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 during the historical period can be credited to the rapid increase of data within organizations, the rising need for business intelligence, the adoption of cloud-based data tools, early investments in artificial intelligence (AI) technologies, and the growing demand for data compliance.
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 during the forecast period can be attributed to the increasing need for real-time data processing, integration with cloud-native platforms, demand for automated data quality tools, the expanding role of artificial intelligence (AI) in data governance, and the growing significance of predictive analytics. Key trends in the forecast period include the adoption of generative AI for data synthesis, a shift toward self-service data quality platforms, the use of AI in master data management, the convergence of AI with data fabric architecture, and a focus on explainable AI in data quality.
The growing adoption of cloud computing is expected to accelerate the expansion of artificial intelligence (AI) in the data quality market in the coming years. Cloud computing adoption involves transitioning from traditional on-premises IT infrastructure to cloud-based platforms, which offer scalable, cost-effective, and remotely accessible computing resources. This shift is largely fueled by digital transformation efforts across various industries and the need for more flexible and agile data management solutions. AI contributes to data quality in cloud environments by automating processes such as data profiling, cleansing, and validation, ensuring the accuracy and integrity of data for real-time decision-making. For example, in December 2023, Eurostat, the statistical office of the European Union, reported that 45.2% of EU enterprises used cloud computing, marking a 4.2-point increase from 2021, primarily for email, file storage, and office tools. As a result, the rise in cloud computing adoption is driving the growth of AI in the data quality market.
Leading companies in the artificial intelligence (AI) in data quality market are focusing on integrating generative AI to improve data accuracy and operational efficiency. Generative AI refers to AI systems that can create new content, such as text, images, videos, audio, or code, by learning patterns from existing data. For example, in September 2023, Saama Technologies Inc., a US-based software company, launched a Data Quality (DQ) Co Pilot within its Smart Data Quality (SDQ) platform. This innovative feature utilizes generative AI to automate data quality checks. By allowing users to simply describe the desired data validation, the tool automatically generates and tests the corresponding code, significantly reducing manual effort and speeding up clinical trial workflows.
In January 2024, QlikTech International AB, a US-based data integration and analytics company, acquired Kyndi for an undisclosed amount. This acquisition allows Qlik to enhance its artificial intelligence (AI) capabilities by integrating Kyndi’s advanced natural language processing and AI-powered search technology into its platform. Kyndi, a US-based company, specializes in natural language processing and AI software that helps businesses extract actionable insights from unstructured data.
Major players 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., and Ataccama Corporation.
North America was the largest region in the artificial intelligence (AI) in data quality market in 2024. The regions covered in artificial intelligence (AI) in data quality report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.
The countries covered in the artificial intelligence (AI) in data quality market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Artificial intelligence (AI) in data quality involves using AI technologies to automate, improve, and sustain the accuracy, consistency, completeness, and dependability of data across various systems. AI-powered tools are capable of identifying and correcting errors, detecting anomalies, filling in missing information, removing duplicate entries, and ensuring that data aligns with established standards.
The key elements of AI in data quality are software and services. Software in this context consists of AI-based tools developed to streamline and enhance data quality operations such as cleansing, validation, and enrichment. These solutions assist organizations in preserving precise and trustworthy data, which is essential for informed decision-making and operational effectiveness. They are available in both cloud-based and on-premise formats, accommodating organizations of different sizes - from small and medium-sized enterprises to large corporations - and are utilized across a broad range of industries, including banking, financial services, and insurance (BFSI), information technology (IT) and telecommunications, healthcare, retail and e-commerce, manufacturing, government, and the public sector, among others.
The artificial intelligence (AI) in data quality market research report is one of a series of new reports that provides artificial intelligence (AI) in data quality market statistics, including the artificial intelligence (AI) in data quality industry's global market size, regional shares, competitors with an artificial intelligence (AI) in data quality market share, detailed artificial intelligence (AI) in data quality market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence (AI) in data quality industry. This artificial intelligence (AI) in data quality market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.
The artificial intelligence (AI) in data quality market includes revenues earned by entities by providing services such as automated data profiling, anomaly detection, data cleansing, error reduction, and continuous monitoring. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI) in data quality market also includes sales of graphics processing units (GPUs), central processing units (CPUs), and high-performance memory. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).
