Tag: artificial intelligence (AI)-driven web scraping market size

The Business Research Company’s 2026 market reports feature advanced enhancements such as market attractiveness analysis, total addressable market evaluation, company benchmarking matrices, interactive Excel dashboards, expanded supply chain intelligence, emerging startup coverage, and detailed product insights, delivering more actionable and strategically valuable research.

How Will The Market Value Of The Artificial Intelligence (AI)-Driven Web Scraping Market Change Between 2026 And 2030?

In recent years, the artificial intelligence (AI)-driven web scraping market has shown substantial expansion. It is anticipated to increase from $8.24 billion in 2025 to $10.20 billion in 2026, achieving a compound annual growth rate (CAGR) of 23.8%. Factors contributing to this historical growth include increasing digital data volumes, growing e-commerce activity, rising demand for competitive intelligence, the expansion of cloud-based scraping solutions, and broader adoption across various sectors.

The artificial intelligence (AI)-driven web scraping market size is projected to experience rapid expansion in the coming years, with an anticipated growth to $23.70 billion by 2030, at a compound annual growth rate (CAGR) of 23.5%. This growth in the forecast period is primarily driven by the increasing demand for real-time business intelligence, the rising adoption of artificial intelligence and machine learning technologies, a growing need for dynamic pricing and market monitoring, the expansion of no-code/low-code scraping platforms, and increasing demand from small and medium enterprises. Significant trends in the forecast period include technological advancements in artificial intelligence (AI) and machine learning, innovations in automated data extraction tools, developments in cloud-native and scalable scraping platforms, research and development in anti-bot evasion and proxy networks, and greater integration with real-time analytics and decision-making systems.

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What Influential Factors Are Boosting The Artificial Intelligence (AI)-Driven Web Scraping Market Demand?

The increasing integration of AI-powered decision-making tools is projected to drive the expansion of the artificial intelligence (AI)-driven web scraping market moving forward. Specifically, AI-powered decision-making tools are software systems that employ artificial intelligence, including machine learning and predictive analytics, to automate and elevate business decisions and insights. This surge in adoption can be attributed to heightened enterprise digitalization and the necessity for strategic decision-making guided by data. Artificial intelligence (AI)-driven web scraping improves AI-powered decision-making tools by automatically gathering and organizing substantial quantities of real-time data from various online platforms. This process boosts analytical precision and promptness through providing machine learning models with current insights, thus facilitating quicker, data-informed strategic choices. As an illustration, a report in January 2025 from Eurostat, the Luxembourg-based statistical office of the European Union, revealed that in 2024, 13.5% of enterprises with 10 or more employees were utilizing AI technologies, which is an increase from 8.0% in 2023, indicating a 5.5 percentage-point rise. Consequently, the expanding use of AI-powered decision-making tools is accelerating the expansion of the artificial intelligence (AI)-driven web scraping market.

What Are The Major Segment Categories Within The Artificial Intelligence (AI)-Driven Web Scraping Market?

The artificial intelligence (AI)-driven web scraping market covered in this report is segmented –

1) By Scraping Type: Static Web Scraping, Dynamic Web Scraping, Application Programming Interface Scraping, Image And Text Recognition

2) By Deployment Type: On-Premises, Cloud, Hybrid

3) By Organization Size: Small Enterprises, Medium Enterprises, Large Enterprises

4) By Application: Price Monitoring, Market Intelligence, Lead Generation, Data Mining

5) By Industry Vertical: E-Commerce, Financial Services, Healthcare, Manufacturing, Retail, Technology

Subsegments:

1) By Static Web Scraping: Manual Static Page Extraction, Automated Static Content Parsing, Hypertext Markup Language Structure Based Extraction, File Based Static Data Retrieval, Script Driven Static Data Collection

2) By Dynamic Web Scraping: Browser Automation Extraction, Java Script Rendered Content Extraction, Interactive Page Element Extraction, Form Submission Based Extraction, Dynamic Hypertext Markup Language Content Parsing

3) By Application Programming Interface Scraping: Public Application Programming Interface Data Extraction, Private Application Programming Interface Data Extraction, Rest Application Programming Interface Based Data Collection, Graph Query Language Application Programming Interface Based Extraction, Automated Application Programming Interface Response Parsing

4) By Image And Text Recognition: Optical Character Recognition Based Data Extraction, Image Pattern Recognition Extraction, Document Image Data Capture, Visual Content Based Data Identification, Text Recognition From Multimedia Content

What Trends Are Influencing The Artificial Intelligence (AI)-Driven Web Scraping Market?

Leading companies operating in the artificial intelligence (AI)-driven web scraping market are concentrating on developing advanced platforms, such as AI-powered low-code tools, to enhance efficiency, improve accessibility, and reduce technical barriers and the duration of development. AI-powered low-code tools are platforms that utilize artificial intelligence to automate the extraction and structuring of web data based on natural language descriptions, thereby removing the necessity for manual coding. For instance, in July 2025, Oxylabs.io, a Lithuania-based web-intelligence and proxy services company, introduced AI Studio. This new collection of AI-powered tools is engineered to facilitate finding, collecting, and obtaining ready-to-use web data through natural language prompts. It incorporates AI-Crawler and AI-Scraper functionalities, enabling effortless data extraction from multiple or single pages without requiring operator intervention. The platform also includes tools like Browser Agent for dynamic interactions and AI-Search for web queries, thereby expanding its utility and simplifying operational complexity for developers, product teams, and data analysts.

