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Artificial Intelligence (AI)-Driven Web Scraping Market Outlook Indicating Growth to $23.7 Billion by 2030

April 8, 2026 by Marketing Posting

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

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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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