LinkedIn Content Strategy for AI Strategy Consultants | Netwarm
LinkedIn playbook · Case study
LinkedIn content strategy for AI strategy consultants: how a Copenhagen AI advisor and podcast host reached 155 executives in four weeks
We read every reaction on 28 posts from a Copenhagen AI strategy consultant, keynote speaker and podcast host. 766 people, 155 executives. Here is what brings buyers, what brings peers, and the 5 posts we’d publish next.
Max Sawyer · Netwarm··11 min read
The creator in this case studyA Copenhagen AI strategy consultant, keynote speaker and podcast host
Followers21,312
Posts~7 a week
SellsAI strategy consulting and advisory, intelligent automation, keynotes
These numbers are from 1 November. Your audience has already moved.
New executives turn Hot every week and others go quiet. Run your free scan to see today’s version, with the names.
Ideal client: executives and business leaders who have to make AI work inside a real company, from finance to IT.The challenge: The consultant posts almost every day: sharp jabs at AI hype, longer notes on what real transformation takes, and a podcast with 100+ episodes. Consultants, speakers and AI authors react a lot. Which posts reach the executives who hire an AI advisor?
Key takeaways
1 in 5 readers is an executive.155 founders, C-level leaders, directors and heads of reacted in four weeks: 20.2% of the 766 people who reacted.
The jabs bring them in.The posts poking at AI hype reached 9 executives per post. Podcast episodes reached about 2.
Executives come once.Only 2 executives reacted to 3 posts or more. The work is turning a one-time reader into a regular.
01
Who actually reads you, and what the LinkedIn algorithm changed
The consultant writes about AI for business: jabs at the hype coming out of Silicon Valley, notes on what transformation really takes, and episodes of a podcast past 100 episodes. 28 posts between 4 October and 1 November.
The LinkedIn algorithm shows a post to the people who reacted to the last ones, then to people like them. In AI, those people are often other consultants, speakers and authors. They push reach, and they rarely hire an advisor. So we looked at every person who reacted and sorted them by role.
28posts in four weeks
766people reacted
155executives
2came back 3+ times
Audience by roleThe 766 people who reacted, by roleFree
Peers are the largest group: 172 consultants, advisors, speakers and authors, many of them in AI too. Executives come close: 155 people, 1 in 5.
Many of the rest work in IT and data: engineers, architects, project managers. They are the teams an AI strategy lands on, and they are worth keeping. But they rarely sign the consulting contract.
SeniorityAll people who reactedFree
Founder, owner, C-level17.5%
Director, VP7.6%
Manager11.1%
Independent9.1%
Other54.7%
IndustriesExecutives onlyNetwarm
Tech, software, AI and data51%
Hidden in preview00%
Hidden in preview00%
Hidden in preview00%
Hidden in preview00%
See all industries and company sizes in your free scan.
These rules come from what worked on the consultant’s own profile, and from the best-performing posts by AI strategy and transformation advisors on LinkedIn over the last 3 months.
1
Put a number on the hype. The jab that worked best set three figures side by side (real EBITDA, adjusted EBITDA, valuation). Finance and business leaders recognise a number before they recognise a joke.On this profile: the EBITDA post reached 27 executives, the most of any post. The global-warming jab, with no number, reached 2.
Give them one line to repeat in the boardroom. “You don’t need AI literacy, you need technology literacy.” A sentence an executive can say out loud in the next meeting travels further than the argument around it.On this profile: the paradox of visibility post had the highest share of executives, 35.7%.
Joke about the client meeting, not the CEO in the news. Jabs at Silicon Valley bosses draw peers who share the joke. A joke about the meetings clients sit in draws the people who sit in them.On this profile: the consultant joke reached 19 executives (25.3%). The Sam Altman RAM post drew more reactions, 194, and a lower share, 13%.
End with a question about their own week. A question readers can answer from their own feed, team or year brings them into the comments, where the consultant can see who they are.On this profile: the “first 8 posts in my scroll” post, which ends on a question, reached 30.8% executives.
Land the analogy in two lines. Gotham, bears and fur, stone tablets: the consultant’s analogies are a signature. They work when the business point arrives right after the image, not three paragraphs later.On this profile: the Gotham post, where the AI point comes in paragraph three, reached 0 executives out of 17 reactions.