Who Are The Firms Contributing To The Artificial Intelligence (AI)-Driven Web Scraping Market Ecosystem?

Major companies operating in the artificial intelligence (AI)-driven web scraping market are Tungsten Automation, Hangzhou Duosuan Technology Co. Ltd., Oxylabs UAB, Bright Data Ltd., Zyte Ltd., Grepsr Pvt. Ltd., Apify Technologies s.r.o., Octopus Data Inc., Octoparse Co. Ltd., SerpApi LLC, ParseHub Inc., Diffbot Technologies Corp., Browse AI Inc., The Phantombuster Company, Scraping Robotics Inc., Scrapfly, DataHen Canada Inc., Datahut, ZenRows Inc., Smartproxy LLC

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Which Region Commands The Largest Share Of The Artificial Intelligence (AI)-Driven Web Scraping Market?

North America was the largest region in the artificial intelligence (AI)-driven web scraping market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI)-driven web scraping market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

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Uncover key drivers, emerging technologies, and competitive movements shaping the artificial intelligence (ai)-driven web scraping market from 2026–2035 with trusted insights from The Business Research Company

What upper market value could the Artificial Intelligence (AI)-Driven Web Scraping Market reach by 2030 starting from 2026 levels?

The artificial intelligence (AI)-driven web scraping market has witnessed significant growth in recent years. This market is projected to expand from $8.24 billion in 2025 to $10.20 billion in 2026, achieving a compound annual growth rate (CAGR) of 23.8%. Historically, this expansion has been fueled by factors such as the increasing volumes of digital data, a rise in e-commerce activity, growing demand for competitive intelligence, the proliferation of cloud-based scraping solutions, and wider adoption across numerous sectors.

The artificial intelligence (AI)-driven web scraping market is poised for significant expansion in the coming years. It is projected to reach $23.70 billion in 2030, showing a compound annual growth rate (CAGR) of 23.5%. This anticipated growth during the forecast period is fueled by factors such as a heightened need for real-time business insights, increased adoption of artificial intelligence and machine learning technologies, a growing requirement for adaptable pricing and market oversight, the proliferation of no-code/low-code scraping platforms, and rising demand from small and medium-sized businesses. Key trends foreseen during this period include technological breakthroughs in artificial intelligence (AI) and machine learning, progress in automated data extraction tools, evolution of cloud-native and scalable scraping solutions, ongoing research and development in anti-bot evasion and proxy networks, and greater integration with real-time analytical and decision-support systems.

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Which Drivers Are Influencing Long-Term Growth In The Artificial Intelligence (AI)-Driven Web Scraping Market?

The increasing use of AI-powered decision-making tools is anticipated to fuel the expansion of the artificial intelligence (AI)-driven web scraping market in the future. These tools are software systems leveraging artificial intelligence, including machine learning and predictive analytics, to automate and improve business insights and decisions. This growing adoption stems from heightened enterprise digitalization and the necessity for strategic decisions informed by data. Artificial intelligence (AI)-driven web scraping boosts AI-powered decision-making tools by automatically gathering and organizing vast amounts of real-time data from various online platforms. It enhances analytical precision and promptness by supplying machine learning models with current insights, thereby facilitating quicker, data-informed strategic choices. For example, data released by Eurostat, the European Union’s statistical office based in Luxembourg, in January 2025 showed that 13.5% of businesses employing 10 or more people utilized AI technologies in 2024, an increase from 8.0% in 2023, representing a 5.5 percentage-point rise. Consequently, the increased uptake of AI-powered decision-making tools is propelling the expansion of the artificial intelligence (AI)-driven web scraping market.

How Is The Artificial Intelligence (AI)-Driven Web Scraping Market Divided Into Segments?

The artificial intelligence (AI)-driven web scraping market covered in this report is segmented –

1) By Scraping Type: Static Web Scraping, Dynamic Web Scraping, Application Programming Interface Scraping, Image And Text Recognition

2) By Deployment Type: On-Premises, Cloud, Hybrid

3) By Organization Size: Small Enterprises, Medium Enterprises, Large Enterprises

4) By Application: Price Monitoring, Market Intelligence, Lead Generation, Data Mining

5) By Industry Vertical: E-Commerce, Financial Services, Healthcare, Manufacturing, Retail, Technology

Subsegments:

1) By Static Web Scraping: Manual Static Page Extraction, Automated Static Content Parsing, Hypertext Markup Language Structure Based Extraction, File Based Static Data Retrieval, Script Driven Static Data Collection

