Best of LinkedIn: Strategy & Consulting CW 12/ 13

00:00:00: provided by Thomas Allgaier and Frennis, based on the most relevant LinkedIn post about strategy in consulting from CW-II and XIII.

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00:00:32: So, welcome to the deep dive everyone!

00:00:34: Yeah.

00:00:34: Welcome.

00:00:35: and if you are operating anywhere across the M&A private equity venture capital or consulting landscape this analysis is really curated specifically for you.

00:00:43: Exactly Today we're looking at top strategy in consulting trends seen across LinkedIn in calendar weeks twelve-thirteen

00:00:51: Right.

00:00:51: And our mission today is basically map out a massive structural shift that's happening right under your feet.

00:00:57: It

00:00:57: IS.

00:00:59: We're gonna unpack how the classic consulting delivery model is fundamentally Breaking and rebuilding.

00:01:05: we'll look at why AI as an operating model problem rather than you know just a tech one.

00:01:10: Yeah,

00:01:11: that's big one.

00:01:11: And then how legacy platforms are being wrapped instead of replaced and finally will get into Why The Human Element Is?

00:01:19: The ultimate differentiator in an AI native world.

00:01:22: it's a profound realignment.

00:01:24: I mean we're moving away from an era where Value is tied to human leverage.

00:01:29: Right and we're moving into one where value was tied entirely to organizational adaptability, well outcome velocity.

00:01:37: Okay Let's unpack this from the foundation because a traditional consulting business model The one built on selling elite executive judgment but actually delivering it through a massive pyramid of junior resources It's under immense structural pressure right now.

00:01:51: Oh,

00:01:52: completely!

00:01:52: There is this fundamental shift happening where strategy and execution are just merging

00:01:57: And we're seeing the symptoms of that everywhere.

00:01:59: Ark Byershader actually pointed out a really fascinating dynamic happening inside major firms Right Now.

00:02:05: Well they're quietly but very aggressively building what he calls digital workforces.

00:02:11: We're talking about internal platforms like Deloitte Zora AI or PWC's Agent OS.

00:02:19: But just to be clear, these aren't just like glorified chat GPT windows where an associate asks for a summary of a ten-k right?

00:02:27: No no exactly the opposite.

00:02:28: they're orchestrations of hundreds of specialized narrow AI agents.

00:02:33: wow yeah.

00:02:34: so one agent pulls the financial data another runs the anomaly detection third drafts the slide narrative based on the firm's frameworks and fourth formats.

00:02:43: It takes

00:02:44: us a while.

00:02:45: Right,

00:02:46: Mark makes this brilliant case that in traditional consulting the resource pyramid you know associates doing research and deck production wasn't the product it was factory.

00:02:55: what we are watching is actual industrialization of that factory competition shifting from who writes smartest prompts to who has the most optimized delivery factor.

00:03:05: so no longer consultant versus an orchestrator.

00:03:09: But I mean, if the classic leverage model that pyramid of junior consultants is becoming software doesn't consulting shift from being this artisanal craft to just an industrialized assembly line?

00:03:20: That's

00:03:20: a danger.

00:03:21: Yeah

00:03:21: And what does that mean for The Billable Hour?

00:03:23: like If i'm A PE partner and I know your delivery cost Just dropped by forty percent How do I force you To give me An automation discount?

00:03:30: That is the exact question clients are asking.

00:03:33: Jeffrey Buske posted a really sharp take on this, highlighting a recent ultimatum from PwC's US CEO The

00:03:40: AI First Mandate.

00:03:41: Yes!

00:03:42: Basically telling partners that if they don't embrace it then have no future at the firm.

00:03:47: But for the client This creates some massive commercial tension.

00:03:50: I like that.

00:03:51: We're seeing a forced pivot away from effort-based billing toward outcome based pricing.

00:03:56: if we connect this to the bigger picture it makes total sense.

00:03:59: How so?

00:04:00: Well, The billblower was always just a convenient proxy for value.

00:04:03: It measured effort not impact.

00:04:06: as Maren Hauptmann outlined in her post Value is rapidly moving towards end-to-end outcomes

00:04:11: Right because of an AI agent?

00:04:12: does the baseline analysis In seconds?

00:04:15: Efficiency alone isn't a competitive mode anymore.

00:04:18: its Just the cost of entry.

00:04:19: Precisely What matters to you as a client now is the interpretation, the strategic judgment and the actual implementation.

00:04:27: Which perfectly sets up this collapse of The Divide between setting the strategy... Yeah!

00:04:32: ...and writing code to execute it.

