LinkedIn confirms training its AI on user data by default, and says it is “making sure that those who have specific privacy preferences” can opt out
LinkedIn is using its users' data for improving the social network's generative AI products, but has not yet updated its terms …
Context & Ripple Effects
LinkedIn had already introduced OpenAI-powered assistance across learning, marketing, sales and recruiting in its initial wave of AI workplace tools. This disclosure identifies the platform’s user activity as an input to improving the generative products built around those workflows.
The policy choice also sits alongside Slack’s earlier confirmation that some AI features used customer content under a default-on approach, while distinguishing its generative tool from that training practice. The common issue is not merely adding AI features, but defining what user-contributed material can become model input.
First-order effects
- LinkedIn users are opted into having their data used to improve the company’s generative AI products unless they set the available privacy preference to opt out.
- LinkedIn gains a larger default pool of platform data for product improvement, while its privacy controls become the immediate mechanism for users who object.
Second-order effects
- The disclosure raises the burden on other workplace and professional platforms to state clearly whether AI training is separate from feature delivery and whether participation is default-on.
- For recruiters, marketers and other professional users, confidence in sharing platform content may become more dependent on understandable controls, not only on the usefulness of LinkedIn’s AI features.
Third-order effects
- If default-on training becomes common across work platforms, consent design will become a competitive and policy fault line: services with extensive user-generated data can improve AI products faster, but face greater pressure to make permission boundaries legible.
- The longer-term distinction may shift from whether platforms use content for AI at all to whether users can meaningfully control reuse of material they created for a different purpose.
The trend: Professional software platforms are turning the content and activity already generated in their networks into inputs for workflow AI, making data permissions part of product strategy.