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You Can Now Get Paid To Train LinkedIn’s AI

  • LinkedIn Strategy
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LinkedIn is taking a new approach to building better AI; it’s recruiting members to help label and annotate data.
 

Instead of relying only on anonymous contractors, LinkedIn will invite professionals to apply their industry expertise to create high-quality, human-labelled training data, and yes, you can get paid for it.
 

This isn’t just manual tagging.

LinkedIn says it will vet applicants to make sure their background matches the annotation tasks, using profile details (education, licenses, work history) and an AI-driven conversational interview to verify expertise.
 

Learn more about the program on LinkedIn’s help page.

 

How the process works

 

Profile-based vetting and AI interviews

 

If you express interest, LinkedIn may use an AI-powered conversation to ask about your professional background and assess whether you’re the right fit for specific annotation projects.

 

The platform uses that information to match you with tasks that need specialized knowledge — for example, medical, legal, or financial labeling.

 

Annotating industry-specific data

 

Once matched, you’ll annotate examples so AI systems learn how people in your profession refer to tools, products, outcomes, and context.

 

This helps AI models provide more accurate recommendations, search results, and professional insights across LinkedIn, and potentially for other companies that license training data.

 

Why this matters (and why it’s complicated)

 

Benefits for professionals and AI quality

 

  • Earn flexible, skill-based income by applying domain knowledge.

 

  • Improve AI understanding of niche terms and context, leading to better matches and recommendations.

 

  • Receive personalized feedback, LinkedIn may suggest profile improvements based on the interview.

 

Ethical and career considerations

 

There’s a tension here: by training AI, experts could also be helping build systems that automate parts of their own jobs.

 

The conversation about fairness, pay, and long-term impacts of AI labor is ongoing — see a deeper dive into the industry’s reliance on human labelers in this article from The Conversation.

 

What to consider before you sign up

 

  • Confirm what tasks you’ll do, and how much you’ll be paid per assignment.

 

  • Understand how your interview data will be used, LinkedIn says it will supplement your profile information to match you to projects and suggest profile updates, and will not use that info for other purposes without permission.

 

  • Think about long-term implications for your role and industry.

 

LinkedIn’s approach leverages its unique access to professionals across industries to create higher-quality, specialized training data.

 

For people who want flexible income and enjoy applying domain expertise, it’s an attractive option, but it’s reasonable to weigh the potential trade-offs for your career.

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Document Posts Now Outperform Every Other LinkedIn Format The biggest finding from the Socialinsider study is that native document posts have overtaken all other content types for engagement. As Social Media Today reported, this is a significant departure from other social platforms where short-form video dominates. Here is how each format performed based on average engagement rate by impressions in 2025: Native documents: 7.00% (up 14% year-over-year) Multi-image posts: 6.45% Video: 6.00% (up 7% YoY) Image: 5.30% (up 9% YoY) Text: 4.50% (up 12% YoY) Poll: 4.20% Link: 3.25% The year-over-year trend is notable. Engagement grew across every content format except polls and links. Document posts saw the largest increase at 14%, but even simple text posts climbed 12%. LinkedIn users are engaging more across the board. Julia Holmqvist, Social Media Manager at Semrush, explained the document trend well in the Socialinsider report: documents perform because they deliver downloadable, practical value like frameworks, templates, and checklists in a format that is easy to scan and save for later. This aligns with what LinkedIn's own algorithm now rewards: dwell time. Document carousels require swiping through multiple slides, which keeps users on the post longer than almost any other format. That extended attention signals quality to the algorithm and triggers broader distribution. Multi-Image Posts Drive the Most Likes While documents lead on overall engagement rate, the data shows a different winner for likes specifically: multi-image posts generate the most likes across every page size. For pages with 100K to 1M followers, multi-image posts average 180 likes per post compared to 155 for video and 30 for native documents. The pattern holds for smaller pages too, though at lower absolute numbers. This creates a useful strategic distinction. If your goal is overall engagement (comments, shares, saves, clicks), prioritise documents. If your immediate goal is social proof through visible like counts, multi-image posts are your best option. For employee advocacy content, this distinction matters. Employees sharing document carousels will generate deeper engagement that drives profile visits and conversations. Employees sharing multi-image posts will generate higher visible reaction counts that build credibility in the feed. Both have a place in a well-rounded advocacy programme. Video Views Are Declining Despite More Video Being Posted One of the most counterintuitive findings in the data is that LinkedIn video views dropped 36% year-over-year across all page sizes, even as brands doubled their video posting frequency from 2 to 4 posts per month. The decline is consistent across every audience tier. Pages with 10K to 50K followers saw average video views drop from 1,000 to Even the largest pages (100K to 1M followers) saw views fall from 2,430 to 1,This does not mean video is dead on LinkedIn. Video still generates a 6.00% engagement rate, which is above the platform average. But it does suggest that the market is saturated with video content, and the returns are diminishing as more brands compete for attention in the same format. The Socialinsider report includes a useful insight from Semrush's social team: LinkedIn is not a video-first platform the way TikTok or Instagram are. Users do not open LinkedIn to scroll through video feeds. They come for professional knowledge sharing, and the formats built for that purpose (documents, text, images) are outperforming video on the metrics that matter. For employee advocacy, this reinforces the case for document carousels and well-crafted text posts over video. 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    Best LinkedIn Tools for B2B Marketing: A Complete Guide by Category

