AI Web Scraping on the Rise, Should Companies Block It or Welcome It?

As generative AI technology becomes more advanced, it is increasingly web-scraping content to supply big language models. For businesses, this raises a new question: Are AI bots welcomed as a source of traffic and visibility, or repelled as digital intruders?

A recent study by Liquid Web surveyed over 500 developers and business owners to find out how companies are responding to AI-driven web scraping. The outcome reflects a divide in the digital world. While some are gaining visibility and income from AI-driven referrals, others worry they are handing a competitive edge to their competitors.

This is what the information tells us about how businesses are dealing with this shifting target and what the trade-offs are.

AI Scraping: A Double-Edged Sword

The report provides that 43% of businesses believe AI scraping is benefiting their competitors more than their own businesses. However, 1 in 5 businesses report they've experienced an increase in revenue, with an average 23% increase in revenue due to AI-driven referrals.

AI scraping has also brought about greater exposure:

27% indicated increased interaction via AI-powered discovery tools and chatbots
26% observed more brand mentions in AI-created content
22% experienced an increase in direct traffic because of AI-driven search results

These numbers indicate a growing tension: AI can enhance exposure but can also strip individuals of control over how content is used, re-used, and monetized.

A Growing Divide: AI Bot Policies

More than half of organizations polled, (56%), have formal policies regarding how AI bots engage with their sites. Policies vary widely:

28% block AI bots completely
17% offer unlimited access
39% have partial restrictions based on the bot type, compliance, or value

Health, tech, and marketing industries are more likely to block access, with the focus on protecting content. At the other end, government, legal services, and hospitality industries are more likely to permit AI scraping.

Why Certain Companies Block AI Bots

The reasons to block scrapers are clear:

66% do it to protect intellectual property
62% intend to secure proprietary content
57% look to prevent AI models from using their data without consent

There are also perceived security advantages. 59% of those blocking AI bots report having more secure websites. It is not without cost, however: 28% had less search engine traffic, and 18% had a ranking decrease.

Why Others are Saying Yes to Scraping

On the other hand, there are businesses that see AI as the source of new traffic. 68% of firms that allow scraping mention increased AI search visibility as the most significant benefit. Other findings are:

51% saw improved web traffic
41% reported higher search rankings
45% observed increased brand awareness
42% saw SEO improvements

Nevertheless, 23% were concerned that competitors would gain from their openness, and nearly one-third saw no real effect either positively or negatively.

Legal Grey Areas and Ethical

The legality of web scraping is in a gray zone. Courts, for example, in the LinkedIn v. HiQ Labs case, have found that scraping public data doesn’t exactly violate federal law. That doesn’t eliminate risk, though. Litigation over terms of service, copyright law, and data privacy statutes like GDPR or CCPA still pose risk to businesses.

Ethical considerations are also taking hold of businesses as they struggle with how much transparency to provide. Policy scraping transparency is rare, and most companies are working out how to reconcile openness with data ownership.

SEO Benefits

Blocking scrapers has unforeseen SEO effects. By blocking the bots, businesses can become invisible from AI-produced summaries or answers. These are increasingly utilized by websites like Google, Perplexity, and ChatGPT.

The study suggests a compromise solution: allow Googlebot and Bingbot to have standard visibility, but exclude unwanted scrapers. Structured data added to the site's content can also affect the perception of AI models towards site content.

Technical Strategies for Monitoring and Regulating AI Bots

The report also contains a step-by-step guide for companies who wish to control bot access more accurately. It contains:

Behavioral monitoring and log analysis to detect unusual bot behavior
robots.txt rules, typically ignored by scrapers
CAPTCHAs, rate limiting, and JavaScript traps to filter out non-human traffic
Token-based or rate-limiting API authentication in order to have secure data delivery

Companies can also adopt bot fingerprinting. This recognizes bots based on interaction patterns and device settings.

Industry-Specific Strategies

The research emphasizes the way scraping affects industries differently:

Finance companies endanger real-time data exposure and are prone to restricting API access
Media outlets see referral traffic drop and may install paywalls or disclaimers
Ecommerce sites fear competitors scraping prices and supply levels
SaaS startups are faced with scrapers targeting feature sets or onboarding flows
Anti-scraping procedures need to be coordinated with industry-specific threats.

Final Takeaway: A Decision Framework for the Age of AI

Rather than a straightforward yes or no, research encourages a questioning spirit. Organizations must ask:

Is it proprietary or confidential?
Would referrals by AI generate trackable traffic or revenue?
Do we have the capability for effectively monitoring scraping?
Are we subject to obligatory compliance or privacy legislation?

For the majority, the best solution will be conditional access—blocking suspicious scrapers and allowing legitimate bots on controlled terms. As quoted by Liquid Web President Sachin Puri, “AI bots are bound to reshape the web. From customer behavior to decision to selection to success. This is a traffic and visibility problem but a big revenue opportunity powered by authentic and original content.”

AI web scraping has moved at such a speed that has taken it from a niche concern to a large challenge, and opportunity, for businesses. While large language models continue to redefine the way users discover and engage with online content, businesses are facing increasing pressure to decide how much of their online presence to expose to such systems.

Liquid Web's research results are indicative of a divided landscape. There are companies that are seeing real benefits from exposure to AI in traffic, rankings, and brand visibility overall. There are others, particularly those operating in verticals that handle sensitive or proprietary data, that are shifting to restrict or block AI scrapers altogether in order to maintain control and minimize risk.

Legal and ethical gray areas pose another hindrance, with much of the industry still not knowing what's compliant, safe, or sustainable. And while aggressive blocking can protect intellectual property, it can also suppress a brand's visibility on AI-powered discovery sites, as AI-driven search experiences become the norm.

For companies weighing their choices, a hybrid method appears to be the most practical. Allowing useful bots with organized information, rate limiting, and detection features could be a compromise between security and openness.

Lastly, no single fix will work for all situations. The optimal fix does vary by company' goals, risk tolerance, and technical capabilities. The one certainty is this, however: doing nothing is not an option. The web scraping performed by AI already has an effect on who is noticed, and who goes unnoticed, in the online environment.