The revenues for a specified geography are consumption values and are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
This product will be delivered within 3-5 business days.
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 during the forecast period can be attributed to the increasing need for real-time data processing, integration with cloud-native platforms, demand for automated data quality tools, the expanding role of artificial intelligence (AI) in data governance, and the growing significance of predictive analytics. Key trends in the forecast period include the adoption of generative AI for data synthesis, a shift toward self-service data quality platforms, the use of AI in master data management, the convergence of AI with data fabric architecture, and a focus on explainable AI in data quality.
The growing adoption of cloud computing is expected to accelerate the expansion of artificial intelligence (AI) in the data quality market in the coming years. Cloud computing adoption involves transitioning from traditional on-premises IT infrastructure to cloud-based platforms, which offer scalable, cost-effective, and remotely accessible computing resources. This shift is largely fueled by digital transformation efforts across various industries and the need for more flexible and agile data management solutions. AI contributes to data quality in cloud environments by automating processes such as data profiling, cleansing, and validation, ensuring the accuracy and integrity of data for real-time decision-making. For example, in December 2023, Eurostat, the statistical office of the European Union, reported that 45.2% of EU enterprises used cloud computing, marking a 4.2-point increase from 2021, primarily for email, file storage, and office tools. As a result, the rise in cloud computing adoption is driving the growth of AI in the data quality market.
Leading companies in the artificial intelligence (AI) in data quality market are focusing on integrating generative AI to improve data accuracy and operational efficiency. Generative AI refers to AI systems that can create new content, such as text, images, videos, audio, or code, by learning patterns from existing data. For example, in September 2023, Saama Technologies Inc., a US-based software company, launched a Data Quality (DQ) Co Pilot within its Smart Data Quality (SDQ) platform. This innovative feature utilizes generative AI to automate data quality checks. By allowing users to simply describe the desired data validation, the tool automatically generates and tests the corresponding code, significantly reducing manual effort and speeding up clinical trial workflows.
In January 2024, QlikTech International AB, a US-based data integration and analytics company, acquired Kyndi for an undisclosed amount. This acquisition allows Qlik to enhance its artificial intelligence (AI) capabilities by integrating Kyndi’s advanced natural language processing and AI-powered search technology into its platform. Kyndi, a US-based company, specializes in natural language processing and AI software that helps businesses extract actionable insights from unstructured data.
Major players 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., and Ataccama Corporation.
North America was the largest region in the artificial intelligence (AI) in data quality market in 2024. The regions covered in artificial intelligence (AI) in data quality report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.
The countries covered in the artificial intelligence (AI) in data quality market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Artificial intelligence (AI) in data quality involves using AI technologies to automate, improve, and sustain the accuracy, consistency, completeness, and dependability of data across various systems. AI-powered tools are capable of identifying and correcting errors, detecting anomalies, filling in missing information, removing duplicate entries, and ensuring that data aligns with established standards.
The key elements of AI in data quality are software and services. Software in this context consists of AI-based tools developed to streamline and enhance data quality operations such as cleansing, validation, and enrichment. These solutions assist organizations in preserving precise and trustworthy data, which is essential for informed decision-making and operational effectiveness. They are available in both cloud-based and on-premise formats, accommodating organizations of different sizes - from small and medium-sized enterprises to large corporations - and are utilized across a broad range of industries, including banking, financial services, and insurance (BFSI), information technology (IT) and telecommunications, healthcare, retail and e-commerce, manufacturing, government, and the public sector, among others.
The artificial intelligence (AI) in data quality market research report is one of a series of new reports that provides artificial intelligence (AI) in data quality market statistics, including the artificial intelligence (AI) in data quality industry's global market size, regional shares, competitors with an artificial intelligence (AI) in data quality market share, detailed artificial intelligence (AI) in data quality market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence (AI) in data quality industry. This artificial intelligence (AI) in data quality market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.
The artificial intelligence (AI) in data quality market includes revenues earned by entities by providing services such as automated data profiling, anomaly detection, data cleansing, error reduction, and continuous monitoring. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI) in data quality market also includes sales of graphics processing units (GPUs), central processing units (CPUs), and high-performance memory. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).
