We pulled every artificial intelligence post from a dataset of 12,988 LinkedIn posts and ranked them by engagement rate. 397 posts from 37 creators qualified. The median one earned 87 reactions and 7 comments, and the category tracks close to the cohort median for engagement per follower. Below are 12 of the highest-performing artificial intelligencehooks in the set, exactly as they appeared before LinkedIn's “see more” fold, plus what separates them from the artificial intelligence posts nobody read.
The short version
- Sample: 397 artificial intelligence posts from 37 creators.
- Median artificial intelligence post: 87 reactions, 7 comments (0.46 per 1,000 followers).
- Top-decile artificial intelligence posts run 60 comments at the median, against 7 for the category overall.
- The highest-lift hook style here: First-person opener.
How do artificial intelligence posts perform on LinkedIn?
Engagement rate here is (reactions + 4 × comments) ÷ followers, reported per 1,000 followers so accounts of different sizes can be compared. Comments carry four times the weight of reactions because they are scarcer and push a post into the commenter's own network.
| Measure | Artificial Intelligence posts | All posts in cohort |
|---|---|---|
| Posts analyzed | 397 | 12,988 |
| Creators | 37 | 65 |
| Median reactions | 87 | 122 |
| Median comments | 7 | 12 |
| Median rate per 1,000 followers | 0.46 | 0.4 |
Read that last row carefully. It says artificial intelligence content tracks close to the cohort median for engagement per follower, which is a statement about this cohort of 37 creators, not a law of the platform. Category averages move with who writes in them. What travels better is the pattern data below, because it compares posts against other posts by the same kinds of accounts.
What makes artificial intelligence posts different?
These are the ways artificial intelligence posts diverge most from the rest of the cohort. Each is a comparison of this category against all 12,988 posts.
- Artificial Intelligence posts open in first person more often. 17.1% of artificial intelligence posts start with I, my, or we, against 13.5% across the whole cohort (1.3x).
- These posts address the reader far less often. 23.2% put "you" or "your" in the visible hook, against 36.4% cohort-wide.
- Video is used less often for artificial intelligence. 9.3% of these posts are native video, against 12.4% cohort-wide.
- Hashtag stuffing is far more often here. 63.2% of artificial intelligence posts carry four or more hashtags, against 35% cohort-wide.
- Emoji appear far less often in these hooks. 1.8% of artificial intelligence hooks contain an emoji, against 6.1% cohort-wide.
Which hook style works best for artificial intelligence posts?
We sorted every artificial intelligencehook into five opening styles, then checked which styles are over-represented among the category's top-decile posts compared to the category as a whole. A lift above 1.0 means the style appears more often at the top than it does on average.
| Hook style | All artificial intelligence posts | Top decile | Lift |
|---|---|---|---|
| First-person opener | 17.1% | 25% | 1.46x |
| Question hook | 12.6% | 16.7% | 1.33x |
| Flat declaration | 67% | 58.3% | 0.87x |
| Direct address (you/your) | 2% | 0% | 0.00x |
| Number-led opener | 1.3% | 0% | 0.00x |
Sample sizes shrink fast once you slice a category by style, so treat the smaller rows as directional. The pattern that holds across every category we measured is the one in the full study: openers with a person in them beat openers with only a topic in them.
12 real artificial intelligence LinkedIn post examples
Every hook below is real, taken from a public dataset, and shown as the reader saw it before tapping “see more”. Author names are stripped. Engagement figures are lifetime totals at the time the data was collected, so treat them as relative signals rather than precise scores. Follower counts are included because a post that earns 400 reactions on 3,000 followers is doing something a post that earns 400 on 300,000 is not.
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Breaking down the three strongest artificial intelligence posts
#1: the flat declaration
31 reactions and 37 comments against 3,447 followers, a rate of 51.93 per 1,000. That is 129.8 times the cohort median. Notice the comment-to-reaction ratio: roughly one comment for every 1 reactions, which is unusually conversational. Posts like this are asking something the reader wants to answer, not performing for applause. The visible hook runs about 36 words, using nearly the full pre-fold allowance to build the setup. It ran with a shared article.
#2: the first-person opener
251 reactions and 15 comments against 6,299 followers, a rate of 49.37 per 1,000. That is 123.4 times the cohort median. This one earned reactions far more than replies, the signature of a post people agree with rather than argue about. That still travels, but it travels less far than a post that starts a conversation. The visible hook runs about 32 words, using nearly the full pre-fold allowance to build the setup. It ran with a shared article.