00:04:34: Mm-hmm.

00:04:34: Nermin D'Arish calls that full stack strategy?

00:04:37: I love

00:04:37: that term.

00:04:38: Same And Matthew Kay coined one incredibly accurate, forward deployed executive engineer.

00:04:43: That's good Right, he shared this anecdote about presenting a high level AI strategy to a Fortune-Five Hundred CTO during the day and then going home spending three hours debugging an agent orchestration loop that same night.

00:04:57: That's the new reality?

00:04:58: Yeah!

00:04:58: The days of being pure slide deck strategist who hands off a PDF and walks away those days are over.

00:05:03: They

00:05:03: really are Because the translation layer between business needs and software engineering is exactly where most enterprise AI initiatives just die,

00:05:12: right?

00:05:12: The business leaders don't get the tech constraints.

00:05:15: Yeah engineers Don't Get the commercial context.

00:05:17: Exactly so.

00:05:18: the professionals who can span both Who Can define the strategy And then get hands-on to build it they are the ones ensuring the advice actually works in reality.

00:05:27: Okay But let me challenge the reality on the ground here a bit.

00:05:30: If consulting is shifting from just giving advice to actually orchestrating execution, that completely changes the reality for the clients.

00:05:38: How do you mean?

00:05:39: It means AI isn't just an IT project.

00:05:42: it's a full-blown operating model transformation and The internal plumbing of most clients is fundamentally broken.

00:05:48: Oh absolutely!

00:05:50: A Gilpata Turi shared detail perfectly captures this friction.

00:05:54: He talks about the rise of The Secret Cyborg.

00:05:56: The secret cyborg?

00:05:57: Yeah, or the hundred X super icy?

00:05:59: these are employees who were secretly paying out a pocket for their own AI tools.

00:06:04: They're maintaining parallel shadow infrastructure purely because the official IT is too slow and bureaucratic.

00:06:10: That is a massive headache For security teams but it really highlights A critical vulnerability.

00:06:17: Raphael Tiberio brought this up noting that seventy percent Of Ai challenges Are actually people And process issues

00:06:23: Not the tech itself.

00:06:24: Exactly, companies are paralyzed spending months evaluating platforms completely ignoring the workflow redesign they need.

00:06:32: The real blockage is what Raphael calls the frozen middle

00:06:35: Middle management layer?

00:06:37: Yeah!

00:06:37: The managers whose entire professional identity Is tied to old way of working.

00:06:41: They actively resist organizational readiness needed for AI Because

00:06:46: dropping new tech onto a broken process just magnifies dysfunction.

00:06:50: It feels like companies are buying a Formula One car, but they haven't paved any roads.

00:06:55: Or taught their staff how to drive it?

00:06:56: Right!

00:06:57: Christian Karstle gave a highly specific example of this.

00:06:59: with supply chain planning or APS systems If you don't define decision rights escalation rules and ownership new tech just exposes your lack leadership.

00:07:09: rather than fixing the supply chain It

00:07:11: forces change in operating model.

00:07:13: You can avoid that.

00:07:14: So How do leaders actually bridge gap between ambition & capability?

00:07:19: That is the defining question right now.

00:07:21: Florian Huber brought some sobering data to this, his research shows that forty-nine percent of executives say their workforce simply cannot execute their strategy.

00:07:29: Wow!

00:07:30: Half of them.

00:07:31: Half?

00:07:31: That's a systemic capability failure.

00:07:34: The fix as Florian points out is proactive capability building.

00:07:37: you have build people first and let the strategy follow.

00:07:41: That makes total sense.

00:07:42: And because organizations are struggling so much to redesign these human workflows, we're seeing a totally new approach how we handle massive legacy platforms and how private equity evaluates the companies during diligence.

00:07:56: Here's where it gets really interesting.

00:07:58: Alan Duarte brought up totally counterintuitive point about legacy enterprise software like SAP.

00:08:04: Yeah, the consensus was always that AI would just rip and replace these clunky old systems.

00:08:08: Right

00:08:08: but Alan points out that replacing them costs millions And often fails because an SAP instance isn't just software It's a digital fossil record of undocumented human workarounds.

00:08:20: Exactly so.

00:08:21: instead of replacing it AI is acting as a rapper

00:08:25: A rapper

00:08:26: Yeah!

00:08:26: The AI agent sits on top and makes the clunky interface completely invisible to human user.

00:08:32: You just type a natural language request, And the agent navigates complex screens in background.

00:08:37: That is huge But doesn't that fundamentally threaten the business model of traditional system integrators?

00:08:44: Oh,

00:08:44: completely.