    Quick answer: The best LinkedIn tools in 2026 are not one product but a small stack chosen by job: analytics and measurement to prove what works, AI content creation to publish consistently in an authentic voice, employee advocacy to extend reach through your people, and scheduling to keep it all running. The right combination depends on whether your priority is reach, content quality, or proving return. This guide breaks the market down by category so you can pick the right tool for each job rather than forcing one platform to do everything. TL;DR LinkedIn is the dominant B2B channel: according to LinkedIn, it drives around 80% of all B2B leads that come from social media, and four out of five members influence business decisions at their organisation. The advantage sits with individuals, not brand pages. 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Most teams need two or three of these categories, not all of them: Analytics and measurement to see what is working and prove return AI content creation to publish consistently without it feeling corporate Employee advocacy to extend reach through your team's networks Scheduling and publishing to stay consistent without manual effort Engagement and social selling to turn visibility into conversations Native LinkedIn tools that the platform provides directly The sections below cover each category, what to look for, and the tools worth knowing. We will expand the named picks in each category over time. LinkedIn analytics and measurement tools This is the category that determines whether everything else is working. Most LinkedIn tools report at the company-page level, which hides the data that actually matters: how each individual's content performs, and what that activity returns. What to look for: profile-level reporting (reach and engagement per person, ideally including in-network versus out-of-network reach), and crucially, data pulled through LinkedIn's official API rather than browser-extension scraping. This matters more in 2026 than it used to, because a wave of scraping-based analytics tools lost access as LinkedIn enforced its anti-scraping policies. Official-API tools kept working; the workarounds broke. Featured: Vulse Vulse is a LinkedIn-native advocacy and analytics platform built around individual, profile-level measurement using LinkedIn's official API. Rather than aggregate company-page numbers, it shows reach and engagement per person, so B2B teams can see who is actually driving results and prove return at the individual level. It also includes AI tone-of-voice post drafting, scheduling and a participation leaderboard, but the differentiator is the analytics layer and the compliant, official-API data behind it. Best for: B2B teams, roughly 25 to 200 people, that want to prove advocacy and content are working at the individual level, and that prioritise compliant data over scraping-based tools. You can read more on LinkedIn analytics and how to measure advocacy ROI. AI content creation tools The single biggest barrier to LinkedIn success is consistency, and the biggest barrier to consistency is the blank page. AI content tools solve this, but the 2026 differentiator is whether the AI produces something that sounds like the individual or something that reads like corporate filler. What to look for: AI that learns each person's voice and writing style, so the output feels authentic rather than templated. Generic content shared identically across many profiles looks like spam and performs like it. Featured: Bloomberry Bloomberry is an AI-native platform that generates original LinkedIn posts in each employee's individual voice. 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Employee advocacy platforms Employee advocacy tools help organisations get their people sharing company content on their own profiles, extending reach far beyond the brand page. This is a large category in its own right, with platforms ranging from legacy enterprise distribution tools to newer, more individual-voice approaches. Because the choice here is nuanced, we cover it in depth separately. See our dedicated guide to the best employee advocacy tools for a full comparison of the platforms, their pricing, and their trade-offs. The short version: the older platforms are built around distributing approved brand content for employees to reshare, while the 2026 direction is toward original, voice-matched employee posts and individual-level measurement of what that activity returns. Scheduling and publishing tools Consistency is the strongest predictor of LinkedIn growth, and scheduling tools remove the friction that breaks consistency. These let you draft, queue and publish posts at optimal times rather than posting manually and inevitably falling off. What to look for: reliable native LinkedIn publishing (not workarounds that risk reach), optimal-time recommendations, and a content calendar that a team can plan against. Many of the analytics and AI tools above include scheduling, so a standalone scheduler is often unnecessary if your chosen platform already covers it. Featured: Supergrow Supergrow is a LinkedIn-first platform that pairs content creation with scheduling. Beyond queuing posts, it gives