LinkedIn Content Strategy for AI Value Creation Consultants | Netwarm
LinkedIn playbook · Case study
LinkedIn content strategy for AI value creation consultants: how a Hamburg consulting partner reached 130 executives in six weeks
We read every reaction on 21 posts from a Hamburg-based partner at a global strategy consultancy who works on AI value creation. 1,048 people, 130 executives. Here is what brings buyers, what brings peers, and the 5 posts we’d publish next.
Max Sawyer · Netwarm··13 min read
The creator in this case studyA Hamburg-based partner at a global strategy consultancy who works on AI value creation
Followers23,610
Posts~3–4 a week
Sells
These numbers are from 5 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.
AI value creation programs for large companies: where AI pays off, how to scale it, and how it reaches the P&L
PeriodSep 25 – Nov 5
Ideal client: executives of large companies (CEOs, CFOs, C-level, VPs, heads of and directors) who have AI pilots running and need them to show up in the numbers.The challenge: The partner asks the question every AI program has to answer: “Where is the money?” The posts mix research, event recaps, industry takes and team news. Which of them reach the executives who decide on AI budgets, and which mostly reach colleagues, consultants and students?
Key takeaways
The buyers are hiding among peers.130 of the 1,048 people who reacted are executives: 12.4%. 567, more than half, are consultants, colleagues at the firm, students and recruiters.
Research posts bring 2x more executives.AI value research posts: 16.1% executives. Industry and AI takes: 7%. Event and lecture posts sit in between at 10.2%.
9 executives keep coming back.9 executives reacted to 3 posts or more, and 3 of them to 5 or more. One reacted to 10 of the 21 posts.
01
Who actually reads you, and what the LinkedIn algorithm changed
The partner posts about AI value creation: firm research (the AI Maturity Matrix, token costs, leaders vs laggards), the TUM lecture series and events, industry takes, and team milestones. 21 posts between 25 September and 5 November, about 3 to 4 a week.
The LinkedIn algorithm shows a post first to the people who reacted to the last ones. On a profile followed by a large network of colleagues and students, that first circle is mostly peers, so who reacts matters more than how many. We sorted every person who reacted by role.
21posts in six weeks
1,048people reacted
130executives
9came back 3+ times
Audience by roleThe 1,048 people who reacted, by roleFree
Consultants, colleagues at the firm, students & recruiters567 · 54.1%
Everyone else351 · 33.5%
Executives are 130 people, about 1 in 8. They include CFOs, chief people officers, heads of AI, SVPs at carmakers and managing directors of investment firms: the people who sign off AI budgets.
567 consultants, colleagues, students and recruiters make up the peers, more than half of everyone. They celebrate the milestones and fill the lecture hall, and they help reach, but they don’t buy a transformation program. That is why a post with 1,000 reactions can bring fewer executives than one with 100.
SeniorityAll people who reactedFree
Founder, owner, C-level16.6%
Director, VP7.9%
Manager9.3%
Independent8.6%
Other57.6%
IndustriesExecutives onlyNetwarm
Tech, data & AI roles51.5%
Hidden in preview00%
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See all industries and company sizes in your free scan.
A consultancy partner’s posts get plenty of reactions. The question is whose.
We tagged each of the 21 posts by topic, then measured the share of executives among the people who reacted, and how many each topic reached per post.
Your topicsWhat your 21 posts were aboutFree
21posts
AI value research7
Events and the TUM lecture6
Industry and AI takes4
Firm milestones and wins4
Topics that attract executivesShare of each topic’s reactions from executivesNetwarm
AI value research16.1%
Events and the TUM lecture10.2%
Firm milestones and wins9.8%
Industry and AI takes7.0%
One topic brings about 2x more executives than another. See which.See which topics
AI value research posts bring 16.1% executives, industry and AI takes 7%: about 2x more. By reach, research also leads with 11.9 executives per post, against 4.2 for industry takes.
Posts that brought the most executivesShare of executives in each post’s reactions1 of 5 open
#1AI Maturity Matrix 2026 is out29%
#2The AI numbers look great on paper. In practice, they often aren’t.21%
#3We keep monitoring 1,330 companies17.3%
#415 years ago today, I started at BCG15%
#5Try to find a single open seat13%
Among posts with 25 reactions or more. For comparison, the Paris Motor Show post reached 4.8% executives, and the Forrester Wave post 9% despite 829 reactions.
These rules come from what worked on the partner’s own profile, and from the best-performing posts by AI strategy consultants, enterprise AI leaders and business school researchers on LinkedIn over the last 3 months.
1
Lead with one number from your own research. Executives don’t need another AI opinion. They want a benchmark they can’t get elsewhere. Put the number and the scope (“75 economies, 33 indicators”) in the first line, then what it means for their company.On this profile: the AI Maturity Matrix post reached 29% executives, the highest share of the 21 posts.
