As AI-generated content continues to spread across the internet, LinkedIn is rolling out new tools to help users identify and flag low-quality, AI-produced posts on its platform.

On Thursday, the professional networking site introduced a "Seems like AI slop" button, accessible through a post's options menu. The feature allows users to report content they believe is low-quality or overly reliant on AI generation. The move is notable for a platform whose core value proposition relies on professional trust and authentic career-related interaction, where formulaic AI-generated posts risk eroding user engagement over time.

"Slop is hard to define and the definition changes; this lets us tune our models and make better feeds," said LinkedIn Chief Product Officer Hari Srinivasan in a post announcing the feature.

LinkedIn is also removing its "enhance your post" tool, replacing it with a proofreading feature designed to correct posts without altering a user's voice. The company is simultaneously reinforcing profile and page verification systems.

On the bot-detection front, Srinivasan said LinkedIn now identifies and blocks hundreds of thousands of automated slop comment attempts each day. The platform has also prevented "billions of other automation attempts (posting at scale, slop) in the last couple months alone," he wrote.

Srinivasan acknowledged that AI use is not inherently problematic, noting that many people use it to refine their writing. The new tool will also alert users when their own posts sound "inauthentic."

"AI slop is a top priority for all of us. We really care about this," Srinivasan said.

The new measures arrive amid a surge of AI-written content online following the release of ChatGPT in 2022. A recent study by AI text detection tool Pangram found that 40% of long-form posts and 30% of short-form posts on LinkedIn were flagged as fully AI-generated. Such detection tools have faced documented accuracy challenges, including false positives and circumvention by newer models, which is partly why platforms like LinkedIn are complementing automated detection with crowdsourced user reporting.

When contacted for comment, a LinkedIn spokesperson directed Fortune to Srinivasan's public post.

Broader Industry Response to AI Content

Other platforms are also taking steps to address AI-generated material, and their responses are diverging sharply. Snapchat announced on Friday that it would no longer recommend fully AI-generated videos through its Spotlight feature, which surfaces content from users across the app. The restriction will not apply to videos edited or enhanced using Snapchat's own AI creative tools, though those videos will carry transparency indicators.

"As low-quality, repetitive, AI-generated content becomes increasingly common across the internet, we want Spotlight to remain a place where people can discover authentic creativity from real people," Snapchat said in a statement.

Meta, by contrast, has embraced AI-generated content by developing its own family of generative media models. Earlier this month, the Facebook and Instagram parent company launched Muse Image, which creates AI-generated images based on references "including people, objects, clothing, styles, and environments."

Alongside Muse Image, Meta released a preview of Muse Video, allowing users to produce AI-generated video. Images created with Muse Image include an invisible watermarking system called "Content Seal" that can identify them even when cropped, resized, or screenshotted. Meta plans to extend Content Seal to Muse Video in the near future.

During Meta's second-quarter earnings call, CEO Mark Zuckerberg said Muse Image and Muse Video would "dramatically expand the universe of content that people can discover across our platform."

"This is going to make our services a lot more useful and engaging for people," Zuckerberg said during his prepared remarks.

The divergent approaches come as regulators are also weighing in. The European Union's AI Act, which began phased implementation in 2025, includes transparency obligations requiring providers of AI systems to label certain AI-generated content, adding a compliance dimension to the choices platforms are now making about detection, labeling, and watermarking.

This story was originally featured on Fortune.com.