Latest / Best of LinkedIn: Strategy, M&A & Investments / Best of LinkedIn: Strategy & Consulting CW 30/ 31

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Best of LinkedIn: Strategy & Consulting CW 30/ 31 · Best of LinkedIn: Strategy, M&A & Investments

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  Speaker 1: provided by Thomas Allgaier and Frenis based on the most relevant LinkedIn posts about strategy in consulting, in calendar weeks thirty-and-thirty one.
• 0:08
  Speaker 1: Frenes is a BDB market research company supporting consultancies with a marketing competition perspective for example in commercial due diligence's CDD.
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• 0:31
  Speaker 1: you can find more info in the description.
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  Speaker 0: So we are jumping right into a pretty massive unfreezing moment today for our deep dive in to the top strategy and consulting trends across LinkedIn.
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  Speaker 1: Yeah, exactly.
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  Speaker 1: And I mean The core theme We're seeing.
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  Speaker 1: is this just crazy widening gap between?
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  Speaker 1: This sheer mountain of cash being spent on AI Right now and the actual value hitting the bottom line?
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  Speaker 0: great It's huge disconnect.
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  Speaker 0: plus
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  Speaker 1: On top all that how geopolitics.
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  Speaker 1: it's Just completely redrawing the map For global business.
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  Speaker 0: It really is a stunning paradox.
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  Speaker 0: I mean you have boards authorizing these unprecedented tech budgets on one side of the ledger, right?
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  Speaker 0: While the external operating environment it's just fracturing into tariffs and sanctions...
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  Speaker 1: Yeah that's wild!
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  Speaker 1: The fundamental rules are being rewritten live.
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  Speaker 1: so we need to figure out what actually drives value in this environment.
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  Speaker 1: for YOU The listener, let's start with the money.
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  Speaker 1: Let's do it because It is staggering.
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  Speaker 1: we are looking at a projected two point five three trillion dollars expected to be spent on enterprise AI by twenty twenty six.
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  Speaker 0: Wow
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  Speaker 1: Trillion yeah With a T.
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  Speaker 0: Which brings us to that shocking reality check you mentioned earlier.
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  Speaker 0: Sumundra Mahanti points out, right now, ninety-five percent of these enterprise generative AI pilots show absolutely zero measurable P&L impact.
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  Speaker 1: Zero I mean the ninety five percent is basically all them
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  Speaker 0: Literally zero.
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  Speaker 0: Their research notes that companies are desperately trying to restructure into these Palantir-like deploy codes, like they want to be this hyper efficient software deployment engines but their doing it before the technology is even fully baked.
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  Speaker 1: Okay let's unpack for a second because I mean its buying a fleet of Formula One cars and only driving them in grocery store parking lot.
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  Speaker 1: You've got all this raw power, but the environment around it just isn't built to handle it at all.
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  Speaker 1: Yeah
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  Speaker 0: and The stats back that up completely.
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  Speaker 0: I mean eighty eight percent of organizations are using AI somewhere But the share of companies actively abandoning their initiatives That jumped from seventeen percent.
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  Speaker 0: two forty-two percent in Just a single year.
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  Speaker 1: wait forty two percent almost half or just giving Up.
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  Speaker 0: basically yeah The patience is just running out at the board level.
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  Speaker 1: So, okay if the spend is drastically outrunning the value how are the successful minority actually making it work?
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  Speaker 0: Well Rodney Coutinho shares this framework for capturing ROI and it reveals something pre-counterintuitive.
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  Speaker 0: Okay bought AI tools actually land value roughly twice as often as homegrown builds
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  Speaker 1: really.
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  Speaker 1: but I mean everyone always says data is the new oil right.
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  Speaker 1: you'd think building your own custom model would give you the ultimate edge.
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  Speaker 0: It sounds great in theory, but in practice homegrown builds are a total trap for most enterprises because building your own requires incredibly scarce AI talent.
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  Speaker 1: Oh right which is super expensive!
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  Speaker 0: Exactly.
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  Speaker 0: But Continuo notes that buying the tool is really only step one.
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  Speaker 0: The real failure point here Is that boards are entirely ignoring operating model redesigns.
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  Speaker 1: So they buy this shiny new tool and just slap it onto a break in process.
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  Speaker 0: Exactly, And even if you do by the tool there are still these massive hidden traps waiting for you.
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  Speaker 0: Look
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  Speaker 1: what?
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  Speaker 0: Diana Kern's Manolatos highlights a trend that should honestly terrify CFOs.
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  Speaker 0: It is the rise of toll gating fees.