2) By Dynamic Web Scraping: Browser Automation Extraction, Java Script Rendered Content Extraction, Interactive Page Element Extraction, Form Submission Based Extraction, Dynamic Hypertext Markup Language Content Parsing

3) By Application Programming Interface Scraping: Public Application Programming Interface Data Extraction, Private Application Programming Interface Data Extraction, Rest Application Programming Interface Based Data Collection, Graph Query Language Application Programming Interface Based Extraction, Automated Application Programming Interface Response Parsing

4) By Image And Text Recognition: Optical Character Recognition Based Data Extraction, Image Pattern Recognition Extraction, Document Image Data Capture, Visual Content Based Data Identification, Text Recognition From Multimedia Content

What Trends Are Expected To Impact The Competitive Landscape Of The Artificial Intelligence (AI)-Driven Web Scraping Market?

Leading companies within the artificial intelligence (AI)-driven web scraping market are concentrating on developing sophisticated platforms, such as AI-powered low-code tools, to boost efficiency, enhance accessibility, and reduce both technical barriers and development time. These AI-powered low-code tools are defined as platforms that employ artificial intelligence to automate the extraction and structuring of web data based on natural language descriptions, thereby eliminating the need for manual coding. For instance, in July 2025, Oxylabs.io, a Lithuania-based web-intelligence and proxy services company, introduced AI Studio. This new suite of AI-powered tools is designed to simplify the process of finding, collecting, and obtaining ready-to-use web data through natural language prompts. It features AI-Crawler and AI-Scraper functionalities, which enable seamless data extraction from multiple or single pages without requiring operator intervention. The suite also incorporates tools like Browser Agent for dynamic interactions and AI-Search for web queries, thereby extending the platform’s utility and reducing operational complexity for developers, product teams, and data analysts.

Which Key Players Are Driving Competition In The Artificial Intelligence (AI)-Driven Web Scraping Market?

Major companies operating in the artificial intelligence (AI)-driven web scraping market are Tungsten Automation, Hangzhou Duosuan Technology Co. Ltd., Oxylabs UAB, Bright Data Ltd., Zyte Ltd., Grepsr Pvt. Ltd., Apify Technologies s.r.o., Octopus Data Inc., Octoparse Co. Ltd., SerpApi LLC, ParseHub Inc., Diffbot Technologies Corp., Browse AI Inc., The Phantombuster Company, Scraping Robotics Inc., Scrapfly, DataHen Canada Inc., Datahut, ZenRows Inc., Smartproxy LLC

Access The Complete Report For Deeper Market Insights:

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Which Region Is Projected To Lead The Artificial Intelligence (AI)-Driven Web Scraping Market During The Forecast Period?

North America was the largest region in the artificial intelligence (AI)-driven web scraping market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI)-driven web scraping market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

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Email us at marketing@tbrc.info

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What Changes In Market Value Are Expected For The Artificial Intelligence (AI)-Driven Web Scraping Market Over The 2026–2030 Period?

The artificial intelligence (AI)-driven web scraping market size has seen significant growth in recent years. It is forecast to grow from $8.24 billion in 2025 to $10.20 billion in 2026, achieving a compound annual growth rate (CAGR) of 23.8%. This historical expansion can be linked to increasing digital data volumes, rising e-commerce activity, greater demand for competitive intelligence, the spread of cloud-based scraping solutions, and wider adoption across various industries.

The artificial intelligence (AI)-driven web scraping market is poised for substantial expansion in the coming years. It is projected to reach $23.70 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 23.5%. This anticipated growth is driven by factors such as the increasing need for real-time business intelligence, the growing adoption of artificial intelligence and machine learning technologies, the rising demand for dynamic pricing and market monitoring, the spread of no-code/low-code scraping platforms, and expanding interest from small and medium enterprises. Prominent trends for this period include technological improvements in artificial intelligence (AI) and machine learning, innovations in automated data extraction tools, the evolution of cloud-native and scalable scraping platforms, continued research and development in anti-bot evasion and proxy networks, and enhanced integration with real-time analytics and decision-making systems.

Access Your Free Sample Report For In-Depth Market Analysis:

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Which Primary Drivers Are Impacting The Artificial Intelligence (AI)-Driven Web Scraping Market Growth?

The anticipated expansion of the artificial intelligence (AI)-driven web scraping market is attributed to the increasing acceptance of AI-powered decision-making tools. These tools are defined as software systems leveraging artificial intelligence, including machine learning and predictive analytics, to automate and improve business insights and decisions. This growing adoption stems from heightened enterprise digitalization and the demand for strategic decisions supported by data. Artificial intelligence (AI)-driven web scraping improves AI-powered decision-making tools by automatically gathering and organizing vast amounts of real-time data from various online sources. It boosts analytical precision and promptness by supplying machine learning models with current insights, thus facilitating quicker, data-informed strategic choices. For example, data released in January 2025 by Eurostat, the European Union’s statistical office based in Luxembourg, indicated that in 2024, 13.5% of enterprises employing 10 or more individuals utilized AI technologies, showing an increase of 5.5 percentage-points from 8.0% in 2023. Consequently, the increased uptake of AI-powered decision-making tools is fueling the expansion of the artificial intelligence (AI)-driven web scraping market.

