CHICAGO, Jan. 17, 2024 /PRNewswire/ -- The market for AI data management will grow as augmented analytics becomes more widely used, natural language processing advances, and ethical and responsible data practices are prioritised. Anticipations encompass the emergence of AI-powered automation, improved predictive analytics, and the merging of AI and DataOps, forming a terrain in which AI-powered data governance, personalised data experiences, and continuous learning models serve as essential components in propelling productivity and creativity.
The AI Data Management Market is estimated to grow from USD 25.1 billion in 2023 to USD 70.2 billion by 2028, at a CAGR of 22.8% during the forecast period, according to a new report by MarketsandMarkets. AI data management refers to artificial intelligence that leverages a variety of data types, such as video, audio, speech, images, text, and conventional numerical datasets, to enhance its ability to make more precise predictions, draw insightful conclusions, and provide accurate solutions to real-world challenges. This approach involves training AI systems to synthesize and process diverse data sources concurrently, enabling them to better understand content and context, a significant improvement compared to earlier AI models.
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Scope of the Report
Report Metrics | Details |
Market size available for years | 2017-2028 |
Base year considered | 2022 |
Forecast period | 2023-2028 |
Forecast units | USD Billion |
Segments Covered | Offering by Type (Platform, Software tools & Services) Offering by Deployment mode (Cloud, On-premises), Data Type (Audio, Speech & Voice, Image, Text, Video), Technology (ML, NLP, Computer Vision, Context Awareness), Application, Vertical, and Region. |
Geographies covered | North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
Companies covered | 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). |
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.
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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.
The healthcare and life sciences vertical is projected to grow at the highest CAGR during the forecast period.
AI data management in healthcare & life sciences sector involves the comprehensive handling of vast amounts of patient data, genomic information, clinical trial results, and other healthcare-related data. Through AI-powered analytics and machine learning algorithms, healthcare organizations can derive actionable insights from complex datasets. This enables personalized medicine, predictive analytics for disease diagnosis and prognosis, and the identification of potential drug candidates. In addition to advancing clinical decision-making, AI data management enhances operational efficiency by streamlining administrative processes, optimizing resource allocation, and improving patient outcomes through data-driven interventions.
Europe is expected to hold the second-largest market size for the estimated year.
Europe has been actively engaged in the evolution and adoption of AI data management solutions, showcasing significant advancements and a growing market landscape. Countries within Europe, including the UK, Germany, France, and the Nordic countries, have been investing in AI research and development, fostering innovation in data-driven technologies. The region emphasizes data privacy and security, leading to the development of robust regulations like GDPR (General Data Protection Regulation), which has significantly influenced how AI data management is approached, ensuring ethical and responsible data practices. Europe's collaborative approach to research and innovation fosters partnerships between academia, industry, and governments, fueling the continuous growth and innovation in AI data management solutions.
Top Key Companies in AI Data Management Market:
The major AI data management and service providers include 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). These companies have used both organic and inorganic growth strategies such as product launches, acquisitions, and partnerships to strengthen their position in the AI Data Management Market.
Recent Developments:
- In November 2023, AWS introduced a preview of an innovative Generative AI-based feature within Amazon DataZone. This capability aims to enhance data discovery, comprehension, and utilization by enriching the business data catalog.
- In November 2023, Databricks acquired Arcion, a prominent provider specializing in real-time data replication technologies. By integrating Arcion's capabilities, Databricks aims to offer native solutions facilitating the seamless replication and ingestion of data from diverse databases and SaaS applications.
- In September 2023, Oracle unveiled the Fusion Data Intelligence Platform, representing a cutting-edge data, analytics, and AI platform. This platform is tailored to assist Oracle Fusion Cloud Applications customers in achieving superior business outcomes by merging data-centric insights with intelligent decision-making and actionable steps.
- In May 2023, Microsoft unveiled Microsoft Fabric, an analytics platform designed to streamline data and analytics tools for organizations. This integrated solution merges technologies such as Azure Data Factory, Azure Synapse Analytics, and Power BI into a unified product. Fabric empowers data and business professionals to harness the full potential of their data, setting the stage for the era of AI while simplifying data-related workflows.
- In May 2023, Qlik acquired Talend, broadening its top-tier capabilities for modern enterprises to manage, process, trust, analyze, and act upon data. The synergies between Qlik and Talend solutions complement each other, strengthening various critical aspects including data quality, transformation, application connectivity, and API services.
- In March 2023, SAP introduced strategic partnerships with leading data and AI companies, including Collibra NV, Confluent Inc., Databricks Inc., and DataRobot Inc. With these partnerships, SAP aims to empower millions of users worldwide to make informed, data-driven decisions crucial to their businesses, bridging various data sources like never before.
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AI Data Management Market Advantages:
- Regular operations like data cleansing, normalisation, and classification are automated by AI in data management, increasing operational efficiency and lowering manual labour.
- By locating and fixing flaws, inconsistencies, and inaccuracies, AI algorithms can evaluate and improve data quality, guaranteeing that businesses operate with dependable and accurate data.
- By upholding standard procedures for data processing, guaranteeing regulatory compliance, and enforcing data policies, AI-based data management systems improve data governance.
- By automating dataset mapping, transformation, and merging, artificial intelligence (AI) enables the smooth integration of data from many sources and fosters a single, unified perspective of information throughout the company.
- Within massive datasets, AI algorithms help with the automatic identification of pertinent patterns, correlations, and trends, revealing important insights that would not be visible using more conventional data analysis techniques.
- Real-time data processing and analysis made possible by AI technologies enables businesses to react quickly to changing circumstances, take advantage of opportunities that don't last long, and make swift judgements.
- When used in conjunction with AI data management, natural language processing (NLP) skills can help comprehend and analyse unstructured data, including text documents, social media posts, and customer reviews, providing insightful information that can be used to make decisions.
Report Objectives
- To define, describe, and predict the AI Data Management Market by offering type (platform, software tools and services) offering by deployment mode, data type, technology, application, vertical, and region
- To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
- To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
- To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America
- To profile key players and comprehensively analyze their market rankings and core competencies
- To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the AI Data Management Market.
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