Best of Linkedin: Strategy & Consulting CW 42/ 43

00:00:00: Provided by Thomas Allgaier and Freeness, based on the most relevant LinkedIn posts about strategy and consulting in calendar weeks forty-two and forty three.

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00:00:30: Today's deep dive is a sharp no fluff look at the top strategy and consulting trends surfacing across LinkedIn.

00:00:38: we curated this specifically for You As A Strategy M&A or Investments Professional

00:00:44: And our mission today is really unpacking this massive gap between AI adoption and actual profit impact.

00:00:50: Yeah, it's a huge gap.

00:00:51: It really is.

00:00:52: We're gonna look at how that gap is rewriting the consulting business model itself.

00:00:56: The urgent shift to agentic AI NY physical world geopolitics are quietly constraining all these digital ambitions.

00:01:03: So diving right into that first theme This AI value illusion we are observing just incredible unprecedented rates of enterprise adoption.

00:01:12: Oh absolutely.

00:01:13: But the financial returns, like the actual bottom line results they are largely missing in action.

00:01:19: Companies are buying the tools but the profit and loss statements just remain stubbornly flat.

00:01:24: I mean i want to ground this on some specific numbers that Arne Gas shared from McKinsey's recent corporate strategy data.

00:01:30: Let us hear it.

00:01:31: We're sitting at a point where eighty percent of leaders report seeing individual productivity gains within their teams.

00:01:37: Eighty percent

00:01:39: Right.

00:01:39: But when we actually look at the financials, only thirty-seven percent report any positive impact on EBIT.

00:01:46: Wow!

00:01:46: Yeah that is a massive disconnect.

00:01:48: if eighty percent of the workforce has genuinely more productive That should inevitably flow down to the bottom line you know?

00:01:54: Exactly So.

00:01:55: the fact it isn't suggests this fundamental misallocation of that save time.

00:02:00: And we are seeing this disconnect play out most starkly in industries which bridge digital and physical

00:02:05: divide.

00:02:06: Max Müller-Semit published some really interesting research focusing on container ports and terminals.

00:02:11: Okay, now logistics is an industry heavily reliant on complex routing and optimization right?

00:02:16: So theoretically it's prime territory for measurable AI efficiency.

00:02:20: I think so.

00:02:20: yeah

00:02:21: his data shows that forty four percent of port terminals are actively scaling AI solutions.

00:02:26: okay almost half Right.

00:02:27: yet only a shocking four percent can demonstrate a measurable impact on their earnings.

00:02:32: wait four percent That's it.

00:02:34: Yeah

00:02:35: just four percent

00:02:36: That is wild.

00:02:37: I mean, let's analyze the mechanics behind that failure rate for a second.

00:02:40: Sure A container terminal might optimize its internal crane routing algorithm by say twenty percent But if the physical trucks arriving at the gate are still snarled in traffic or you know union contracts restrict how many automated workflows can be executed per hour?

00:02:57: That isolated digital efficiency just hits a physical bottleneck

00:03:01: Right!

00:03:01: The physical world gets it away.

00:03:03: Exactly.

00:03:04: you've accelerated one component of a machine that is still governed by its slowest physical gear.

00:03:10: It's honestly like buying a faster treadmill, but refusing to change your

00:03:13: diet.".

00:03:14: That's a great way to put it!

00:03:16: You're optimizing an isolated action...but expecting this holistic transformation.

00:03:21: And the local optimization as a total trap?

00:03:24: You optimize specific workflow without questioning broader operating model.

00:03:29: Mark Britholtz framed perfectly in his post.

00:03:32: What did he say?

00:03:33: He warns that the biggest strategic risk in the market today isn't failing to adopt AI.

00:03:38: The biggest risk is successfully adopting AI into a business model, but it's losing relevance.

00:03:43: Yeah like being really efficient at something nobody wants anymore

00:03:47: exactly.

00:03:48: he gave you example of A consulting firm using AI to cut the time It takes to produce a standard Market analysis from two weeks To two days.

00:03:56: on paper I mean That software deployment looks Like a massive operational win

00:04:00: But strategically its completely irrelevant.

00:04:02: Right, because if you can produce that analysis in two days your clients have already learned how to produce that exact same analysis themselves.

00:04:10: Using the exact same foundational models?

00:04:12: Precisely!

00:04:13: So what good is cutting that time If clients are doing it themself?

00:04:17: You're suddenly five times more efficient at producing a commodity nobody wants to buy from you

00:04:22: Which is huge takeaway for you when listening from M&A or investment space.

00:04:26: This fundamentally alters how conduct do diligence on target company

00:04:30: It really does.

00:04:31: you cannot value a target based merely on their AI tools or their departmental efficiency metrics.

00:04:37: You have to audit there market relevance if this Target company becomes fifty percent more efficient, but they're end customers also become fifty-percent more efficient at solving the same problem?