What Segment Categories Shape The Artificial Intelligence (AI)-Driven Web Scraping Market Segment Landscape?

The artificial intelligence (AI)-driven web scraping market covered in this report is segmented –

1) By Scraping Type: Static Web Scraping, Dynamic Web Scraping, Application Programming Interface Scraping, Image And Text Recognition

2) By Deployment Type: On-Premises, Cloud, Hybrid

3) By Organization Size: Small Enterprises, Medium Enterprises, Large Enterprises

4) By Application: Price Monitoring, Market Intelligence, Lead Generation, Data Mining

5) By Industry Vertical: E-Commerce, Financial Services, Healthcare, Manufacturing, Retail, Technology

Subsegments:

1) By Static Web Scraping: Manual Static Page Extraction, Automated Static Content Parsing, Hypertext Markup Language Structure Based Extraction, File Based Static Data Retrieval, Script Driven Static Data Collection

2) By Dynamic Web Scraping: Browser Automation Extraction, Java Script Rendered Content Extraction, Interactive Page Element Extraction, Form Submission Based Extraction, Dynamic Hypertext Markup Language Content Parsing

3) By Application Programming Interface Scraping: Public Application Programming Interface Data Extraction, Private Application Programming Interface Data Extraction, Rest Application Programming Interface Based Data Collection, Graph Query Language Application Programming Interface Based Extraction, Automated Application Programming Interface Response Parsing

4) By Image And Text Recognition: Optical Character Recognition Based Data Extraction, Image Pattern Recognition Extraction, Document Image Data Capture, Visual Content Based Data Identification, Text Recognition From Multimedia Content

Which Trends Are Shaping Growth In The Artificial Intelligence (AI)-Driven Web Scraping Market?

Leading entities within the artificial intelligence (AI)-driven web scraping market are concentrating on creating sophisticated platforms, particularly AI-driven low-code solutions, aimed at improving operational efficiency, broadening user accessibility, and mitigating technical hurdles and development cycles. These AI-powered low-code tools are defined as platforms leveraging artificial intelligence to automate the process of extracting and organizing web data through natural language commands, thereby removing the requirement for traditional coding. A notable example occurred in July 2025 when Oxylabs.io, a company specializing in web intelligence and proxy services based in Lithuania, introduced its AI Studio. This offering is a novel collection of AI-enabled instruments designed to simplify the discovery, acquisition, and preparation of web data using natural language instructions. Key features encompass AI-Crawler and AI-Scraper capabilities, which facilitate effortless data extraction from either numerous or individual web pages without requiring human involvement. Furthermore, it integrates tools like Browser Agent for managing dynamic web interactions and AI-Search for conducting web queries, thereby broadening the platform’s overall usefulness and diminishing operational complexities for developers, product teams, and data analysts alike.

Who Are The Companies Operating Across The Artificial Intelligence (AI)-Driven Web Scraping Market Value Chain?

Major companies operating in the artificial intelligence (AI)-driven web scraping market are Tungsten Automation, Hangzhou Duosuan Technology Co. Ltd., Oxylabs UAB, Bright Data Ltd., Zyte Ltd., Grepsr Pvt. Ltd., Apify Technologies s.r.o., Octopus Data Inc., Octoparse Co. Ltd., SerpApi LLC, ParseHub Inc., Diffbot Technologies Corp., Browse AI Inc., The Phantombuster Company, Scraping Robotics Inc., Scrapfly, DataHen Canada Inc., Datahut, ZenRows Inc., Smartproxy LLC

Get The Full Artificial Intelligence (AI)-Driven Web Scraping Market Report:

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Which Region Leads The Artificial Intelligence (AI)-Driven Web Scraping Market In Terms Of Market Share?

North America was the largest region in the artificial intelligence (AI)-driven web scraping market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI)-driven web scraping market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

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The Business Research Company’s 2026 market reports include new capabilities such as market attractiveness scoring and analysis, total addressable market analysis, company scoring matrix, interactive excel data dashboard, improved supply chain analysis, upcoming startups in the market, and overview of key products, aimed at improving the depth, usability, and strategic value of the insights delivered.

What Market Size Growth Is Projected For The Artificial Intelligence (AI)-Driven Web Scraping Market During The Forecast Period 2026–2030?

The artificial intelligence (AI)-driven web scraping market has experienced significant expansion in its size over recent years. This market is projected to expand from $8.24 billion in 2025 to $10.20 billion in 2026, demonstrating a compound annual growth rate (CAGR) of 23.8%. Historically, this expansion has been driven by factors such as increasing digital data volumes, growing e-commerce activity, a rising demand for competitive intelligence, the expansion of cloud-based scraping solutions, and broader adoption across various sectors.