#3: the first-person opener
159 reactions and 86 comments against 19,101 followers, a rate of 26.33 per 1,000. That is 65.8 times the cohort median. Notice the comment-to-reaction ratio: roughly one comment for every 2 reactions, which is unusually conversational. Posts like this are asking something the reader wants to answer, not performing for applause. The visible hook runs about 38 words, using nearly the full pre-fold allowance to build the setup. It ran as native video, the format that over-indexes hardest among top performers.
The common thread is that none of the three resolve before the fold. The reader has to open the post to find out what happened, which is the entire mechanism behind a hook that works.
What format should you use for artificial intelligence posts?
Format mix for this category, next to the cohort. Cohort-wide, native video over-indexes about 2.6 times among top-decile posts while shared article links over-index in the bottom half, which is covered in detail in the piece on external links.
| Format | Artificial Intelligence posts | All posts |
|---|---|---|
| text | 10.8% | 21% |
| image | 38.3% | 36.4% |
| video | 9.3% | 12.4% |
| Shared article/link | 40.6% | 29.4% |
| Document/carousel | 0.8% | 0.5% |
| poll | 0.3% | 0.3% |
Which hashtags do artificial intelligence posts use?
The most-used tags on artificial intelligence posts in this cohort, by number of posts. We are reporting usage only, not performance: most individual tags in this dataset are dominated by a handful of accounts, so a per-tag engagement figure would describe those accounts rather than the tag. For what the data does support on tags, see the hashtag analysis.
- #digitalhealth (194 posts)
- #technology (192 posts)
- #healthcare (185 posts)
- #medicine (164 posts)
- #future (162 posts)
- #themedicalfuturist (158 posts)
- #ai (143 posts)
- #artificialintelligence (126 posts)
- #machinelearning (84 posts)
- #deeplearning (70 posts)
How to write your own artificial intelligence post
In this category specifically, the first-person opener carries the highest lift into the top decile (1.46x), so that is the shape to reach for first. Video is also under-used here (9.3% against 12.4% cohort-wide), which makes it the cheapest available edge in this category.
- Pick a moment, not a subject. “What I learned about artificial intelligence” is a subject. The Tuesday you got it wrong is a moment.
- Write the first 210 characters last. Draft the body, then find the most arresting line in it and move it to the top. More on this in how to start a LinkedIn post.
- Cut at the fold and reread. If the visible part answers itself, there is no reason to tap.
- Ask something you actually want to know. In this category 13.6% of hooks contain a question, and questions correlate with the comments that carry the most weight.
- Keep it native. Put links in the comments if they have to exist.
Frequently asked questions
What should I post about artificial intelligence on LinkedIn?
Post specific moments rather than general observations. In our cohort, the artificial intelligence posts that reached the top decile by engagement rate had a median of 60 comments against 7 for artificial intelligence posts overall. The pattern behind that gap is concrete detail: a decision you made, a number you can name, a thing that went wrong. Generic advice on artificial intelligence is the most crowded and least rewarded content in this category.
How much engagement do artificial intelligence posts get on LinkedIn?
Across 397 artificial intelligence posts from 37 creators in our cohort, the median post earned 87 reactions and 7 comments, which works out to 0.46 engagements per 1,000 followers using our weighted formula. The cohort-wide median is 0.4 per 1,000, so artificial intelligence content tracks close to the cohort median for engagement per follower.
How long should a artificial intelligence LinkedIn post be?
The part that matters is the visible hook, roughly the first 210 characters before LinkedIn's "see more" fold. In this category the median hook runs 206 characters and 34 words, and hook length does not separate top performers from weak ones anywhere in our data. Write for the fold, not for a word count.
Should artificial intelligence posts use hashtags?
Keep them minimal. 63.2% of artificial intelligence posts in our cohort carry four or more hashtags, and cohort-wide, heavy hashtag use appears about 1.6 times as often in bottom-half posts as in top-decile ones. LinkedIn has also removed hashtag following and de-emphasized tags in search, so they no longer drive the discovery they once did.
About this data
Numbers come from our analysis of a public dataset of 34,012 LinkedIn influencer posts. We scored 12,988 English posts from 65 creators by engagement rate (reactions + 4× comments, divided by the author's followers) and compared the top 10% against the bottom half. The dataset captures each post's text up to LinkedIn's “see more” fold, which is exactly what a reader sees before deciding to engage. These are correlations, not guarantees. Full methodology and caveats are in the full study.