Product Code: GVR-4-68040-355-0
AI Data Management Market Growth & Trends:
The global AI data management market size is expected to reach USD 104.32 billion by 2030, registering a CAGR of 22.7% from 2024 to 2030, according to a new report by Grand View Research, Inc. The increasing adoption of cloud computing services is a prominent growth factor in the market. Cloud-based data management systems offer scalability, flexibility, and affordability, making them suitable for organizations of all sizes. Cloud storage also facilitates easier access to data for geographically dispersed teams. Additionally, companies are becoming more aware of the benefits of migrating workloads, and the imperative to lower capital and operational expenses. Therefore, the surge in the adoption of cloud platforms is fueling the need for AI data management solutions.
The continuous expansion of the e-commerce sector in the Asia Pacific region is boosting the size of the AI data management market. The increasing trend of online shopping is raising consumer consciousness regarding data privacy and security, prompting the e-commerce sector to embrace AI technologies for better management of customer data. In addition, AI data management is pivotal in supporting online transactions, which is expected to drive the market in the forecast period.
Advancements in AI and machine learning (ML) technologies are a major driver for the broad-based implementation of AI-powered data management solutions. As the adoption of AI and ML tools advances, they are providing companies with increasingly potent capabilities to extract valuable insights from the massive amounts of data they produce and collect. Incorporating AI and ML into data management strategies is revolutionizing the way businesses handle, analyze, and make decisions based on data.
The proficiency of artificial intelligence (AI) and ML algorithms in automating and enhancing data management operations. These technologies are adept at sifting through and making sense of vast datasets rapidly, a task that far exceeds human capabilities, thereby streamlining efficiency in processes like data integration, purification, and categorization. AI-driven automated data management not only alleviates the workload associated with manual tasks but also sharply decreases the likelihood of mistakes, guaranteeing the precision and trustworthiness of data-centric conclusions.
AI Data Management Market Report Highlights:
- North America dominated the market in 2023, accounting for the largest global revenue share. North American companies are at the forefront of adopting new technologies. This drive to digitize operations creates vast amounts of data that need to be efficiently managed and secured. Data management solutions become crucial for organizations to extract value from this data.
- Based on deployment, the cloud segment dominated the market in 2023. Cloud-based AI data management platforms offer scalable, flexible, and cost-effective storage and processing power essential for running AI algorithms and managing the vast amount of data they require. This synergy between cloud and AI fuels the growth of cloud-based AI data management solutions.
- Based on offering, the services segment dominated the market in 2023. AI data management services encompass various offerings that leverage artificial intelligence (AI) to improve the handling of data throughout its lifecycle. These services can streamline data collection, organization, storage, analysis, and security.
- Based on data type, the text segment dominated the market in 2023. AI can personalize text content to individual users or customer segments. This allows for more targeted marketing campaigns and a more engaging user experience.
- Based on application, the imputation predictive modeling segment dominated the market in 2023. The amount of data organizations collect is constantly growing, and this data often comes from diverse sources and formats. This complexity makes it more likely for missing values to occur. Imputation predictive modeling offers a way to address these missing points and create a more complete picture from the vast amount of data.
- Based on technology, the computer vision segment dominated the market in 2023. Computer vision is being integrated into a wide range of applications across various industries, including autonomous vehicles, retail and manufacturing, and healthcare. specifically focuses on the tools and techniques for managing the vast amounts of image and video data used to train and operate computer vision models.
- Based on vertical, the healthcare & life sciences segment represented a significant market share in 2023. AI data management systems are crucial for preparing and analyzing healthcare and life science industry data to drive advancements in drug discovery, personalized medicine, and clinical research. Moreover, healthcare data is often fragmented across different institutions and systems. AI data management systems can bridge these silos, enabling better data integration and a more holistic view of a patient's health. This can improve diagnosis, treatment planning, and overall patient care.