The market for artificial intelligence (AI)-powered web scraping is projected to experience rapid expansion over the upcoming years. This market is forecast to reach $23.70 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 23.5%. This anticipated growth is driven by several factors, including the heightened need for immediate business insights, wider acceptance of artificial intelligence and machine learning tools, the increasing requirement for flexible pricing and market surveillance, the proliferation of no-code/low-code scraping solutions, and increasing uptake from small and medium-sized businesses. Key developments expected during this period encompass technological progress in artificial intelligence (AI) and machine learning, novel advancements in automated data extraction, the evolution of cloud-native and scalable scraping infrastructures, ongoing research and development in anti-bot circumvention and proxy network technologies, and deeper integration with real-time analytical and decision-making frameworks.

Download the Free Sample Report to Explore Key Market Insights:

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Which Major Factors Are Driving The Expansion Of The Artificial Intelligence (AI)-Driven Web Scraping Market?

The increased adoption of AI-powered decision-making tools is anticipated to fuel the expansion of the artificial intelligence (AI)-driven web scraping market in the future. These AI-powered decision-making tools are software systems that employ artificial intelligence, such as machine learning and predictive analytics, to automate and enhance business decisions and insights. This rise in adoption is attributed to growing enterprise digitalization and the necessity for data-driven strategic decision-making. Artificial intelligence (AI)-driven web scraping improves AI-powered decision-making tools by automatically gathering and structuring extensive volumes of real-time data from diverse online sources. It boosts analytical accuracy and timeliness by supplying machine learning models with up-to-date insights, enabling more rapid, data-driven strategic decisions. For instance, in January 2025, according to Eurostat, a Luxembourg-based statistical office of the European Union, in 2024, 13.5% of enterprises with 10 or more employees used AI technologies, which was an increase from 8.0% in 2023, representing a 5.5 percentage-point increase. Therefore, the growing adoption of AI-powered decision-making tools is driving the growth of the artificial intelligence (AI)-driven web scraping market.

What Market Segments Are Evaluated Within The Artificial Intelligence (AI)-Driven Web Scraping Market?

The artificial intelligence (AI)-driven web scraping market covered in this report is segmented –

1) By Scraping Type: Static Web Scraping, Dynamic Web Scraping, Application Programming Interface Scraping, Image And Text Recognition

2) By Deployment Type: On-Premises, Cloud, Hybrid

3) By Organization Size: Small Enterprises, Medium Enterprises, Large Enterprises

4) By Application: Price Monitoring, Market Intelligence, Lead Generation, Data Mining

5) By Industry Vertical: E-Commerce, Financial Services, Healthcare, Manufacturing, Retail, Technology

Subsegments:

1) By Static Web Scraping: Manual Static Page Extraction, Automated Static Content Parsing, Hypertext Markup Language Structure Based Extraction, File Based Static Data Retrieval, Script Driven Static Data Collection

2) By Dynamic Web Scraping: Browser Automation Extraction, Java Script Rendered Content Extraction, Interactive Page Element Extraction, Form Submission Based Extraction, Dynamic Hypertext Markup Language Content Parsing

3) By Application Programming Interface Scraping: Public Application Programming Interface Data Extraction, Private Application Programming Interface Data Extraction, Rest Application Programming Interface Based Data Collection, Graph Query Language Application Programming Interface Based Extraction, Automated Application Programming Interface Response Parsing

4) By Image And Text Recognition: Optical Character Recognition Based Data Extraction, Image Pattern Recognition Extraction, Document Image Data Capture, Visual Content Based Data Identification, Text Recognition From Multimedia Content

What Industry Trends Are Redefining The Artificial Intelligence (AI)-Driven Web Scraping Market?

Major companies in the artificial intelligence (AI)-driven web scraping market are emphasizing the creation of advanced platforms, including AI-powered low-code tools, to enhance efficiency, increase accessibility, and reduce both technical obstacles and development periods. AI-powered low-code tools are platforms that employ artificial intelligence to automate the extraction and structuring of web data through natural language descriptions, thereby removing the necessity for manual coding. For example, in July 2025, Oxylabs.io, a web-intelligence and proxy services company from Lithuania, introduced AI Studio. This new suite of AI-powered tools aims to simplify the process of finding, collecting, and preparing web data using natural language prompts. It includes functionalities like AI-Crawler and AI-Scraper, enabling effortless data extraction from numerous or individual pages without human intervention. Additionally, it integrates tools such as Browser Agent for dynamic interactions and AI-Search for web queries, thereby broadening the platform’s utility and diminishing operational complexity for developers, product teams, and data analysts.

Who Are The Top Market Participants Influencing The Artificial Intelligence (AI)-Driven Web Scraping Market?

Major companies operating in the artificial intelligence (AI)-driven web scraping market are Tungsten Automation, Hangzhou Duosuan Technology Co. Ltd., Oxylabs UAB, Bright Data Ltd., Zyte Ltd., Grepsr Pvt. Ltd., Apify Technologies s.r.o., Octopus Data Inc., Octoparse Co. Ltd., SerpApi LLC, ParseHub Inc., Diffbot Technologies Corp., Browse AI Inc., The Phantombuster Company, Scraping Robotics Inc., Scrapfly, DataHen Canada Inc., Datahut, ZenRows Inc., Smartproxy LLC

Read the full artificial intelligence (ai)-driven web scraping market report here:

https://www.thebusinessresearchcompany.com/report/artificial-intelligence-ai-driven-web-scraping-market-report

Which Region Is Projected To Lead The Artificial Intelligence (AI)-Driven Web Scraping Market During The Forecast Period?