Open on the gap between paper and practice. Two numbers that don’t match make an executive stop: what was promised and what reached the P&L. Name the gap, then explain it.On this profile: “The AI numbers look great on paper. In practice, they often aren’t.” reached 21% executives, second of the 21 posts.
Talk growth, not headcount. Most AI posts are about saving time and cutting cost. A post on where AI grows revenue gives the executive a reason to read on, and it is the argument the partner already makes: the real value is in more and better outcomes.Across the niche: in the report this post cites, 35% of departments tracking a growth measure report strongly positive ROI, against 17% of those tracking time saved.
Write to the reader’s desk, not to the industry. Event news and product launches are about the market. Executives react when the post is about their own strategy document, their board meeting, their budget. Say “your AI strategy”, not “the industry”.On this profile: industry and AI takes reached 7% executives, the AI value research 16.1%.
Put your own stake in it. A personal milestone travels further than any study. Use that reach: tie the story to one lesson an executive can use, so the new readers it brings are the right ones.On this profile: the 15-year post had the biggest reach of the period, 1,101 reactions, with 15% executives in its first 100.
Turn a conversation into the question boards ask. Event talks and interviews work when the first line is the question an executive is asked in their next board meeting, not the name of the event.
When executives read: the best time to post on LinkedIn for AI value creation consultants
We compared the share of executives by the day and the hour each post was published (Berlin time). Every 2-hour slot from 8 a.m. to 4 p.m. had 3 posts or more.
Share of executives by posting dayAmong the people who reacted to each postFree
6.0%
Mon
16.6%
Tue
10.7%
Wed
13.5%
Thu
10.6%
Fri
Best time to post, by hourShare of executives among people who reactedFree
17.0%
8:00
4.7%
10:00
12.6%
12:00
8.5%
14:00
12.9%
16:00
Thursday is the most reliable day: 6 posts, 13.5% executives, 53 in total. Tuesday had the highest share (16.6%) but only 2 posts. Monday was the lowest (6%).
Post at 8 a.m. Berlin time: the 5 posts at 8 a.m. reached 17% executives and 15.2 per post, against 4.7% for the 4 posts at 10 a.m. Keep research posts for Tuesday and Thursday mornings. Six weeks is a short sample, so treat it as a direction.
05
5 posts ready to publish to target executives
Each post follows the rules above, in the partner’s voice, and reuses points already made on the profile. Swap in your own details before posting: your real numbers, studies and client cases are what make it land.
1Ready to postBenchmark
Germany does not have an AI ambition problemRules 1 and 4: one number from your own research, then the reader’s own company. Modelled on the partner’s AI Maturity Matrix post, the best for executives.
Hook
Germany does not have an AI ambition problem. 🇩🇪It has a scaling problem.Our AI Maturity Matrix 2026 assessed 75 economies on 33 indicators. Germany sits with the “AI Contenders”, next to France, Australia, Israel and Italy. The “Pioneers” are led by the US, Singapore, the UK, China and Canada.Looking at the data, the gap is not in the strategy papers. Almost every economy has an AI strategy by now. It no longer sets anyone apart.The gap is in three places:
- building ecosystems
- attracting investments
- scaling talent and researchI see the same pattern inside companies. The AI strategy is written. The pilots run. What is missing is the system that scales the few use cases that create real value.📌 If you lead a business in Germany: which of the three is your biggest gap today?Full report and the interactive country dashboard in the comments.#AIValueCreation #AIMaturity
Visual · Single imageThe Matrix chart with Germany highlighted among the AI Contenders, and the three gaps written next to it.Check before postingCheck the country groups against the final report, and put the report and dashboard links in the first comment.
The hours were freed up. EBIT did not move.Rules 2 and 3: open on the gap between paper and practice, then talk outcomes, not hours. Modelled on Gabriel Millien’s AI execution gap post and the partner’s “great on paper” post.
Hook
The hours were freed up. EBIT did not move.I keep seeing the same AI story.An automated process frees up people’s time. The dashboard is green. The team celebrates.Then the CFO asks: where is the money?📌 The time was saved, but nobody changed what the team does with it.
📌 One process step became much faster, but the overall process stayed the same.
📌 The output did not change, so the P&L did not either.The real value is rarely in fewer working hours. It is in a process that produces more and better outcomes: more leads, better conversion, lower material cost.🔥 Measure the output of the process, not the input.Which AI project in your company saved the most time, and what did it change in your numbers?#AIValueCreation
Visual · Single imageTwo bars side by side: “hours saved” going up, “EBIT” flat.Check before postingAdd one real, anonymised client case if you can: the process, what changed, what it did to the numbers.
Where is the money? The one-page AI value scanRule 3 and the lead magnet below: the three value pools from the partner’s October 27 post, given away on comment. Modelled on that post’s “drop AIValueCreation in the comments” offer.
