Zyte’s 2025 review: Year of locks and unlocks

At the end of one of the busiest, most exciting and disruptive ever years for the web industry, what can we extract, from the remains of 2025, about the business of data extraction?

The story of 2025 is one of competing pressures. As AI moved from theoretical promise to practical application, businesses and developers got more powerful tools - yet faced increasingly sophisticated obstacles.

This year's developments suggest that the future of web scraping belongs to those who can surf these trends with technical skill but also strategic foresight.

Large Language Models (LLMs) began to become a genuine part of web scraping workflows.

Models matter. Benchmarking exercises conducted throughout 2025 demonstrate that modern LLMs can generate functional scraping code with varying degrees of accuracy and efficiency. The performance differences between models are substantial. That has real implications for production deployments.

In 2025, data engineers finally found ways to embrace AI in scraping while remaining in control of their data pipelines. That involved tooling like Zyte's Web Scraping Copilot, a code-first AI assistant embedded directly in the developer's workflow. It’s traditional, familiar scraping, accelerated.

Read our coverage:

• Introducing Web Scraping Copilot - A rocket boost for data extractors

• Partial autonomy, full control: Why we built Web Scraping Copilot

• Why AI agents struggle with web scraping (and how to help them)

• New in Zyte: Web Scraping Copilot, LLM-friendly text, MCP scraping

• Gemini 3.0 Pro is the new best model for writing scrapers

• Why "Full Control" May Be an Illusion - And How AI-Powered Scraping Gives You More Control, Not Less

• AI Delegation vs. AI DIY in Web Scraping

As extraction tools became more capable, so did the defensive measures deployed against them.

Websites employed increasingly sophisticated bot detection, behavioral analysis, and dynamic content delivery mechanisms.

Zyte’s Extract Summit heard how many websites adopted a more nuanced, score-based approach to blocking data gatherers, including building a profile of a user’s journey over time.

Essentially, the technical obstacles became more diverse - by the end of 2025, new bot protection methods, changes to search result displays and new, infrastructure-level access restrictions all posed new challenges to web scraping.

Read our coverage:

• Beyond the block: The front line of data access

• Why your spiders keep getting banned, and how to fix it

• Unblockers vs Zyte API: What's the Real Cost of Bans?

• How an analytics platform solved a 'hard-to-scrape' site using Zyte API

• Zyte leads the pack in Proxyway's 2025 Web Scraping API Report

• Getting Past Geoblocks: Why Your Scraper Needs More Than Just a Proxy

• The Problem With XPath, CSS Selectors, and Keeping Your Scraper Alive

The legal environment surrounding data extraction became a little more defined in 2025, with court decisions providing new clarity on copyright, trademark, and fair use principles.

With laws and best practice on web scraping at large having been codified some time ago, application of scraped data for AI services took centre-stage as the industry’s leading legal debate.

With the UK ruling in Getty v. Stability, a new EU AI Act and new guidance on the topic from the United States Copyright Office, the contours for acceptable web data use came into sharper focus.

Read our coverage:

• Key takeaways from the Getty v. Stability AI UK ruling

• Balancing innovation and regulation in data scraping

• Web scraping as social practice: Ethics and efficiency in a data-hungry world

• Scraping a synthetic web: Dead Internet Theory meets web data extraction

• Crawl with care: How to gather AI training data sustainably

• Sustainability in Open Source Software, According to Creators of PhantomJS and Scrapy

• The preservationists: Meet the data collectors racing to save the web

While publishers in 2025 were offered new infrastructure to help govern bot access to their sites - a signal of a potential new economic ecosystem emerging - the economics of web data extraction itself got unlocked.

Growing popularity of web scraping APIs lowered cost barriers to entry, making web scraping accessible to smaller teams and organizations with more modest budgets. Extraction using one, AI-powered API call is a radical change from the days of manually orchestrating an entire stack of code.

So, the application of web data became more diverse. More than just software, web data is now powering a new wave of data-driven software business.

Read our coverage:

• The new economics of web data: Smaller scraping just got cheaper

• Why the Best Engineers Are Actually Lazy

• Extract clean content automatically with Zyte API's new pageContent data type

• How to build a daily industry news digest

• Why your agent deserves a wallet

• Five key takeaways from Extract Summit 2025

• How an Open Source Tool from a Small Startup Became the Backbone of Web Scraping

• The D&D of data: A scraper's quest for the web's hidden treasures

The developments of 2025 reveal an industry in transition. The convergence of more capable AI tools, more sophisticated access barriers, clearer legal frameworks, and shifting economics has created a new operating environment for web data extraction.

Success in this environment requires technical sophistication, strategic thinking about access infrastructure, and serious engagement with legal and ethical considerations.

However, on reflection, it feels like 2025’s trends were incremental steps, setting the stage for a more substantial shake-up in 2026.