AI Atlas:
Web Agents are Rewriting the Internet
Rudina Seseri
Clearly, the internet is one of the most transformative technologies in human history. Nearly 30 years after it became mainstream, it remains the backbone of modern life: both our largest source of information and primary communication network, as well as the foundation for countless business operations.
Furthermore, while businesses move fast, the internet moves faster. In the modern world, staying ahead of the constant flow of online information is harder than ever. This is why we see the rise of web agents, AI-powered tools that can browse websites and complete online tasks automatically. Because of the pace of digital acceleration, AI is the only thing capable of continuously keeping track of everything published online, and as of 2025, bots officially make up the majority of all internet traffic. As agentic capabilities grow more sophisticated, their impact will only expand in scope and magnitude.
🗺️ What are Web Agents?
In essence, a web agent is an AI system designed to navigate and interact with websites like a person would, from reading content to clicking on links and downloading data. What makes web agents especially powerful is their integration with LLMs, the transformer-based technology found in tools like ChatGPT. This architecture gives web agents the ability to understand context, resulting in more human-like decision-making. This means that AI agents on the web are capable of much more than simple data scraping, becoming increasingly indistinguishable from human operators.
🤔 What does this mean for today’s LLMs?
The rise in popularity of web agents has completely disrupted search, and with it the way we look at fundamental concepts such as SEO. For instance, traditional SEO is built on the assumption that humans click and scroll through websites, and optimizes for the keywords that would catch our attention. However, web agents do not behave like people; they navigate directly to the most relevant source of information and only extract exactly what they need. With machines now consuming the majority of content, businesses are needing to rethink how they present information to remain discoverable.
Web agents are only going to become more and more popular, in large part because of their ease of use and clear ROI, including:
- Time and cost savings: Web agents automate manual digital tasks, enabling human teams to focus on higher-value work.
- Real-time decision support: These agents are able to constantly pull fresh data from online sources, monitoring digital channels such as social media and stock markets so that businesses can react quickly to changes.
- Scalability: Web agents can handle increasing volumes of online data without adding more staff, and the entire internet is already within our reach. In fact, DeepL just announced that, by using NVIDIA’s new chips, they are able to translate every website in just a matter of days.
However, this new paradigm in how we use the web also has many areas for improvement:
- Security: Per recent research from the University of Maryland, web agents actually demonstrate greater vulnerability compared to standard LLMs because they are designed to be more flexible, and thus are more exposed to malicious manipulation.
- Data quality: For anything pulling data from the internet, misinterpreting or extracting outdated/inaccurate information can lead to bad decisions if results are not validated. Furthermore, as a greater percentage of original content on the internet becomes AI-generated, this problem is likely to worsen.
- Regulatory concerns: Web agents are a significant driver of the rise of deepfakes and misinformation across the internet. AI could perhaps also be a mitigator for this noise, for example by training them to prioritize recognized sources of truth. Nevertheless, enterprises building out web agent interaction need to keep in mind privacy laws and ethical guidelines, especially when dealing with user data.
🛠️ Use Cases of Web Agents
Web agents are already being used across industries to improve productivity and accelerate decision-making, including applications such as:
- Market intelligence: Web agents can scrape the web across multiple sources to monitor the news, track competitors, and anticipate regulatory changes without manual tracking.
- Lead gen: AI agents are used to automatically collect public information on leads and prospects to enrich sales pipelines.
- Productivity: Autonomous AI systems are leveraged to fill out repetitive forms, seamlessly validate compliance requirements, and streamline back-office workflows.
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