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  Speaker 1: Toll gating I mean like a highway toll.
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  Speaker 0: Yeah exactly Like That!
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  Speaker 0: It completely upends The traditional data ownership model.
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  Speaker 0: Vendors Are starting to charge companies unexpected fees Just to access their own historical Data so They can scale Their AI.
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  Speaker 1: Wait hold on.
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  Speaker 1: They have to pay a toll just to look at their own digital property.
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  Speaker 1: Yes,
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  Speaker 0: the vendors are building these contractual fences around data and essentially metering access to it...
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  Speaker 1: Wow!
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  Speaker 1: Which completely blows up the original business case.
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  Speaker 1: If accessing your own data suddenly costs a fortune Your ROI goes negative before you even launch.
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  Speaker 0: Precisely So if this broad generic pilots are failing And Data Access is getting weaponized Where's the real value?
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  Speaker 1: Right It has got be moving somewhere
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  Speaker 0: It is, it's migrating deep into the commercial core.
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  Speaker 0: We are seeing a huge shift toward agentic AI.
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  Speaker 1: Okay so moving away from just like passive chatbots to agents that actually execute commercial workflows independently.
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  Speaker 1: Exactly!
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  Speaker 1: Yeah, Ema K points out that a genetic AI and customer-facing functions is scaling three and half times faster than in other areas.
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  Speaker 0: Three and a half times?
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  Speaker 0: That's massive
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  Speaker 1: It is And forty one percent of those are already fully scaled.
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  Speaker 1: By
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  Speaker 0: the way if you want to keep catching these aha moments make sure you subscribe so don't miss future additions.
• 4:56
  Speaker 1: Yes definitely hit subscribe.
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  Speaker 1: But going back to the commercial core why is it scaling so fast there?
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  Speaker 0: Isabel Huber shed some light on this, specifically in B-to-B sales.
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  Speaker 0: She notes that seventy one percent of top teams raise their AI budgets by double digits.
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  Speaker 0: Okay but are they actually staling
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  Speaker 1: it?
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  Speaker 1: No under ten percent have scaled It because again They're just layering AI onto broken processes instead of Actually rewiring the workflow
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  Speaker 0: automating inefficiency exactly.
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  Speaker 0: But wait I have a major question here.
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  Speaker 1: If the AI
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  Speaker 0: is making commercial decisions on its own like negotiating a contract, who actually gets sued when it messes up?
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  Speaker 1: Yeah.
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  Speaker 1: That's the million-dollar question!
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  Speaker 1: And Sebastian Terwee notes that legal teams are absolutely terrified about this because of the unclear ownership and eroding trust.
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  Speaker 1: Legal has to be design partner from day one now not just final checkpoint.
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  Speaker 1: Right
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  Speaker 0: Because traditional liability relies on human intent.
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  Speaker 0: if an agent goes rogue There's no logic tree to blame.
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  Speaker 1: Exactly, which is why Gary Aurora frames this whole transition around four architecture questions you have to answer before launch.
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  Speaker 0: What are they?
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  Speaker 1: First what does the AI actually own?
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  Speaker 1: second whats its autonomy level
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  Speaker 0: so like?
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  Speaker 0: can it act alone or Does a human need to approve It
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  Speaker 1: right?
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  Speaker 1: third Is what's The source of truth?
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  Speaker 1: and fourth what is Its post-launch behavior meaning?
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  Speaker 1: how Does it drift Or change once it's out in the wild?
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  Speaker 0: exactly You Have To monitor it Constantly
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  Speaker 1: okay?
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  Speaker 1: So If these AI agents are taking over the commercial core and making decisions, what happens to the human workforce?
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  Speaker 1: Are we just looking at mass layoffs.
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  Speaker 0: Actually counterintuitively humans become more important not less.
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  Speaker 1: really
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  Speaker 0: How so?
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  Speaker 0: Bob Sternfelds highlights that one major firm is actually targeting a twenty percent increase in consultant headcount.
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  Speaker 0: A
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  Speaker 1: twenty-percent increase, yeah!
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  Speaker 1: In the middle of an AI boom.
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  Speaker 1: Yeah
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  Speaker 0: They are betting that AI will just supercharge human judgment So they can tackle way bigger problems.
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  Speaker 1: That makes sense.
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  Speaker 1: Mark Byer Shoder points out that AI's real power isn't just productivity It's capturing the tacit experience.
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  Speaker 0: Right, the reasoning behind why a seasoned employee makes specific trade-off.
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  Speaker 1: Exactly!
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  Speaker 1: But to capture that you need healthy corporate culture.