teams a content board for drafts, approvals and scheduled publishing, plus voice-to-post and AI-guided drafting so employees can keep a consistent cadence without writing from scratch. It is LinkedIn-only by design, so teams wanting multi-platform scheduling will need a broader tool, but for a LinkedIn-native content and scheduling workflow it is a strong fit. Best for: teams that want LinkedIn scheduling tied to content creation, rather than a general multi-platform scheduler. Engagement and social selling tools Visibility without engagement is a billboard. Engagement tools focus on what happens after content is posted: the strategic commenting, profile visits and conversations that turn impressions into pipeline. This category overlaps with social selling, where individual reps use LinkedIn to build relationships and surface opportunities. What to look for: compliant engagement methods that LinkedIn rewards rather than penalises, and clear tracking from engagement activity through to inbound interest. Approaches that automate aggressive outreach carry account-risk, so weigh compliance carefully. We will add named picks to this category over time. Design and visual content tools LinkedIn rewards native visual content: carousels (document posts) and clean graphics consistently outperform plain text for many teams. Canva is the most widely used tool here, with LinkedIn-sized templates for carousels, single images and banners, so non-designers can produce on-brand visuals quickly. For written polish, Grammarly helps keep posts clear and error-free before they publish. Neither replaces an advocacy or analytics platform; they sit alongside one and improve the quality of what your team puts out. Native LinkedIn tools Before buying third-party software, know what LinkedIn provides directly. LinkedIn Marketing Solutions includes the platform's own analytics, Lead Gen Forms (which pre-fill professional data and convert well above typical landing pages), and Sales Navigator for prospecting. Native LinkedIn analytics are limited at the individual level, which is precisely the gap that profile-level tools like Vulse exist to fill, but for company-page reporting and advertising, the native tools are the baseline. 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A practical 2026 stack looks like this: Foundation: native LinkedIn analytics and Lead Gen Forms for the company page and any advertising. Content: an AI content tool so your people publish consistently in their own voice. Reach: an advocacy approach that activates employees beyond the brand page. Proof: a profile-level analytics layer so you can see who is driving results and justify the investment. The two pieces teams most often underbuild are authentic content creation and individual-level measurement. Get those two right and the rest tends to follow, because consistent, authentic posting is what the platform rewards, and clear measurement is what keeps the programme funded. Frequently asked questions What are the best LinkedIn tools for B2B in 2026? There is no single best tool, because the category covers different jobs. The strongest stacks combine analytics and measurement, AI content creation, employee advocacy and scheduling. Choose by the job you are solving rather than looking for one platform to do everything. What is the most important LinkedIn tool category? For most B2B teams, the two highest-leverage categories are AI content creation (to publish consistently and authentically) and profile-level analytics (to prove what works). These are also the two categories teams most commonly underbuild. Why does official LinkedIn API access matter for analytics tools? Because tools built on browser-extension scraping became fragile and lost access as LinkedIn enforced its anti-scraping policies. Tools using LinkedIn's official API, such as Vulse, kept working and offer compliant, stable data. It is now a genuine buying criterion. Do I need separate tools or one platform? Most teams use two or three tools across categories. Some platforms bundle several jobs (Vulse pairs analytics with AI drafting and scheduling, for example), which can reduce the number of vendors. Map your needs to categories first, then look for overlap. Are LinkedIn's native tools enough on their own? For company-page reporting, advertising and prospecting, the native tools are a solid baseline. But native analytics are limited at the individual level, which is where third-party profile-level tools add the most value for B2B teams focused on employee-driven reach. Prove what your LinkedIn activity is actually doing The two things most LinkedIn programmes underbuild are authentic content and individual-level measurement. Vulse covers the measurement gap with profile-level analytics built on LinkedIn's official API, so you can see reach and engagement per person and prove return rather than guessing from company-page numbers. Start there, and build the rest of your stack on evidence.

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    Best LinkedIn Tools for B2B Marketing: A Complete Guide by Category

    by - Rob Illidge -

Revolutionise Your LinkedIn Output Today

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