The revenues for a specified geography are consumption values and are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
This product will be delivered within 3-5 business days.
Table of Contents
1. Executive Summary2. Artificial Intelligence (AI) In Data Quality Market Characteristics3. Artificial Intelligence (AI) In Data Quality Market Trends And Strategies4. Artificial Intelligence (AI) In Data Quality Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Trade Wars and Tariffs, And Covid And Recovery On The Market32. Global Artificial Intelligence (AI) In Data Quality Market Competitive Benchmarking And Dashboard33. Key Mergers And Acquisitions In The Artificial Intelligence (AI) In Data Quality Market34. Recent Developments In The Artificial Intelligence (AI) In Data Quality Market
5. Global Artificial Intelligence (AI) In Data Quality Growth Analysis And Strategic Analysis Framework
6. Artificial Intelligence (AI) In Data Quality Market Segmentation
7. Artificial Intelligence (AI) In Data Quality Market Regional And Country Analysis
8. Asia-Pacific Artificial Intelligence (AI) In Data Quality Market
9. China Artificial Intelligence (AI) In Data Quality Market
10. India Artificial Intelligence (AI) In Data Quality Market
11. Japan Artificial Intelligence (AI) In Data Quality Market
12. Australia Artificial Intelligence (AI) In Data Quality Market
13. Indonesia Artificial Intelligence (AI) In Data Quality Market
14. South Korea Artificial Intelligence (AI) In Data Quality Market
15. Western Europe Artificial Intelligence (AI) In Data Quality Market
16. UK Artificial Intelligence (AI) In Data Quality Market
17. Germany Artificial Intelligence (AI) In Data Quality Market
18. France Artificial Intelligence (AI) In Data Quality Market
19. Italy Artificial Intelligence (AI) In Data Quality Market
20. Spain Artificial Intelligence (AI) In Data Quality Market
21. Eastern Europe Artificial Intelligence (AI) In Data Quality Market
22. Russia Artificial Intelligence (AI) In Data Quality Market
23. North America Artificial Intelligence (AI) In Data Quality Market
24. USA Artificial Intelligence (AI) In Data Quality Market
25. Canada Artificial Intelligence (AI) In Data Quality Market
26. South America Artificial Intelligence (AI) In Data Quality Market
27. Brazil Artificial Intelligence (AI) In Data Quality Market
28. Middle East Artificial Intelligence (AI) In Data Quality Market
29. Africa Artificial Intelligence (AI) In Data Quality Market
30. Artificial Intelligence (AI) In Data Quality Market Competitive Landscape And Company Profiles
31. Artificial Intelligence (AI) In Data Quality Market Other Major And Innovative Companies
35. Artificial Intelligence (AI) In Data Quality Market High Potential Countries, Segments and Strategies
36. Appendix
Executive Summary
Artificial Intelligence (AI) In Data Quality Global Market Report 2025 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses on artificial intelligence (ai) in data quality market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
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Description
Where is the largest and fastest growing market for artificial intelligence (ai) in data quality ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The artificial intelligence (ai) in data quality market global report answers all these questions and many more.The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.
- The market characteristics section of the report defines and explains the market.
- The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
- The forecasts are made after considering the major factors currently impacting the market. These include:
- The forecasts are made after considering the major factors currently impacting the market. These include the Russia-Ukraine war, rising inflation, higher interest rates, and the legacy of the COVID-19 pandemic.
- Market segmentations break down the market into sub markets.
- The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth. It covers the growth trajectory of COVID-19 for all regions, key developed countries and major emerging markets.
- The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
- The trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.
Scope
Markets Covered:
1) By Component: Software; Services2) 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 Analytics2) By Services: Professional Services; Managed Services; Consulting Services; Implementation And Integration Services; Training And Support Services
Key Companies Profiled: Alphabet Inc.; Microsoft Corporation; Amazon Web Services; Accenture plc; International Business Machines Corporation (IBM)
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Russia; South Korea; UK; USA; Canada; Italy; Spain
Regions: Asia-Pacific; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast.
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita.
Data Segmentation: Country and regional historic and forecast data, market share of competitors, market segments.
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
Delivery Format: PDF, Word and Excel Data Dashboard.
Companies Mentioned
- 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.