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Artificial Intelligence (AI) In Data Quality Market Value Analysis: What Growth Is Expected Over The Forecast Period?
The artificial intelligence (AI) in data quality market size has witnessed substantial growth in recent years. It is forecast to expand from $1.48 billion in 2025 to $1.85 billion in 2026, achieving a compound annual growth rate (CAGR) of 25.0%. The historical development of this market is attributable to the expanding volumes of enterprise data, early initiatives in data governance, the adoption of master data management, increasing demands for regulatory reporting, and the proliferation of cloud data platforms.
The artificial intelligence (AI) in data quality market is anticipated to undergo significant expansion in the foreseeable future, with its valuation expected to reach $4.47 billion by 2030, growing at a compound annual growth rate (CAGR) of 24.7%. This projected increase during the forecast period is driven by the broader adoption of AI-powered analytics, the pressing need for real-time data accuracy, the advancement of data fabric architectures, heightened automation in data operations, and more rigorous data compliance mandates. Notable trends emerging in this period include automated methods for data cleansing and enrichment, AI-enabled detection of data anomalies, continuous oversight of data quality, anticipatory data quality management strategies, and self-learning models for data validation.
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Artificial Intelligence (AI) In Data Quality Market Growth Momentum: Which Factors Are Influencing Demand?
The increasing embrace of cloud computing is anticipated to accelerate the expansion of artificial intelligence (AI) within the data quality market. Cloud computing adoption signifies a transition from conventional on-premises IT setups to cloud-based platforms, providing computing resources that are scalable, economical, and accessible remotely. This adoption is primarily fueled by ongoing digital transformation efforts across various sectors and the demand for adaptable and agile data management solutions. AI significantly boosts data quality in cloud settings by automating tasks such as data profiling, cleansing, and validation, thereby guaranteeing data accuracy and integrity crucial for making real-time decisions. As an illustration, in December 2023, data from Eurostat, the Luxembourg-based statistical office of the European Union, indicated that 45.2% of EU enterprises utilized cloud computing in 2023, an increase of 4.2 points compared to 2021, predominantly for services like email, file storage, and office tools. Consequently, the growing uptake of cloud computing is propelling the advancement of artificial intelligence (AI) in the data quality market.
Artificial Intelligence (AI) In Data Quality Market Segment Analysis: What Are The Major Market Categories?
The artificial intelligence (AI) in data quality market covered in this report is segmented –
1) By Component: Software, Services
2) By Deployment Mode: Cloud-Based, On-premise
3) By Organization Size: Small And Medium-Sized Enterprises, Large Enterprises
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
Subsegments:
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
2) By Services: Professional Services, Managed Services, Consulting Services, Implementation And Integration Services, Training And Support Services
Artificial Intelligence (AI) In Data Quality Market Growth Trends Influencing Competitive Dynamics
Leading companies active in the artificial intelligence (AI) in data quality market are concentrating on integrating generative artificial intelligence to boost data accuracy and operational efficiency. Generative artificial intelligence (GenAI) refers to AI systems designed to produce 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 capability utilizes generative artificial intelligence (GenAI) to automate data quality checks. By enabling 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.
Artificial Intelligence (AI) In Data Quality Market Leading Companies Driving Competitive Growth
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.
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Artificial Intelligence (AI) In Data Quality Market Geographic Distribution And Regional Opportunities
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.
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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.