Leave them one thing to try before the next AI project. An action a leader can take on Monday (watch three people do the task, ask IT one question) turns a sharp opinion into advice.Across the niche: the “watch three people do it” post drew 75 comments on 42 likes.
When executives read: the best time to post on LinkedIn for AI strategy consultants
We compared the share of executives by the day and the hour (Copenhagen time) each post was published. Hours are shown for slots with 3 posts or more.
Share of executives by posting dayAmong the people who reacted to each postFree
26.2%
Mon
20.9%
Tue
16.6%
Wed
15.2%
Thu
13.8%
Fri
16.7%
Sat
18.7%
Sun
Best time to post, by hourShare of executives among people who reactedFree
21.8%
6:00
15.2%
8:00
12.1%
12:00
17.9%
16:00
Monday brought the highest share of executives (26.2%), Friday the lowest (13.8%). Tuesday brought the most in total: 48 executives across 4 posts.
Early mornings work best: the 8 posts published between 6 and 8 a.m. Copenhagen time reached 21.8% executives, against 12.1% around noon. Put the posts that sell the work (the client joke, the one-line lesson) on Monday and Tuesday mornings, and keep Friday for lighter posts.
05
5 posts ready to publish to target executives
Each post follows the rules above, in the consultant’s voice. Swap in your own details before posting: the real client moment is what makes it land.
1Ready to postNumbers jab
The AI business case, as presentedRule 1: put a number on the hype. Modelled on the EBITDA post, the one that reached the most executives.
Hook
The AI business case, as I keep seeing it presented 😅- Licences bought: 400
- Licences opened last week: 61
- Time saved per employee: “up to 30%” (according to the vendor)
- Time spent in AI steering committees: also up to 30%
- Processes that actually changed: 0It’s hard to replace a skilled controller after all, it seems 🤦Before you buy the next 400 seats, take the slide to finance and ask one question:Which of these numbers would you sign?#ai #technology
Visual · Single imageA plain slide with the five lines, the vendor figure in big type and the “0” circled in red.Check before postingThe figures are satirical. Keep them clearly so, or swap in the real (anonymised) numbers from a client case.
You don’t need an AI strategyRule 2: one line to repeat in the boardroom. Modelled on the paradox of visibility post, the highest share of executives.
Hook
Monday musings: you don’t need an AI strategy.You need a problems strategy that AI is allowed to be part of.Every week a client asks me for good AI use cases.
Almost nobody asks me to help them list their biggest problems first.So here is the swap I suggest in every first meeting:You don’t need AI use cases, you need a list of what slows you down.
You don’t need an AI roadmap, you need to know which data your processes can trust.
You don’t need an AI owner, you need an owner for each process AI touches.
You don’t need more pilots, you need one change that sticks.Then AI becomes what it should be: one tool among many.Fixation is limitation.#ai #technology
Visual · Text onlyNo image. The four “you don’t need / you need” lines do the work.Check before postingKeep the four pairs to what you really say to clients. Cut any that sound like a slogan you would not defend.
Things I heard in AI meetings this monthRule 3: joke about the client meeting, not the CEO in the news. Modelled on the “great time to be a consultant” post.
Hook
Things I heard in AI meetings this month 😅🤦- “We have the licences, now we just need the use cases.”
- “Can the agent just read SharePoint?”
- “Our data is fine, it’s only spread over 14 systems.”
- “Let’s do a pilot first and decide the goal later.”
- “Peter built an agent for that. Peter left in August.”It is still a great time to be a consultant.But every one of these sentences is the start of a good conversation: about data, ownership, and what you actually want to change.Which one have you heard (or said) this year?#ai #technology
Visual · Single imageA meme-style image in the usual style: a meeting room, the five quotes as speech bubbles.Check before postingUse sentences you really heard, without naming the client.
Which process did AI change this year?Rule 4: end with a question about their own week. Modelled on Rob Llewellyn’s “AI fiction is expensive”.
Hook
Name one process AI actually changed in your company this year.Not a pilot. Not a demo. Not a licence.A process that runs differently on a Tuesday because of it.I asked this at a recent keynote. Most of the room had to think for a long time.That’s not a failure. It’s where most companies are.The ones that can answer usually did three boring things first:
→ They picked a process before they picked a tool
→ They asked IT what data that process can trust
→ They named who keeps it running when the person who built it leavesNo magic. Just a better way of working, with AI as a subset.So: which process changed in yours?#ai #technology
Visual · Text onlyNo image. The question at the top and bottom carries the post.Check before postingThe keynote moment must be real: use your own room and what really happened.
