Featuring market attractiveness scoring, total addressable market sizing, company benchmarking matrices, interactive Excel dashboards, deeper supply chain intelligence, emerging startup tracking, and granular product-level insights, The Business Research Company’s 2026 market reports are built to deliver research that is both more actionable and more strategically valuable.
#Artificial Intelligence (AI) In Data Quality Market Growth From $1.85 Billion In 2026 To $4.47 Billion By 2030 At A CAGR Of 24.7%#_x000D_
The size of the artificial intelligence (AI) in data quality market has seen rapid expansion in recent years. This market is projected to expand from $1.48 billion in 2025 to $1.85 billion in 2026, demonstrating a compound annual growth rate (CAGR) of 25.0%. Factors contributing to its historical growth include the expansion of enterprise data volumes, initial data governance efforts, the implementation of master data management, escalating demands for regulatory reporting, and the emergence of cloud data platforms._x000D_
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The artificial intelligence (AI) in data quality market size is set to experience significant growth in the coming years. It is forecast to grow to $4.47 billion in 2030, exhibiting a compound annual growth rate (CAGR) of 24.7%. The expansion over this period is propelled by the spread of AI-driven analytics, the requirement for real-time data precision, the development of data fabric architectures, increasing automation in data operations, and stricter data compliance mandates. Important trends identified for the forecast period include automated data cleansing and enhancement, AI-powered detection of data anomalies, continuous observation of data quality, proactive data quality management, and self-teaching data validation systems._x000D_
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#Artificial Intelligence (AI) In Data Quality Market Growth Catalysts And Demand Drivers#_x000D_
The increasing uptake of cloud computing is projected to fuel the expansion of artificial intelligence (AI) in the data quality market moving forward. Cloud computing adoption signifies a move from traditional on-premises IT setups to cloud-based platforms, offering scalable, cost-effective, and remotely accessible computing resources. This shift to the cloud is predominantly driven by digital transformation efforts across industries and the necessity for adaptable and agile data management solutions. Artificial intelligence (AI) improves data quality within cloud environments by automating tasks such as data profiling, cleansing, and validation, thus ensuring data accuracy and integrity for effective real-time decision-making. For instance, in December 2023, Eurostat, a Luxembourg-based statistical office of the European Union, reported that cloud computing was utilized by 45.2% of EU enterprises in 2023, marking an increase of 4.2 points from 2021, primarily for email, file storage, and office tools. Consequently, the growing adoption of cloud computing is propelling the growth of artificial intelligence (AI) in the data quality market._x000D_
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#Artificial Intelligence (AI) In Data Quality Market Segment Performance And Emerging Opportunities#_x000D_
The artificial intelligence (AI) in data quality market covered in this report is segmented – _x000D_
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1) By Component: Software, Services_x000D_
2) By Deployment Mode: Cloud-Based, On-premise_x000D_
3) By Organization Size: Small And Medium-Sized Enterprises, Large Enterprises_x000D_
4) By Industry Vertical: Banking, Financial Services, and Insurance (BFSI), Information Technology (IT) And Telecommunications, Healthcare, Retail And E-commerce, Manufacturing, Government And Public Sector, Other Industry Verticals_x000D_
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Subsegments:_x000D_
1) By Software: Data Profiling Tools, Data Cleansing Tools, Data Monitoring And Validation Tools, Data Integration Software, Master Data Management (MDM) Solutions, Metadata Management Tools, Predictive Data Quality Analytics_x000D_
2) By Services: Professional Services, Managed Services, Consulting Services, Implementation And Integration Services, Training And Support Services_x000D_
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#Artificial Intelligence (AI) In Data Quality Market Trends Shaping Long-Term Demand#_x000D_
Major companies operating in the artificial intelligence (AI) in data quality market are focusing on integrating generative artificial intelligence to enhance data accuracy and operational efficiency. Generative artificial intelligence (GenAI) refers to AI systems designed to create new content, such as text, images, videos, audio, or code, based on patterns learned from existing data. For instance, in September 2023, Saama Technologies Inc., a US-based software company, introduced a Data Quality (DQ) Co-Pilot within its Smart Data Quality (SDQ) platform. This innovative feature leverages generative artificial intelligence (GenAI) to automate data quality checks. By allowing users to simply describe the desired data quality validation, the tool automatically generates and tests the corresponding code, significantly reducing manual effort and accelerating clinical trial workflows._x000D_
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#Artificial Intelligence (AI) In Data Quality Market Key Players: Which Companies Lead Industry Competition?#_x000D_
Major companies operating in the artificial intelligence (AI) in data quality market are Alphabet Inc., Microsoft Corporation, Amazon Web Services, Accenture plc, International Business Machines Corporation (IBM), Oracle Corporation, SAP SE, Salesforce.com Inc., Experian plc., Collibra, Dataiku, Sas Institute Inc., Teradata, Informatica Inc., Snowflake Inc., Alteryx Inc., QlikTech International AB, Precisely Corporation, TIBCO Software Inc., Databricks Inc., Ataccama Corporation. _x000D_
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#Artificial Intelligence (AI) In Data Quality Market Regional Analysis: Which Geography Leads On Revenue?#_x000D_
North America was the largest region in the artificial intelligence (AI) in data quality market in 2025. The regions covered in the artificial intelligence (AI) in data quality market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa._x000D_
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.