Hook
Where is the money?Most AI programs start with productivity. It is the obvious place to look.But the value sits in three pools, not one:1️⃣ Productivity: fewer hours for the same output
2️⃣ Revenue growth: more leads, better conversion, a better customer journey
3️⃣ External spend: lower material, service and token costsMost companies only measure the first. The other two are often just as big.So we turned this into a one-page AI value scan. For each pool: the questions to ask, where AI is technically feasible, and how to check that it will show up in the P&L.Run it with your leadership team before your next AI budget decision.Comment “VALUE” and I will send it to you.#AIValueCreation
Visual · Document previewThe first page of the scan: three columns, one per value pool, with the questions underneath.Check before postingBuild the one-page scan before posting, and plan who answers the comments and sends it on the day.
The question boards ask about AI has changedRules 5 and 6: your own stake, then the question boards ask. Modelled on the partner’s 15-year post, the biggest reach of the period.
Hook
When I started at BCG, clients asked what a new technology would cost them.Today, almost every board asks a different question about AI: where is the money?15 years taught me that the question a leader asks decides the answer they get.Ask about cost, and you get efficiency cases. Fewer hours, smaller teams, a nice slide.Ask about value, and the option space opens: growth, pricing, a better customer journey, lower external spend.Three things I tell every leadership team today:
📌 Look for value in the right places first, not for use cases.
📌 Redesign the whole process, not one step of it.
📌 Measure what the process produces, not the hours it saves.What question is your board asking about AI this year?#AIValueCreation
Visual · PhotoA photo of you on stage or with a client team, no slide.Check before postingUse the question your first clients really asked, and the one you hear most from boards today.
AI leaders outperform laggards by 3-5xRules 1 and 3: one number from your research, then what the leaders do. Modelled on the partner’s 1,330 companies post.
Hook
We keep monitoring 1,330 companies.The AI leaders outperform the laggards by 3-5x: on top-line growth, TSR, profitability and cost.That is not a technology gap. It is a leadership gap.What we see the leaders do differently:📌 They look for value in the right places: productivity, but also revenue growth and external spend.
📌 They redesign the full process, not a single step.
📌 They measure outputs: leads, conversion, material cost. Not hours saved.
📌 They plan the token bill: smart usage, smart infrastructure, smart contracting.And the window is closing. There is a 2nd mover advantage in AI right now. Wait another 2-3 years and it turns into a 3rd mover disadvantage.Which side of the gap is your company on today?#AIValueCreation
Visual · Single imageOne chart: leaders vs laggards on growth, TSR, profitability and cost.Check before postingCheck the 3-5x figure and the company count against the latest edition of the study, and link it in the first comment.
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 request shows intent. The quickest way to see which executives are about to act on AI is to offer them something they can use with their own team, and see who asks for it.
Among AI strategy consultants and educators, these formats get the most requests:
Format 1The report, sent on commentReaders comment a keyword and get the research before it is public. The partner already does it.
Format 2The workbook with worksheetsA guide where every section ends in a worksheet the reader fills in for their own business, built around the decisions a leader has to defend.
Format 3The playbook for one functionOne resource per function (the CFO, the head of sales), with what to do from day one.
Format 4The personalised auditThe reader asks in the comments and gets an audit of their own company, with benchmarks and an action plan.
Our pick for you: “The one-page AI value scan”Built from the three value pools the partner already names (productivity, revenue growth, external spend) and the leaders vs laggards research: for each pool, the questions to ask, where AI is feasible, and how to check it reaches the P&L. Offer it in post 3, on the comment keyword “VALUE”.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 among hundreds of colleagues and students, and a CFO reading every research post this month may have picked another firm by next quarter.
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 now3 executives · not contacted yetNetwarm
3 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 Claudia, you’ve been reading our AI value research for a few weeks. Is your team looking at growth use cases yet, or still at productivity?Hi Martin, I saw you reacted to the AI Maturity Matrix post. Which of the three gaps is the biggest in your company?
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, AI value research brought about 2x more executives than industry takes: 16.1% against 7%. Lead with one number from your own research, open on the gap between paper and practice, and write to the reader’s own company.
For this partner, Thursday was the most reliable day: 6 posts, 13.5% executives. Tuesday had the highest share (16.6%) on only 2 posts, Monday the lowest (6%). Post at 8 a.m. Berlin time. Six weeks is a short sample, so treat it as a direction.
This partner posts 3 to 4 times a week. The research posts did most of the work with executives, so one strong research post on Tuesday or Thursday does more than an extra event recap.
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 21 posts published between 25 September and 5 November 2026 (up to the first 100 reactions per post), and sorted the 1,048 people by role. Reposts, posts written by others and a recruiting post were left out. Comments were not counted, so engagement figures are a floor.
Niche rules come from top posts by AI strategy consultants, enterprise AI leaders and business school researchers over the last 3 months. Role groups are approximate: an executive is anyone with a C-level, VP, head of, director, managing director or founder title outside consulting firms and universities. A Netwarm scan matches people to your own ideal client.