00:04:47: You Have To Ask If The Target's Core Value Proposition Still Holds Up.

00:04:51: Yeah Are You Just Buying A Highly Efficient Version Of A Company That Is Being Structurally Disintermediated?

00:04:55: Exactly?

00:04:56: And you know, that structural disintermediation is already blowing back on the very industry selling these digital transformations.

00:05:03: The consulting industry itself?

00:05:05: Right!

00:05:05: If clients realize that faster output doesn't equal profit... ...the firms selling them.

00:05:10: these strategies are facing an economic reckoning of their own.

00:05:13: The underlying unit economics of professional services are shifting violently right now.

00:05:17: Marcus Bjork highlighted a recent internal policy at Accenture.

00:05:21: Oh I saw this one.

00:05:22: Yeah, they placed a strict twenty nine dollar month cap on Claude usage per employee.

00:05:26: Right?

00:05:27: On the surface people just treat this as standard corporate cost cutting.

00:05:30: but it actually signals a massive shift from traditional billable hours to metered consumption based billing.

00:05:37: Because under the old model, a per-seat software license whether it was Excel or some proprietary database that Was just a predictable fixed cost.

00:05:45: Exactly you Just bury in the general overhead charge The client four hundred dollars an hour and maintain A forty percent margin.

00:05:52: but

00:05:52: AI

00:05:53: operates on tokens.

00:05:55: It's metered

00:05:56: totally variable right?

00:05:58: It forces firms to explicitly allocate AI costs To specific client projects rather than hiding them In General margins.

00:06:05: If a team consumes massive amounts of computing power over weekend for complex model, the cost of that specific hour or work could skyrocket unpredictably.

00:06:13: It's an absolute margin killer.

00:06:14: if they failed to track and pass those variable costs on have you compute engagement?

00:06:19: Could literally cost the firm money to execute.

00:06:22: it's like running in all.

00:06:23: You can eat buffet but suddenly your landlord starts charging you for electricity based On how many times your customers chew.

00:06:29: That's hilarious But its true.

00:06:32: The entire fixed fee pricing structure just collapses.

00:06:36: But the threat isn't just internal margin compression, it's external competition too.

00:06:40: Jason Spencer surfaced a major development where big tech is not selling tools anymore.

00:06:45: What are they doing?

00:06:47: Anthropic is reportedly backing European AI consultancy alongside private equity for HG.

00:06:54: AI builders coming directly to lucrative implementation and advisory revenues They realize the real margin is in the service layer that integrates model into client's operations.

00:07:05: This an existential threat to industry.

00:07:08: Wait, I have push back a little strategically here... Go

00:07:10: for it!

00:07:11: If

00:07:11: AI doing all of heavy lifting doesn't this just mean consulting firms need hire way fewer graduates?

00:07:17: Isn't that the real margins saver

00:07:19: them?!

00:07:19: You would think so but no.

00:07:21: Christian Eisner effectively dismantled his idea and insights on agentic CRM.

00:07:26: Okay howso?

00:07:27: That whole strategy relies on the assumption that work is static, like if a project has hundred fixed tasks and AI does fifty.

00:07:35: you only need half of junior analysts.

00:07:38: But working in market economy isn't static.

00:07:41: things were previously unscalable are now possible.

00:07:44: take hyper personalized customer interactions.

00:07:47: You could manually design a white glove journey for your top one hundred enterprise clients, but you couldn't do it.

00:07:52: four two million retail users.

00:07:54: The human labor cost made an impossible

00:07:56: exactly.

00:07:57: But with agentic AI It's economically viable.

00:08:00: so firms don't need fewer young talents.

00:08:03: They need graduates with entirely new skills to manage these newly scalable opportunities.

00:08:07: Oh, I see that makes perfect sense and by the way if you want to ensure You catch our future deep dives on how these operating models are shifting make sure your subscribed Yes

00:08:17: definitely subscribe The speed at which these internal architectures or changing is just staggering

00:08:23: It really is.

00:08:24: And the reason we need this new skill Is that were actively moving from AI as an assistant To AI As An Agent

00:08:32: Right, which is a massive leap.

00:08:33: An assistant waits for a prompt but an agent possesses autonomy to execute multi-step workflows.

00:08:39: Dr.

00:08:40: Eloise Epstein discussed this in some recent podcast insights on procurement.

00:08:44: What was her main takeaway?

00:08:45: She noted the fundamental shift and job roles.

00:08:48: Professionals must transition from being process executors To process governors Process

00:08:53: governors.

00:08:54: I like that.

00:08:54: Yeah It completely changes how you evaluate a company's scalability.

00:08:58: An agent company has a structurally lower OPEC ceiling, because they don't need to hire fifty new procurement officers to expand.