Four kinds of invisible AILead magnet: the Invisible AI check, built from the four kinds of invisible AI in the 19 October Monday musings. Modelled on Michael Lee’s one-page cheat sheet.
Hook
The AI that changes your company is the AI nobody puts on a slide.Every executive is chasing the visible kind: the chatbot, the agent, the demo.The transformations I see working are built on the invisible kinds:INDIRECT: AI helped build a solution that wasn’t feasible before (AI coding)
EMBEDDED: a system you already use just works a bit better
CARROT: AI is the reason people finally agree to change how they work
AGNOSTICISM: you solved it another way, but AI made you rethink the work around itThe common denominator is a better way of working.So before your next AI workshop, run each of your projects through these four questions. You’ll find the ones worth funding, and the ones that are only visible.P.S. I turned the four questions into a one-page check, with an example filled in for a finance process. Want it? Comment “invisible” and I’ll send it.
Visual · Single imageThe one-page check: four boxes (Indirect, Embedded, Carrot, Agnosticism), each with one question and a tick box.Check before postingPut your Netwarm Reveal link behind the one-pager so you can see which executives download it.
Free forever: unlimited scheduling through LinkedIn’s official API, with images, video and PDF carousels.
06
LinkedIn lead generation: lead magnets that work to target executives
Reactions show interest. A download shows intent. The fastest way to find out which executives are serious is to give them something useful and see who takes it.
In AI strategy and transformation, these formats get the most requests:
Format 1The catalogueEvery task one team does, with the AI agent or workflow that fits each one.
Format 2The one-page cheat sheetThe frameworks executives have heard of, on one page they can print.
Format 3The readiness scorecardA short assessment that tells a company where it really stands, and what to fix first.
Our pick for you: “The Invisible AI check”Built from the four kinds of invisible AI the consultant already wrote about (indirect, embedded, carrot, agnosticism), as one page of questions with an example for a finance process. Offer it in the P.S. of post 5, and mention it on the podcast.With a Reveal link, every person who downloads it is shown by name, with their role and how warm they are. Your first Reveal link is free.Create your free Reveal link
07
From reactions to clients
Content brings executives to the profile. It doesn’t say when to reach out. Most never comment, so they stay invisible, and an executive who liked the EBITDA post in October may have picked another advisor by January.
On LinkedIn, the right moment to start a conversation is when someone keeps coming back. We call that Hot: 5 or more points over 90 days, where a reaction counts 1, a repost 2, a download or a reply 4.
Hot right now1 executives · not contacted yetNetwarm
1 executives are Hot. See who to message first.See who’s Hot
First messageAn opener for each Hot person, based on the posts they readNetwarm
Hi Mette, you reacted to my post on technology literacy. Is AI literacy training on your list for next year?Hi Jonas, thanks for following the AI posts. Which process is your team trying to change first?
A first line for each of them, ready to send.See the openers
Netwarm sends nothing for you. It tells you who and when, and you write the message. It also works inside Claude and ChatGPT: ask “Who’s Hot today?” and get the list.
08
FAQ
Here, sharp jabs at AI hype reached the most executives per post, and one-line lessons had the highest share. Put a number on the hype, joke about the client meeting, and leave readers one line or one action they can use.
For this consultant, Monday brought the highest share of executives (26.2%) and Friday the lowest (13.8%). Tuesday brought the most executives in total. Early mornings, Copenhagen time, worked best.
This consultant posts about 7 times a week. Volume brings reach, but only 2 executives came back 3 times or more: fewer, sharper posts that executives want to come back for would do more.
Look at who reacts, not how many. Group reactions by role, measure the share of your ideal clients per post, and follow the people who keep coming back. A free Netwarm scan does this for you.
Yes. Netwarm only reads public reactions to your own posts. It never logs in as you, never asks for your password, and never messages anyone for you.
How we made this playbook
We read the public reactions on 28 posts published between 4 October and 1 November 2026 (up to the first 100 per post), and sorted the 766 people by role. Two posts written by other people about the consultant were left out. Comments were not counted, so engagement figures are a floor.
Niche rules come from top posts by AI strategy and transformation advisors over the last 3 months. Role groups are approximate, and some executives sell to the same audience; a Netwarm scan matches people to your own ideal client.