The no-code web scraping tool market is experiencing robust growth, driven by the increasing demand for automated data extraction across diverse sectors. The market's expansion is fueled by several key factors. Firstly, the rise of e-commerce and the need for competitive pricing intelligence necessitates efficient data collection. Secondly, the travel and hospitality industries leverage web scraping for dynamic pricing and competitor analysis. Thirdly, academic research, finance, and human resources departments utilize these tools for large-scale data analysis and trend identification. The ease of use offered by no-code platforms democratizes web scraping, eliminating the need for coding expertise, and significantly accelerating the data acquisition process. This accessibility attracts a wider user base, contributing to market expansion. The market is segmented by application (e-commerce, travel & hospitality, academic research, finance, human resources, and others) and type (text-based, cloud-based, and API-based web scrapers). While the market is competitive, with numerous players offering varying functionalities and pricing models, the continued growth in data-driven decision-making across industries assures continued expansion. Cloud-based solutions are expected to dominate due to scalability and ease of access. Future growth hinges on the development of more sophisticated no-code platforms offering enhanced features such as AI-powered data cleaning and intelligent data analysis capabilities. Geographic regions like North America and Europe currently hold significant market share, but Asia-Pacific is poised for substantial growth due to increasing digital adoption and expanding e-commerce markets. The historical period (2019-2024) likely witnessed a moderate growth rate, setting the stage for the accelerated expansion projected for the forecast period (2025-2033). Assuming a conservative CAGR of 15% for the historical period, resulting in a 2024 market size of approximately $500 million, and applying a slightly higher CAGR of 20% for the forecast period, reflects the increasing adoption and sophistication of these tools. Factors such as stringent data privacy regulations and the increasing sophistication of anti-scraping measures present potential restraints, but innovative solutions are emerging to address these challenges, including ethical data sourcing and advanced proxy management features. The ongoing integration of AI and machine learning capabilities into no-code platforms is also expected to propel market growth, enabling more sophisticated data extraction and analysis with minimal user input.

Snapshot img

AI Driven Web Scraping Market Size 2025-2029

The AI driven web scraping market size is valued to increase USD 3.16 billion, at a CAGR of 39.4% from 2024 to 2029. Surging demand for data-driven insights and business intelligence will drive the ai driven web scraping market.

Major Market Trends & Insights

North America dominated the market and accounted for a 38% growth during the forecast period.
By Type - Dynamic scraping segment was valued at USD 82.90 billion in 2023
By Application - E-commerce and retail segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 1.00 million
Market Future Opportunities: USD 3159.00 million
CAGR from 2024 to 2029 : 39.4%

Market Summary

The AI-driven web scraping market is experiencing significant growth, fueled by the increasing demand for data-driven insights and business intelligence. The rise of Large Language Model (LLM) and the democratization of web scraping through no-code and low-code platforms are key drivers, enabling businesses to extract valuable data from the web more efficiently and effectively than ever before. These advancements enable businesses to extract valuable data from the web more efficiently and effectively than ever before. However, this growth comes with challenges. The sophistication of anti-scraping technologies is escalating, requiring advanced techniques and technologies to bypass these barriers.
According to recent estimates, the global web scraping market is projected to reach USD12.5 billion by 2027, underscoring its growing importance in the digital business landscape. Despite these challenges, the future of AI-driven web scraping is bright, offering businesses a powerful tool to gain a competitive edge in today's data-driven economy.

What will be the Size of the AI Driven Web Scraping Market during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the AI Driven Web Scraping Market Segmented ?

The ai driven web scraping industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Dynamic scraping
  Static scraping
  API-based scraping


Application

  E-commerce and retail
  Finance and banking
  Market research
  Cyber security
  Others


Deployment

  Cloud-based
  On-premises
  Hybrid


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Type Insights

The dynamic scraping segment is estimated to witness significant growth during the forecast period.

The AI-driven web scraping market continues to evolve, with the services segment, or Data as a Service (DaaS,) gaining significant traction. In this model, clients outsource the entire data acquisition process to specialized companies, specifying their data requirements, including target websites and desired data fields, while the service provider manages the technical aspects. This approach is ideal for organizations lacking the in-house expertise, infrastructure, or time for complex web scraping operations. The integration of artificial intelligence is crucial for scalability and efficiency, enabling distributed scraping systems, data validation rules, and data visualization dashboards. Machine learning models power link extraction techniques, image recognition algorithms, and natural language processing, while proxy server management, unstructured data processing, and data cleaning pipelines ensure legal compliance frameworks.

Data transformation rules and structured data parsing facilitate API integration strategies, and headless browser automation, error handling mechanisms, and rate limiting protocols maintain ethical scraping guidelines. The market's growth is evident in the 50% annual increase in companies using cloud storage solutions for data storage and real-time data streaming.

Request Free Sample

The Dynamic scraping segment was valued at USD 82.90 billion in 2019 and showed a gradual increase during the forecast period.

Request Free Sample

Regional Analysis

North America is estimated to contribute 38% to the growth of the global market during the forecast period.Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

See How AI Driven Web Scraping Market Demand is Rising in North America Request Free Sample

The market is experiencing significant growth and evolution, with North America leading the charge. This region, particularly the United States, boasts the largest and most mature market due to its advanced technological infrastructure, the presence of leadi