North America was the largest region in the artificial intelligence (AI)-driven web scraping market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI)-driven web scraping market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

Request A Tailored Artificial Intelligence (AI)-Driven Web Scraping Market Research Report For Competitive Advantage:

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https://www.thebusinessresearchcompany.com/report/artificial-intelligence-ai-content-generation-global-market-report

Get in touch with us:

The Business Research Company: https://www.thebusinessresearchcompany.com/

Americas +1 310-496-7795

Asia +44 7882 955267 & +91 8897263534

Europe +44 7882 955267

Email us at info@tbrc.info

Follow us on:

LinkedIn: https://in.linkedin.com/company/the-business-research-company

YouTube: https://www.youtube.com/channel/UC24_fI0rV8cR5DxlCpgmyFQ

Global Market Model: https://www.thebusinessresearchcompany.com/global-market-model

The Business Research Company’s 2026 market reports include new capabilities such as market attractiveness scoring and analysis, total addressable market analysis, company scoring matrix, interactive excel data dashboard, improved supply chain analysis, upcoming startups in the market, and overview of key products, aimed at improving the depth, usability, and strategic value of the insights delivered.

What Market Size Growth Is Projected For The Artificial Intelligence (AI)-Driven Web Scraping Market During The Forecast Period 2026–2030?

The artificial intelligence (AI)-driven web scraping market has experienced significant expansion in its size over recent years. This market is projected to expand from $8.24 billion in 2025 to $10.20 billion in 2026, demonstrating a compound annual growth rate (CAGR) of 23.8%. Historically, this expansion has been driven by factors such as increasing digital data volumes, growing e-commerce activity, a rising demand for competitive intelligence, the expansion of cloud-based scraping solutions, and broader adoption across various sectors.

The market for artificial intelligence (AI)-powered web scraping is projected to experience rapid expansion over the upcoming years. This market is forecast to reach $23.70 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 23.5%. This anticipated growth is driven by several factors, including the heightened need for immediate business insights, wider acceptance of artificial intelligence and machine learning tools, the increasing requirement for flexible pricing and market surveillance, the proliferation of no-code/low-code scraping solutions, and increasing uptake from small and medium-sized businesses. Key developments expected during this period encompass technological progress in artificial intelligence (AI) and machine learning, novel advancements in automated data extraction, the evolution of cloud-native and scalable scraping infrastructures, ongoing research and development in anti-bot circumvention and proxy network technologies, and deeper integration with real-time analytical and decision-making frameworks.

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Which Major Factors Are Driving The Expansion Of The Artificial Intelligence (AI)-Driven Web Scraping Market?

The increased adoption of AI-powered decision-making tools is anticipated to fuel the expansion of the artificial intelligence (AI)-driven web scraping market in the future. These AI-powered decision-making tools are software systems that employ artificial intelligence, such as machine learning and predictive analytics, to automate and enhance business decisions and insights. This rise in adoption is attributed to growing enterprise digitalization and the necessity for data-driven strategic decision-making. Artificial intelligence (AI)-driven web scraping improves AI-powered decision-making tools by automatically gathering and structuring extensive volumes of real-time data from diverse online sources. It boosts analytical accuracy and timeliness by supplying machine learning models with up-to-date insights, enabling more rapid, data-driven strategic decisions. For instance, in January 2025, according to Eurostat, a Luxembourg-based statistical office of the European Union, in 2024, 13.5% of enterprises with 10 or more employees used AI technologies, which was an increase from 8.0% in 2023, representing a 5.5 percentage-point increase. Therefore, the growing adoption of AI-powered decision-making tools is driving the growth of the artificial intelligence (AI)-driven web scraping market.

What Market Segments Are Evaluated Within The Artificial Intelligence (AI)-Driven Web Scraping Market?

The artificial intelligence (AI)-driven web scraping market covered in this report is segmented –

1) By Scraping Type: Static Web Scraping, Dynamic Web Scraping, Application Programming Interface Scraping, Image And Text Recognition

2) By Deployment Type: On-Premises, Cloud, Hybrid

3) By Organization Size: Small Enterprises, Medium Enterprises, Large Enterprises

4) By Application: Price Monitoring, Market Intelligence, Lead Generation, Data Mining

5) By Industry Vertical: E-Commerce, Financial Services, Healthcare, Manufacturing, Retail, Technology

Subsegments:

1) By Static Web Scraping: Manual Static Page Extraction, Automated Static Content Parsing, Hypertext Markup Language Structure Based Extraction, File Based Static Data Retrieval, Script Driven Static Data Collection

