# Meta Expands Data Scraping Rights for AI Model Training

New commercial terms allow Meta to scrape business customer websites starting October 2026.

- **Source:** [www.theregister.com - Articles](https://brifing.si/source/2c34ea50-d341-4a10-925d-12c012a9ad10)
- **Published:** 2026-10-16
- **Topic:** [Data & AI](https://brifing.si/c/data-ai)
- **Original article:** <https://www.theregister.com/ai-and-ml/2026/10/16/meta-grants-itself-right-to-scrape-content-from-business-customers-for-model-training/5303658>
- **On Brifing:** https://brifing.si/s/a3baf8cc-3b58-4f26-9a75-2a0a12bd79b7

## New Data Collection Mandate

Meta is updating its commercial terms of service to authorize the scraping of content from websites linked to its business customers. Effective October 30, 2026, this policy allows the company to use automated software, including bots and crawlers, to index and collect data from domains associated with any business using Meta products.

## Scope of Affected Businesses

The policy applies to any entity utilizing Meta's commercial tools, including Ads Manager, Meta Business Suite, or product catalogs. With at least one million businesses currently using AI agents across WhatsApp and Messenger, the reach of this data harvesting initiative is extensive, impacting virtually every news publisher maintaining a Meta business account.

## Technical Data Retrieval Methods

Meta reserves the right to create test credentials and deploy various automated tools to retrieve, cache, and analyze content. These tools are designed to periodically pull updates from URLs and domains, ensuring the company can continuously feed its AI models and product features with fresh information gathered directly from its business customer base.

## Industry Backlash and Criticism

Danielle Coffey, CEO of the News/Media Alliance, condemned the policy as an abuse of market power. She argues that withholding audience access unless businesses consent to scraping is a bad-faith move. Industry leaders are questioning the legality of these terms, suggesting that businesses should carefully evaluate their intellectual property exposure under these rules.

## Procedural and Legal Challenges

Professor Eric Goldman highlights significant procedural concerns regarding how these terms are enforced upon existing relationships. He questions whether businesses have a genuine option to reject these changes without terminating their entire commercial engagement. The lack of clear exit strategies for prepaid customers raises further questions about the fairness of this contractual update.

## Trust and Historical Context

The skepticism surrounding this move is rooted in Meta's 22-year history of data harvesting controversies. Past incidents, such as the Cambridge Analytica scandal and social media addiction settlements, have severely depleted the company's reservoir of good faith. Consequently, observers are interpreting the broad language of these new terms in the worst possible light.

## Ambiguity of Robots.txt Compliance

While reports suggest Meta might respect robots.txt directives, the actual contractual language does not explicitly guarantee this. Legal experts note that there is no inherent legal requirement for companies to honor these files. Without an express commitment in the terms, businesses remain uncertain if they can effectively opt out of the scraping process.

## Implications for Future Relations

This development mirrors past contractual controversies where companies inadvertently overreached while attempting to solve specific technical problems. By prioritizing AI model training over established user trust, Meta risks further alienating its business partners. The outcome will likely depend on whether the company clarifies these terms or faces significant regulatory and legal pushback.

## Sources covering this story

- https://www.theregister.com/ai-and-ml/2026/10/16/meta-grants-itself-right-to-scrape-content-from-business-customers-for-model-training/5303658 — 

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_Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._
