Your LinkedIn profile is a detailed record of your professional life: where you’ve worked, what you’ve built, what you’ve written, who you’re connected to. It’s also, unless you’ve opted out, training data for generative AI models.
LinkedIn announced in September 2025 that it would use member data — including profile information, posts, and activity — to train its generative AI systems. The setting defaulted to on. Users who didn’t actively go looking for it didn’t know it was happening.
What LinkedIn Uses
According to LinkedIn’s published documentation, the data used for AI training includes:
- Profile information — job titles, company history, skills, education, and profile summaries
- Public posts — articles, status updates, shares, and comments you’ve published on the platform
- Engagement patterns — how you interact with content and which topics you consistently engage with
Private messages and direct InMail are excluded. LinkedIn has stated that the content of private conversations is not used for generative AI training.
The practical effect is this: if you’ve written detailed posts about your industry, built out a specific skills section, or documented complex work experience in your profile summary, that content is part of a training corpus that shapes how LinkedIn’s AI discusses those topics for other users. The model learns what professional content in your field sounds like, in part from content you wrote.
The Two Opt-Out Toggles
LinkedIn’s opt-out exists and is reachable, but it’s not prominently positioned in the settings interface:
- Go to LinkedIn.com and click your profile photo in the top right
- Navigate to Settings & Privacy
- Click Data privacy in the left sidebar
- Find Data for Generative AI Improvement
- Toggle off “Use my data for training content creation AI models”
- Toggle off “Use my data for training social intelligence AI models”
There are two separate toggles. If you turn off only one, the other continues. The naming of each toggle is different enough that it’s easy to assume they cover the same thing — they don’t.
For EU, EEA, and Switzerland users: LinkedIn began applying member data to AI training for these regions starting in November 2025. EU users benefit from stronger enforcement of their opt-out rights under GDPR, and LinkedIn’s compliance obligations in the region are more explicit.
The important limitation for all users: opting out stops future use of your data for training, but it does not retroactively remove data that was already used before you opted out. If LinkedIn’s systems ingested your posts before you found the setting, that content remains in whatever model it trained.
Why Professional Data Is Particularly Sensitive
A LinkedIn profile is different from a typical social media post in a specific way: it’s designed to be a complete professional biography. It documents not just what you’ve published but what you’ve done, for whom, in what roles, at what companies, over how long a period.
That specificity makes it valuable training data. It also makes the privacy implications different from what most people consider when they hear “AI training on social media.”
Someone who has written detailed LinkedIn posts about a specialized niche industry, documented a complex career transition, or shared experience from a sensitive field — healthcare administration, legal services, financial advising — has provided a level of professional context that is genuinely revealing. Industry-specific vocabulary, organizational knowledge, and career-stage signals are all embedded in a well-written LinkedIn profile.
The AI models trained on this data produce more realistic-sounding professional content because they’re trained on real professional content written by real people who are not compensated for that use.
What Changed After the Announcement
LinkedIn’s rollout generated significant backlash, primarily from users who noticed they had been opted in without a direct notification or consent moment. The criticism ran along several lines:
Consent architecture. Defaulting users into AI training without a clear acknowledgment moment at login or in a primary settings view is an opt-out architecture. Users who hadn’t changed their settings actively weren’t making an informed choice — they were simply not aware the setting existed. Proton, Malwarebytes, and Tuta each published separate guides walking users through the opt-out steps, which is a reasonable signal of how buried the setting was.
Retroactive data use. Once data has been used to train a model, opting out doesn’t remove it from training. Years of profile updates, articles, and posts that predated the announcement were already processed before most users knew the setting existed. There’s no mechanism to request that your past content be excluded from an already-trained model.
The EU exception. LinkedIn initially excluded EU users from AI training while it assessed whether its practices would comply with GDPR requirements. When it did extend AI training to EU users, the rollout included clearer disclosure and more explicit controls. The practical implication — that EU-style regulation produced meaningfully better consent practices — was noted by multiple observers. US users received less notification and fewer in-context prompts.
LinkedIn’s Stated Rationale
LinkedIn’s position is that using member data to improve its AI features ultimately benefits members: better job matching, more relevant content suggestions, smarter profile feedback, and more accurate skill endorsements.
The company also says its systems are designed not to reproduce specific users’ content verbatim, and that the training data shapes model behavior rather than being surfaced directly to other users in identifiable form.
Both of these claims are plausible and technically consistent with how large language model training typically works. But they don’t change the underlying fact that professional content you wrote for a specific context — career visibility within your network — is being used to train commercial AI systems for a different purpose, without a direct consent moment.
The Broader Pattern in Professional Tools
LinkedIn is the most visible example of a broader dynamic. Professional content — work histories, industry writing, specialized knowledge documented in digital form — is among the most valuable categories of training data for AI systems focused on workplace applications.
If you use other tools to document your professional life — notes apps, file storage, document platforms, productivity tools — the same question applies: do their terms of service allow user content to be used for AI training? Many do. The defaults in those systems, like LinkedIn’s, tend to favor collection unless you look for and change the setting.
Checking the terms before storing professionally sensitive content, and opting out of training data contributions when the option exists, is a practice worth applying across platforms, not just LinkedIn.
What to Do Right Now
Immediately:
- Follow the steps above to toggle off both LinkedIn AI training settings if you haven’t already
Within this week:
- Download a copy of your LinkedIn data to review what’s there: Settings & Privacy → Data Privacy → Get a copy of your data. LinkedIn lets you export your posts, messages, connections, and profile history
- Consider archiving or deleting LinkedIn articles you’d prefer not to contribute to AI training going forward, since future posts will be affected by your opt-out but past posts that were already ingested won’t be removed
Ongoing:
- Apply the same question to every productivity and storage tool you use professionally: who trains on your content, what’s the default, and where’s the opt-out?
The setting is available. The default was on. For most LinkedIn users who set up their profiles before September 2025, that default was quietly in effect for months before they had a chance to change it.