2) By Dynamic Web Scraping: Browser Automation Extraction, Java Script Rendered Content Extraction, Interactive Page Element Extraction, Form Submission Based Extraction, Dynamic Hypertext Markup Language Content Parsing

3) By Application Programming Interface Scraping: Public Application Programming Interface Data Extraction, Private Application Programming Interface Data Extraction, Rest Application Programming Interface Based Data Collection, Graph Query Language Application Programming Interface Based Extraction, Automated Application Programming Interface Response Parsing

4) By Image And Text Recognition: Optical Character Recognition Based Data Extraction, Image Pattern Recognition Extraction, Document Image Data Capture, Visual Content Based Data Identification, Text Recognition From Multimedia Content

What Industry Trends Are Redefining The Artificial Intelligence (AI)-Driven Web Scraping Market?

Major companies in the artificial intelligence (AI)-driven web scraping market are emphasizing the creation of advanced platforms, including AI-powered low-code tools, to enhance efficiency, increase accessibility, and reduce both technical obstacles and development periods. AI-powered low-code tools are platforms that employ artificial intelligence to automate the extraction and structuring of web data through natural language descriptions, thereby removing the necessity for manual coding. For example, in July 2025, Oxylabs.io, a web-intelligence and proxy services company from Lithuania, introduced AI Studio. This new suite of AI-powered tools aims to simplify the process of finding, collecting, and preparing web data using natural language prompts. It includes functionalities like AI-Crawler and AI-Scraper, enabling effortless data extraction from numerous or individual pages without human intervention. Additionally, it integrates tools such as Browser Agent for dynamic interactions and AI-Search for web queries, thereby broadening the platform’s utility and diminishing operational complexity for developers, product teams, and data analysts.

Who Are The Top Market Participants Influencing The Artificial Intelligence (AI)-Driven Web Scraping Market?

Major companies operating in the artificial intelligence (AI)-driven web scraping market are Tungsten Automation, Hangzhou Duosuan Technology Co. Ltd., Oxylabs UAB, Bright Data Ltd., Zyte Ltd., Grepsr Pvt. Ltd., Apify Technologies s.r.o., Octopus Data Inc., Octoparse Co. Ltd., SerpApi LLC, ParseHub Inc., Diffbot Technologies Corp., Browse AI Inc., The Phantombuster Company, Scraping Robotics Inc., Scrapfly, DataHen Canada Inc., Datahut, ZenRows Inc., Smartproxy LLC

Read the full artificial intelligence (ai)-driven web scraping market report here:

https://www.thebusinessresearchcompany.com/report/artificial-intelligence-ai-driven-web-scraping-market-report

Which Region Is Projected To Lead The Artificial Intelligence (AI)-Driven Web Scraping Market During The Forecast Period?

North America was the largest region in the artificial intelligence (AI)-driven web scraping market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI)-driven web scraping market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

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What Market Size Growth Is Projected For The Artificial Intelligence (AI)-Driven Web Scraping Market During The Forecast Period 2026–2030?

The artificial intelligence (AI)-driven web scraping market has experienced significant expansion in its size over recent years. This market is projected to expand from $8.24 billion in 2025 to $10.20 billion in 2026, demonstrating a compound annual growth rate (CAGR) of 23.8%. Historically, this expansion has been driven by factors such as increasing digital data volumes, growing e-commerce activity, a rising demand for competitive intelligence, the expansion of cloud-based scraping solutions, and broader adoption across various sectors.

The market for artificial intelligence (AI)-powered web scraping is projected to experience rapid expansion over the upcoming years. This market is forecast to reach $23.70 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 23.5%. This anticipated growth is driven by several factors, including the heightened need for immediate business insights, wider acceptance of artificial intelligence and machine learning tools, the increasing requirement for flexible pricing and market surveillance, the proliferation of no-code/low-code scraping solutions, and increasing uptake from small and medium-sized businesses. Key developments expected during this period encompass technological progress in artificial intelligence (AI) and machine learning, novel advancements in automated data extraction, the evolution of cloud-native and scalable scraping infrastructures, ongoing research and development in anti-bot circumvention and proxy network technologies, and deeper integration with real-time analytical and decision-making frameworks.

Download the Free Sample Report to Explore Key Market Insights:

https://www.thebusinessresearchcompany.com/sample.aspx?id=30524&type=smp

Which Major Factors Are Driving The Expansion Of The Artificial Intelligence (AI)-Driven Web Scraping Market?

The increased adoption of AI-powered decision-making tools is anticipated to fuel the expansion of the artificial intelligence (AI)-driven web scraping market in the future. These AI-powered decision-making tools are software systems that employ artificial intelligence, such as machine learning and predictive analytics, to automate and enhance business decisions and insights. This rise in adoption is attributed to growing enterprise digitalization and the necessity for data-driven strategic decision-making. Artificial intelligence (AI)-driven web scraping improves AI-powered decision-making tools by automatically gathering and structuring extensive volumes of real-time data from diverse online sources. It boosts analytical accuracy and timeliness by supplying machine learning models with up-to-date insights, enabling more rapid, data-driven strategic decisions. For instance, in January 2025, according to Eurostat, a Luxembourg-based statistical office of the European Union, in 2024, 13.5% of enterprises with 10 or more employees used AI technologies, which was an increase from 8.0% in 2023, representing a 5.5 percentage-point increase. Therefore, the growing adoption of AI-powered decision-making tools is driving the growth of the artificial intelligence (AI)-driven web scraping market.