00:08:45: It collapses their revenue model if you can wrap the complexity in weeks instead of migrating it over years.

00:08:51: The old SI Model is dead and this shifts the entire PE & M&A landscape

00:08:56: because the value drivers are different.

00:08:57: right?

00:08:58: James O'Dowd highlighted That past financial performance Is no longer a proxy for future value.

00:09:03: Investors are now underrating AI native operating model readiness.

00:09:07: So they're looking past the P&L to see if you're relying on armies of junior staff or if you've embedded AI into your delivery architecture.

00:09:14: Exactly, legacy cultures are just viewed as too rigid and to hard-to-unlearn

00:09:19: which naturally leads in to Anupamwadwa's insights on the shift to combo diligence right?

00:09:24: You can't evaluate a target in a silo anymore

00:09:26: exactly.

00:09:27: with geopolitical volatility an AI disruption Diligence is no longer siloed it.

00:09:33: this continuous AI enabled assessment incorporating commercial data cyber vigilance and ESG all at once.

00:09:41: It's a continuous data loop, and this is applying to the public sector too.

00:09:45: Shikasen proposed a sovereign intelligence architecture for governments.

00:09:49: What does that look like?

00:09:50: Basically she argues governments need stop buying static short-term consulting reports And start embedding permanent decision infrastructure Like real time AI policy simulation tools directly inside ministries.

00:10:03: That is massive paradigm shift.

00:10:05: But okay I want take all these trends and push them To their absolute logical extreme.

00:10:09: Let's do it.

00:10:10: If the delivery factories are fully automated and legacy systems are seamlessly wrapped, an AI is instantly pulling combo diligence in milliseconds?

00:10:18: What exactly is?

00:10:21: That is the most critical question, and it brings us to the dark side of this revolution.

00:10:25: Angelo Morata wrote about The Complacency

00:10:28: Trap.

00:10:28: Yeah

00:10:29: he noticed how consultants are increasingly accepting diluted good enough AI solutions just to save time.

00:10:36: they lose their persistence And their intuition

00:10:39: because It's the path of least resistance.

00:10:41: its late.

00:10:42: the output looks mostly right so you Just accept

00:10:44: exactly and Linda Castaneda echoed This with her warning About the sameness trap.

00:10:49: If everyone optimizes using the same models, we all arrive at the exact same answers.

00:10:54: Which means that completely lose original divergent thinking

00:10:57: Right.

00:10:58: Gideon Slifkin made a comparison to the movie Idiocracy which is funny but alarming.

00:11:02: Oh wow

00:11:03: His concern was cognitive atrophy.

00:11:05: Overreliance on AI erodes our fundamental ability think deeply and be creative.

00:11:11: So what does this mean?

00:11:13: Two rival PE firms are using the exact same enterprise AI agents to analyze a target.

00:11:18: Doesn't strategy just become completely commoditized?

00:11:21: It's the

00:11:21: fear, right!

00:11:22: How do you generate alpha when everyone has the exactsame

00:11:24: omniscience?!

00:11:25: Well what is fascinating here is the inversion of value.

00:11:28: Tiger Tiger Rajan summed this up beautifully... He concluded that as AI becomes ubiquitous human curiosity emotional intelligence and critical judgment Unautomatable competitive advantages.

00:11:44: Because the AI can process data, but human has contextual awareness to ask non-obvious questions.

00:11:51: Exactly!

00:11:52: It's a person who builds trust during intense buyout negotiation or navigates politics of organizational transformation.

00:11:59: The machine gives you speed and the humans give direction Precisely.

00:12:03: That is such a perfect centricist!

00:12:06: Just wrapping up the journey we've taken today, The consulting pyramid is flattening into digital factories and AI success requires heavy operational rewiring legacy tech as being wrapped instead of replaced And combo diligence is new standard But none it works if you fall in to complacency trap.

00:12:21: Right.

00:12:22: I'd leave with one final provocative thought to mull over.

00:12:25: Think about your own organization's M&A or consulting targets If you strip away all their historical financial successes and look purely at how quickly their culture can unlearn old habits, and adapt to AI native workflows.

00:12:39: Would you still invest in them?

00:12:40: That is a great question to end on!

00:12:43: If you enjoyed this episode new episodes drop every two weeks.

00:12:46: also check out our other editions on private equity venture capital and M&A.

00:12:50: Thanks so much for joining us On This Deep Dive.

00:12:51: Yes

00:12:52: thank You For Tuning In And Don't Forget To Subscribe.

00:12:54: We'll catch y'all the next one.