potential across different segments, such as offering by type, offering by deployment mode, data type, application, technology, vertical, and region. It includes an in-depth competitive analysis of the key players in the market, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.

Key Benefits of Buying the Report

The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall market for AI data management and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

Analysis of key drivers (AI-powered data fabric solutions and automated integration fueling market expansion, the evolution in cloud technology to drive the AI Data Management market growth, Rapid advancements in AI and ML to propel the adoption of transformative data management solutions), restraints (Issues related to data availability and quality and susceptibility to bias and inaccuracies), opportunities (Automated data cleaning to revolutionize data preparation for better insights, enhanced predictive analytics to empower businesses to anticipate future trends, personalized and adaptive systems to emerge as a significant opportunity in the market), and challenges (Training AI on large and diverse datasets to enhance data quality poses market challenges, acquiring skilled AI experts in data management to challenge the market, limitations in bridging the educational gap for a skilled workforce) influencing the growth of the AI data management market

Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI data management market.

Market Development: Comprehensive information about lucrative markets – the report analyses the AI data management market across varied regions.

Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in AI data management market strategies; the report also helps stakeholders understand the pulse of the AI data management market and provides them with information on key market drivers, restraints, challenges, and opportunities.

Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players such as Microsoft (US), IBM (US), AWS (US), Google (US), Oracle (US) among others in the AI data management market.