What Market Segments Are Evaluated Within The Artificial Intelligence (AI)-Driven Web Scraping Market?

The artificial intelligence (AI)-driven web scraping market covered in this report is segmented –

1) By Scraping Type: Static Web Scraping, Dynamic Web Scraping, Application Programming Interface Scraping, Image And Text Recognition

2) By Deployment Type: On-Premises, Cloud, Hybrid

3) By Organization Size: Small Enterprises, Medium Enterprises, Large Enterprises

4) By Application: Price Monitoring, Market Intelligence, Lead Generation, Data Mining

5) By Industry Vertical: E-Commerce, Financial Services, Healthcare, Manufacturing, Retail, Technology

Subsegments:

1) By Static Web Scraping: Manual Static Page Extraction, Automated Static Content Parsing, Hypertext Markup Language Structure Based Extraction, File Based Static Data Retrieval, Script Driven Static Data Collection

2) By Dynamic Web Scraping: Browser Automation Extraction, Java Script Rendered Content Extraction, Interactive Page Element Extraction, Form Submission Based Extraction, Dynamic Hypertext Markup Language Content Parsing

3) By Application Programming Interface Scraping: Public Application Programming Interface Data Extraction, Private Application Programming Interface Data Extraction, Rest Application Programming Interface Based Data Collection, Graph Query Language Application Programming Interface Based Extraction, Automated Application Programming Interface Response Parsing

4) By Image And Text Recognition: Optical Character Recognition Based Data Extraction, Image Pattern Recognition Extraction, Document Image Data Capture, Visual Content Based Data Identification, Text Recognition From Multimedia Content

What Industry Trends Are Redefining The Artificial Intelligence (AI)-Driven Web Scraping Market?

Major companies in the artificial intelligence (AI)-driven web scraping market are emphasizing the creation of advanced platforms, including AI-powered low-code tools, to enhance efficiency, increase accessibility, and reduce both technical obstacles and development periods. AI-powered low-code tools are platforms that employ artificial intelligence to automate the extraction and structuring of web data through natural language descriptions, thereby removing the necessity for manual coding. For example, in July 2025, Oxylabs.io, a web-intelligence and proxy services company from Lithuania, introduced AI Studio. This new suite of AI-powered tools aims to simplify the process of finding, collecting, and preparing web data using natural language prompts. It includes functionalities like AI-Crawler and AI-Scraper, enabling effortless data extraction from numerous or individual pages without human intervention. Additionally, it integrates tools such as Browser Agent for dynamic interactions and AI-Search for web queries, thereby broadening the platform’s utility and diminishing operational complexity for developers, product teams, and data analysts.

Who Are The Top Market Participants Influencing The Artificial Intelligence (AI)-Driven Web Scraping Market?

Major companies operating in the artificial intelligence (AI)-driven web scraping market are Tungsten Automation, Hangzhou Duosuan Technology Co. Ltd., Oxylabs UAB, Bright Data Ltd., Zyte Ltd., Grepsr Pvt. Ltd., Apify Technologies s.r.o., Octopus Data Inc., Octoparse Co. Ltd., SerpApi LLC, ParseHub Inc., Diffbot Technologies Corp., Browse AI Inc., The Phantombuster Company, Scraping Robotics Inc., Scrapfly, DataHen Canada Inc., Datahut, ZenRows Inc., Smartproxy LLC

Read the full artificial intelligence (ai)-driven web scraping market report here:

https://www.thebusinessresearchcompany.com/report/artificial-intelligence-ai-driven-web-scraping-market-report

Which Region Is Projected To Lead The Artificial Intelligence (AI)-Driven Web Scraping Market During The Forecast Period?

North America was the largest region in the artificial intelligence (AI)-driven web scraping market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI)-driven web scraping market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

Request A Tailored Artificial Intelligence (AI)-Driven Web Scraping Market Research Report For Competitive Advantage:

https://www.thebusinessresearchcompany.com/customise?id=30524&type=smp

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https://www.thebusinessresearchcompany.com/report/artificial-intelligence-ai-content-generation-global-market-report

Get in touch with us:

The Business Research Company: https://www.thebusinessresearchcompany.com/

Americas +1 310-496-7795

Asia +44 7882 955267 & +91 8897263534

Europe +44 7882 955267

Email us at info@tbrc.info

Follow us on:

LinkedIn: https://in.linkedin.com/company/the-business-research-company

YouTube: https://www.youtube.com/channel/UC24_fI0rV8cR5DxlCpgmyFQ

Global Market Model: https://www.thebusinessresearchcompany.com/global-market-model