Table of Contents
Chapter 1. Methodology and Scope
- 1.1. Market Segmentation and Scope
- 1.2. Market Definitions
- 1.3. Research Methodology
- 1.3.1. Information Procurement
- 1.3.2. Information or Data Analysis
- 1.3.3. Market Formulation & Data Visualization
- 1.3.4. Data Validation & Publishing
- 1.4. Research Scope and Assumptions
- 1.4.1. List of Data Sources
Chapter 2. Executive Summary
- 2.1. Market Outlook
- 2.2. Segment Outlook
- 2.3. Competitive Insights
Chapter 3. AI Data Management Variables, Trends, & Scope
- 3.1. Market Introduction/Lineage Outlook
- 3.2. Market Size and Growth Prospects (USD Billion)
- 3.3. Industry Value Chain Analysis
- 3.4. Market Dynamics
- 3.4.1. Market Drivers Analysis
- 3.4.1.1. Implementation of Advanced Technologies in Data Management Solutions
- 3.4.1.2. Personalization of Data Management Solutions to Enhance Business Operations
- 3.4.2. Market Restraints Analysis
- 3.4.2.1. High Cost of Implementation of AI Based Data Management Solutions
- 3.4.3. Industry Opportunities
- 3.4.4. Industry Challenges
- 3.4.5. Key Company Ranking Analysis, 2023
- 3.5. AI Data Management Market Analysis Tools
- 3.5.1. Porter's Analysis
- 3.5.1.1. Bargaining power of the suppliers
- 3.5.1.2. Bargaining power of the buyers
- 3.5.1.3. Threats of substitution
- 3.5.1.4. Threats from new entrants
- 3.5.1.5. Competitive rivalry
- 3.5.2. PESTEL Analysis
- 3.5.2.1. Political landscape
- 3.5.2.2. Economic and Social landscape
- 3.5.2.3. Technological landscape
- 3.5.2.4. Environmental landscape
- 3.5.2.5. Legal landscape
Chapter 4. AI Data Management Market: Deployment Estimates & Trend Analysis
- 4.1. Segment Dashboard
- 4.2. AI Data Management Market: Deployment Movement Analysis, USD Billion, 2023 & 2030
- 4.3. Cloud
- 4.3.1. Cloud Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 4.4. On-premises
- 4.4.1. On-premises Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
Chapter 5. AI Data Management Market: Offering Estimates & Trend Analysis
- 5.1. Segment Dashboard
- 5.2. AI Data Management Market: Offering Movement Analysis, USD Billion, 2023 & 2030
- 5.3. Platform
- 5.3.1. Platform Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 5.4. Software Tools
- 5.4.1. Software Tools Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 5.5. Services
- 5.5.1. Services Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
Chapter 6. AI Data Management Market: Data Type Estimates & Trend Analysis
- 6.1. Segment Dashboard
- 6.2. AI Data Management Market: Data Type Movement Analysis, USD Billion, 2023 & 2030
- 6.3. Audio
- 6.3.1. Audio Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 6.4. Speech & Voice
- 6.4.1. Speech & Voice Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 6.5. Image
- 6.5.1. Image Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 6.6. Text
- 6.6.1. Text Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 6.7. Video
- 6.7.1. Video Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
Chapter 7. AI Data Management Market: Application Estimates & Trend Analysis
- 7.1. Segment Dashboard
- 7.2. AI Data Management Market: Application Movement Analysis, USD Billion, 2023 & 2030
- 7.3. Data Augmentation
- 7.3.1. Data Augmentation Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 7.4. Data Anonymization & Compression
- 7.4.1. Data Anonymization & Compression Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 7.5. Exploratory Data Analysis
- 7.5.1. Exploratory Data Analysis Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 7.6. Imputation Predictive Modeling
- 7.6.1. Imputation Predictive Modeling Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 7.7. Data validation & Noise Reduction
- 7.7.1. Data validation & Noise Reduction Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 7.8. Process Automation
- 7.8.1.1. Process Automation Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 7.9. Others
- 7.9.1.1. Others Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
Chapter 8. AI Data Management Market: Technology Estimates & Trend Analysis
- 8.1. Segment Dashboard
- 8.2. AI Data Management Market: Technology Movement Analysis, USD Billion, 2023 & 2030
- 8.3. Machine Learning
- 8.3.1. Machine Learning Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 8.4. Natural Language Processing
- 8.4.1. Natural Language Processing Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 8.5. Computer Vision
- 8.5.1. Computer Vision Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 8.6. Context Awareness
- 8.6.1. Context Awareness Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
Chapter 9. AI Data Management Market: Vertical Estimates & Trend Analysis
- 9.1. Segment Dashboard
- 9.2. AI Data Management Market: Vertical Movement Analysis, USD Billion, 2023 & 2030
- 9.3. BFSI
- 9.3.1. BFSI Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 9.4. Retail & e-commerce
- 9.4.1. Retail & e-commerce Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 9.5. Government & Defense
- 9.5.1. Government & Defense Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 9.6. Healthcare & Life Sciences
- 9.6.1. Healthcare & Life Sciences Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 9.7. Manufacturing
- 9.7.1. Manufacturing Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 9.8. Energy & Utilities
- 9.8.1. Energy & Utilities Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 9.9. Media & Entertainment
- 9.9.1. Media & Entertainment Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 9.10. IT & Telecommunications
- 9.10.1. IT & Telecommunications Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 9.11. Others
- 9.11.1. Others Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Billion)
Chapter 10. AI Data Management Market: Regional Estimates & Trend Analysis
- 10.1. AI Data Management Market Share, By Region, 2023 & 2030 (USD Billion)
- 10.2. North America
- 10.2.1. North America AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.2.2. U.S.