00:09:06: They just spin up more agents governed by highly strategic human team.

00:09:11: Karsten Ney actually added some great perspective to show what this looks like in practice... ...because agentic AI isn't just the dashboard.

00:09:19: it turns procurement signals into timely negotiations It prepares targets, it wargames supplier responses and captures value before your leverage is lost.

00:09:28: It's actively executing on those market signals

00:09:31: Exactly.

00:09:32: But handing over that level of active execution introduces a massive terrifying gap in readiness.

00:09:39: Jeff Walters shared some data from BCG's applied AI index.

00:09:43: This data is wild.

00:09:45: By twenty thirty forty two percent of companies expect to give AI agents real decision making authority.

00:09:52: Almost

00:09:52: half the market,

00:09:53: right?

00:09:54: Yet today only five percent have the controls in place to do that safely just

00:09:58: five percent.

00:10:00: we are handing over the keys to The Treasury but We haven't installed any security cameras

00:10:04: exactly and companies Are trying to protect the wrong things by simply restricting AI.

00:10:10: Rajiv Singh made a great observation about this vulnerability.

00:10:13: What

00:10:13: did he point out?

00:10:14: He noticed that boards treat this purely as an IT security issue.

00:10:18: They lock down the models and block prompts, but governance actually protects what matters most human judgment.

00:10:25: in relationships restriction protects neither.

00:10:28: precisely documented expertise erodes in value incredibly fast.

00:10:32: now restricting The AI to protect legacy knowledge is just futile.

00:10:37: true governance scales human context.

00:10:39: So while boards are completely obsessed with AI governance and autonomous agents, the actual ceiling on growth is being dictated by far

00:11:09: beyond domestic demand, like we're seeing with steel EVs or solar panels.

00:11:14: They have to flood the global market

00:11:16: which turns a local economic strategy into a massive customs and compliance nightmare.

00:11:22: exactly Global prices crash Domestic industries demand protectionist relief And supply chain compliance just becomes elaborate.

00:11:31: This fragmentation connects two real structural costs.

00:11:34: Lutiano De Fiori shared a McKinsey report on energy that really models this out.

00:11:39: The geographic disparity there is huge.

00:11:41: It is!

00:11:43: Under a fragmented energy order, European gas prices could sit ten to fifteen percent above the baseline by twenty thirty-five but

00:11:50: U.S.,

00:11:51: which is insulated by domestic production only sees zero to five percent bump.

00:11:56: That's permanent structural disadvantage for european heavy industry

00:12:00: Absolutely So.

00:12:01: my question is, if capital is flowing to fix these supply chains why aren't we moving faster?

00:12:06: Why can't we just spend our way out of the bottleneck.

00:12:08: Peter Jonathan Jameson had a great post answering exactly that.

00:12:13: Capital is rarely the binding constraint in the physical world.

00:12:16: Okay what is planning

00:12:18: and permitting speed?

00:12:19: as he put it you can't sprint a rail corridor

00:12:22: right.

00:12:23: You can allocate a billion dollars tomorrow but you still have to wait ten years for the environmental reviews.

00:12:30: The physical world operates on regulatory timeframes that do not care how fast your AI can design a blueprint.

00:12:36: So, How does strategy professionals bring it all together?

00:12:39: Well, Ion Roy shared this concept from EY called the Minimum Viable Enterprise.

00:12:45: In a World of Trade Wars Energy Fragmentation and AI Disruption Strategy Professionals must define the absolute essential commitments their organization must maintain when disruption hits.

00:12:57: So resilience is now your core competitive strategy.

00:13:01: Exactly, it's not just a defensive checkbox anymore.

00:13:04: I want to leave you with the final really provocative thought built on source material we covered today.

00:13:10: August Sugianto noted this hilarious but genuinely dark contrast.

00:13:16: Oh i loved at that point.

00:13:18: When AI produces complex mathematical proof Mathematicians immediately scrutinize it.

00:13:23: They hunt for errors in logic and aggressively question the assumptions

00:13:27: because a beautifully formatted hallucination is still a hallucination exactly.

00:13:32: But when AI produces a beautifully format corporate strategy deck Executives immediately ask how many employees they can replace?

00:13:40: It's crazy.

00:13:41: Did you take it at face value,

00:13:42: it's a stark reminder For you as a strategist.

00:13:45: Beautifully written Confident AI output is completely useless if you lack the domain expertise to understand it.

00:13:52: A hundred percent!

00:13:53: You have to know The underlying business mechanics to govern it.

00:13:57: If you enjoyed this episode, new episodes drop every two weeks.

00:14:01: Also check out our other editions on PE Fundraising, PE Exit Strategies, PE Value Creation Venture Capital and M&A.

00:14:10: Thank-you so much for joining us For This Analysis.

00:14:12: Remember To Subscribe And We'll See You Next Time.