For business leaders, corporate strategists, and growth-focused teams – this report delivers deep market intelligence, forecasts, segmentation, and competitor insights to guide your decisions through 2034.
What is the projected market size of the artificial intelligence (ai) in data quality industry, and what is its expected CAGR?
The artificial intelligence (AI) in data quality market size has grown exponentially in recent years. It will grow from $1.19 billion in 2024 to $1.49 billion in 2025 at a compound annual growth rate (CAGR) of 25.4%. The growth in the historic period can be attributed to data explosion across enterprises, rising demand for business intelligence, adoption of cloud-based data tools, early investments in artificial intelligence (AI) technologies, and increasing data compliance requirements.
The artificial intelligence (AI) in data quality market size is expected to see exponential growth in the next few years. It will grow to $3.65 billion in 2029 at a compound annual growth rate (CAGR) of 25.2%. The growth in the forecast period can be attributed to growth in real-time data processing needs, integration with cloud-native platforms, demand for automated data quality tools, expanding use of artificial intelligence (AI) in data governance, and rising importance of predictive analytics. Major trends in the forecast period include adoption of generative artificial intelligence (AI) for data synthesis, shift toward self-service data quality platforms, use of artificial intelligence (AI) in master data management, convergence of artificial intelligence (AI) and data fabric architecture, and focus on explainable artificial intelligence (AI) in data quality.
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What external factors are influencing the artificial intelligence (ai) in data quality market’s growth momentum?
The rise in cloud computing adoption is expected to propel the growth of artificial intelligence (AI) in the data quality market going forward. Cloud computing adoption refers to the shift from traditional on-premises IT infrastructure to cloud-based platforms, offering scalable, cost-efficient, and remotely accessible computing resources. Cloud adoption is largely driven by digital transformation initiatives across industries and the need for flexible and agile data management. Artificial intelligence (AI) enhances the quality of data in cloud environments by automating data profiling, cleansing, and validation, thus ensuring data accuracy and integrity for real-time decision-making. For instance, in December 2023, according to Eurostat, a Luxembourg-based statistical office of the European Union, cloud computing was used by 45.2% of EU enterprises in 2023, up 4.2 points from 2021, mainly for email, file storage, and office tools. Therefore, the rise in cloud computing adoption is driving growth in artificial intelligence (AI) in the data quality market.
What are the major market segments driving the growth of the artificial intelligence (ai) in data quality industry?
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
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How are emerging trends transforming the artificial intelligence (ai) in data quality market dynamics?
Major companies operating in the artificial intelligence (AI) in data quality market are focusing on the integration of 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.
Who are the key market players contributing to the growth of the artificial intelligence (ai) in data quality industry?
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.
Which regions are leading the growth of the artificial intelligence (ai) in data quality market globally?
North America was the largest region in the artificial intelligence (AI) in data quality market in 2024. The regions covered in the artificial intelligence (AI) in data quality market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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• Benchmark and plan partnerships using competitive landscape insights.
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