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Artificial Intelligence (AI)-Driven Web Scraping Market Revenue Growth Forecast To Reach $23.7 Billion By 2030 At 23.5% CAGR

May 6, 2026 by Marketing Posting

The Business Research Company’s 2026 market reports feature enhanced tools like market attractiveness analysis, TAM assessment, and company scoring matrices, along with interactive dashboards, deeper supply chain insights, and startup coverage strengthening the depth, usability, and strategic value of insights.

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.

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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

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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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