AI-Driven Web Scraping Market Report 2026

The artificial intelligence (AI)-driven web scraping market size has grown exponentially in recent years. It will grow from $8.24 billion in 2025 to $10.2 billion in 2026 at a compound annual growth rate (CAGR) of 23.8%. The growth in the historic period can be attributed to increasing digital data volumes, growing e‑commerce activity, rising demand for competitive intelligence, expansion of cloud‑based scraping solutions, and growing adoption across sectors.

The artificial intelligence (AI)-driven web scraping market size is expected to see exponential growth in the next few years. It will grow to $23.7 billion in 2030 at a compound annual growth rate (CAGR) of 23.5%. The growth in the forecast period can be attributed to increasing demand for real‑time business intelligence, rising adoption of artificial intelligence and machine learning technologies, growing need for dynamic pricing and market monitoring, expansion of no‑code/low‑code scraping platforms, and growing demand from small and medium enterprises. Major trends in the forecast period include technology advancements in artificial intelligence (AI) and machine learning, innovation in automated data extraction tools, developments in cloud‑native and scalable scraping platforms, research and development in anti‑bot evasion and proxy networks, and increasing integration with real‑time analytics and decision‑making systems.

The increasing adoption of AI-powered decision-making tools is anticipated to drive the expansion of the artificial intelligence (AI)-driven web scraping market in the coming years. AI-powered decision-making tools are software solutions that leverage artificial intelligence, including machine learning and predictive analytics, to automate and optimize business decisions and insights. This growth in adoption is driven by the ongoing digital transformation of enterprises and the growing demand for data-driven strategic decision-making. Artificial intelligence (AI)-driven web scraping supports AI-powered decision-making tools by automatically gathering and organizing large amounts of real-time data from various online sources. It enhances analytical precision and speed by providing machine learning models with current insights, enabling quicker, data-informed strategic decisions. For example, in January 2025, according to Eurostat, a Luxembourg-based statistical office of the European Union, 13.5% of enterprises with 10 or more employees utilized AI technologies in 2024, up from 8% in 2023, reflecting a 5.5 percentage-point increase. Consequently, the growing adoption of AI-powered decision-making tools is fueling the expansion of the artificial intelligence (AI)-driven web scraping market.

Major companies in the artificial intelligence (AI)-driven web scraping sector are concentrating on creating advanced platforms, including AI-powered low-code tools, to improve efficiency, increase accessibility, and minimize technical challenges and development time. AI-powered low-code tools are platforms that leverage artificial intelligence to automate the extraction and organization of web data using natural language instructions, removing the requirement for manual coding. For example, in July 2025, Oxylabs.io, a Lithuania-based web intelligence and proxy services provider, introduced AI Studio. This new suite of AI-powered tools is designed to simplify the process of finding, collecting, and preparing web data through natural language prompts. It features AI-Crawler and AI-Scraper functionalities, allowing smooth data extraction from multiple or single web pages without manual intervention. Additionally, it includes tools such as Browser Agent for dynamic interactions and AI-Search for web queries, expanding the platform’s capabilities and reducing operational complexity for developers, product teams, and data analysts.

In June 2025, Oxylabs Group, a Lithuania-based provider of web intelligence acquisition tools and proxy services, acquired ScrapingBee for an undisclosed amount. Through this acquisition, Oxylabs Group intends to strengthen its position in the web scraping sector by incorporating a leading direct-to-consumer API product recognized for its user-friendliness and high-quality data extraction capabilities. ScrapingBee is a France-based software company offering an AI-powered web scraping API that manages headless browsers and proxy rotation for developers.

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.

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. The countries covered in the artificial intelligence (AI)-driven web scraping market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

Tariffs have impacted the ai-driven web scraping market by increasing the cost of cloud infrastructure, software licenses, and hardware components needed for efficient scraping and data processing. regions such as north america and europe, which are heavily reliant on imported cloud solutions and ai software, are most affected. segments like cloud-based deployment and dynamic web scraping face higher operational costs due to these tariffs. however, the tariffs are also encouraging local software development and adoption of cost-optimized, in-house scraping solutions, providing new growth opportunities.

Artificial intelligence (AI)-driven web scraping is a sophisticated technique for automatically gathering, analyzing, and extracting structured data from websites using machine learning, natural language processing, and smart automation. Its goal is to facilitate quicker, more precise, and scalable data collection for insights, analytics, and decision-making across various sectors.

The primary scraping types in AI-driven web scraping include static scraping, dynamic scraping, API scraping, and image and text recognition scraping. Static web scraping involves extracting data from web pages where content remains fixed and does not change dynamically. Deployment types include on-premises, cloud, and hybrid environments. Organization sizes include small, medium, and large enterprises. Applications include price monitoring, market intelligence, lead generation, and data mining, across industries such as e-commerce, financial services, healthcare, manufacturing, retail, and technology.

The artificial intelligence (AI)-driven web scraping market consists of revenues earned by entities by providing services such as artificial intelligence (AI)-powered data extraction, automated web crawling, website content monitoring, real-time competitive intelligence gathering, and large-scale data aggregation services. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI)-Driven Web Scraping market also includes sales of artificial intelligence (AI)-based scraping software tools, intelligent crawlers, automated data parsing engines, web data APIs, and cloud-based scraping platforms.

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 that 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.

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