- 10.2.2.1. U.S. AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.2.3. Canada
- 10.2.3.1. Canada AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.2.4. Mexico
- 10.2.4.1. Mexico AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.3. Europe
- 10.3.1. Europe AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.3.2. UK
- 10.3.2.1. UK AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.3.3. Germany
- 10.3.3.1. Germany AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.3.4. France
- 10.3.4.1. France AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.4. Asia Pacific
- 10.4.1. Asia Pacific AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.4.2. China
- 10.4.2.1. China AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.4.3. Japan
- 10.4.3.1. Japan AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.4.4. India
- 10.4.4.1. India AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.4.5. Australia
- 10.4.5.1. Australia AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.4.6. South Korea
- 10.4.6.1. South Korea AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.5. Latin America
- 10.5.1. Latin America AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.5.2. Brazil
- 10.5.2.1. Brazil AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.6. Middle East and Africa
- 10.6.1. Middle East and Africa AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.6.2. UAE
- 10.6.2.1. UAE AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.6.3. South Africa
- 10.6.3.1. South Africa AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
- 10.6.4. KSA
- 10.6.4.1. KSA AI Data Management Market Estimates and Forecasts, 2017 - 2030 (USD Billion)
Chapter 11. Competitive Landscape
- 11.1. Recent Developments & Impact Analysis by Key Market Participants
- 11.2. Company Categorization
- 11.3. Company Market Positioning
- 11.4. Company Market Share Analysis
- 11.5. Company Heat Map Analysis
- 11.6. Strategy Mapping
- 11.6.1. Expansion
- 11.6.2. Mergers & Acquisition
- 11.6.3. Partnerships & Collaborations
- 11.6.4. New Product Launches
- 11.6.5. Research And Development
- 11.7. Company Profiles
- 11.7.1. Accenture plc
- 11.7.1.1. Participant's Overview
- 11.7.1.2. Financial Performance
- 11.7.1.3. Product Benchmarking
- 11.7.1.4. Recent Developments
- 11.7.2. Amazon Web Services
- 11.7.2.1. Participant's Overview
- 11.7.2.2. Financial Performance
- 11.7.2.3. Product Benchmarking
- 11.7.2.4. Recent Developments
- 11.7.3. Databricks Inc.
- 11.7.3.1. Participant's Overview
- 11.7.3.2. Financial Performance
- 11.7.3.3. Product Benchmarking
- 11.7.3.4. Recent Developments
- 11.7.4. Google LLC
- 11.7.4.1. Participant's Overview
- 11.7.4.2. Financial Performance
- 11.7.4.3. Product Benchmarking
- 11.7.4.4. Recent Developments
- 11.7.5. International Business Machines Corporation
- 11.7.5.1. Participant's Overview
- 11.7.5.2. Financial Performance
- 11.7.5.3. Product Benchmarking
- 11.7.5.4. Recent Developments
- 11.7.6. Microsoft Corporation
- 11.7.6.1. Participant's Overview
- 11.7.6.2. Financial Performance
- 11.7.6.3. Product Benchmarking
- 11.7.6.4. Recent Developments
- 11.7.7. Oracle Corporation
- 11.7.7.1. Participant's Overview
- 11.7.7.2. Financial Performance
- 11.7.7.3. Product Benchmarking
- 11.7.7.4. Recent Developments
- 11.7.8. Salesforce, Inc.
- 11.7.8.1. Participant's Overview
- 11.7.8.2. Financial Performance
- 11.7.8.3. Product Benchmarking
- 11.7.8.4. Recent Developments
- 11.7.9. SAP SE
- 11.7.9.1. Participant's Overview
- 11.7.9.2. Financial Performance
- 11.7.9.3. Product Benchmarking
- 11.7.9.4. Recent Developments
- 11.7.10. SAS Institute
- 11.7.10.1. Participant's Overview
- 11.7.10.2. Financial Performance
- 11.7.10.3. Product Benchmarking
- 11.7.10.4. Recent Developments