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  Speaker 1: and Naya Baxter outlines four cultural tensions currently blocking AI.
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  Speaker 0: Yeah these are huge.
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  Speaker 0: First is agency problem.
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  Speaker 0: people won't experiment if they don't feel safe.
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  Speaker 0: Second is erosion of apprenticeship model.
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  Speaker 1: Oh because the AI doing all the grunt work juniors used learn from?
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  Speaker 0: Exactly how do they learn?
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  Speaker 0: Third is leadership workforce gap.
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  Speaker 0: and fourth is what she calls culture debt.
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  Speaker 1: Here's where it gets really interesting, Culture Debt...is like sleep deprivation for a company.
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  Speaker 0: Oh that's a great way to put it
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  Speaker 1: Right!
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  Speaker 1: Like you can function on low-sleep for awhile You could push through the exhaustion But eventually The fatigue breaks the whole system.
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  Speaker 0: Yeah..the burnout is real.
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  Speaker 0: And Pear Kilfors adds this by pointing out why human presence Is such durable advantage
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  Speaker 1: Because AI can process info but It doesn't have mirror neurons
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  Speaker 0: Exactly.
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  Speaker 0: It can't replicate those shared physical rituals that build actual trust between people,
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  Speaker 1: right?
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  Speaker 1: And trusts is everything internally But what happens when trust breaks down externally on a global scale?
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  Speaker 0: well That shifts us to our final theme.
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  Speaker 0: while leaders are you know obsessing over their internal AI architectures The external map of global business is being completely redrawn by geopolitics.
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  Speaker 1: Yeah We are in this structural transition.
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  Speaker 1: per
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  Speaker 0: Christian Hong makes a great point here.
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  Speaker 0: The situations in the Persian Gulf and the Strait of Hormuz, they are just temporary energy crazies.
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  Speaker 1: No!
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  Speaker 1: They're proof-of concept for a new era of conditional trade.
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  Speaker 0: Right.
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  Speaker 0: Strategic leverage is the game.
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  Speaker 1: And Morgan Montaignee and Sarah Adam point out a massive strategic blind spot here.
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  Speaker 1: Critical minerals.
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  Speaker 0: Huge blindspot...
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  Speaker 1: But wait I mean Doesn't the low cost of these minerals on a balance sheet mean we can just easily source them elsewhere?
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  Speaker 1: Oh wait, that's exactly The Trap.
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  Speaker 0: That is the trap.
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  Speaker 0: their low-cost completely hides there absolute power to halt production On like everything.
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  Speaker 0: fighter jets auto lines you name it.
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  Speaker 1: Wow It's incredible leverage and the trade realities are just hitting us rapid fire right
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  Speaker 0: now.
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  Speaker 0: Yeah they really are.
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  Speaker 0: Just look at the EU.
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  Speaker 0: Mariavar Patarch notes they just launched their massive twenty-first sanctions package against Ressa.
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  Speaker 0: The Twenty
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  Speaker 1: First?
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  Speaker 1: Yeah,
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  Speaker 0: and this one completely bans crypto evasion from third countries!
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  Speaker 1: That is aggressive... And on the US side drew to long warns that the hundred fifty day U.S.
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  Speaker 1: tariff stopgap is expiring
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  Speaker 0: which triggers a fast rollout of section three.
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  Speaker 0: oh one and two hundred thirty two actions.
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  Speaker 1: Right targeting forced labor chips pharma whole landscape.
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  Speaker 1: it's shifting under
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  Speaker 0: our feet.
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  Speaker 0: It really is.
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  Speaker 1: So bringing this all together, what does actually mean for you the listener?
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  Speaker 0: Well to synthesize all of these we are essentially in an unfreezing moment.
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  Speaker 0: Competitive advantage is no longer just about throwing money at tech or assuming that global remains stable.
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  Speaker 0: it's about organizational design human leadership and truly mastering your supply chain choke points.
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  Speaker 1: You know its funny.
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  Speaker 1: if AI can now capture the tacit knowledge decision making experience.
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  Speaker 1: Will a company's unique human culture eventually just become the training data for its own autonomous agents?
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  Speaker 1: Oh
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  Speaker 0: wow, that is a wild thought to leave off on.
• 10:19
  Speaker 1: It is right.
• 10:20
  Speaker 1: Well if you enjoyed this episode new episodes drop every two weeks.
• 10:23
  Speaker 1: also check out our other editions on venture capital M&A and private equity.
• 10:27
  Speaker 0: Thank You so much for hanging out with us for this deep dive And don't forget to subscribe.
• 10:31
  Speaker 1: catch your next time.