Best of LinkedIn: Strategy & Consulting CW 14/ 15

00:00:00: Provided by Thomas Allgeier and Frennus, based on the most relevant LinkedIn posts about strategy in consulting from CW-IV and XV.

00:00:08: Frenness is a B to B market research company supporting consultancies with the Market & Competition perspective for example in commercial due delegances CDD.

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00:00:31: you can find more info in the description.

00:00:33: yeah honestly that kind of operational speed is exactly what we're gonna be unpacking today

00:00:38: right?

00:00:38: I mean imagine waking up at like six AM finding out your biggest competitor just outbid you.

00:00:45: But before you even pour your coffee, Your AI agent has already analyzed their move and it's repriced to your outstanding proposals.

00:00:51: It sounds totally like a sci-fi thought experiment right?

00:00:53: But its actually an employed workflow happening now in professional services!

00:00:58: So welcome to this deep dive.

00:01:00: today we are exploring the top strategy and consulting trends across M&A private equity and venture capital And we pulled straight from conversations dominating LinkedIn Right Now

00:01:11: Exactly Because we are looking at, well a fundamental rewiring of how these sectors operate.

00:01:19: Yeah Like the conversation is completely moved past the initial AI hype cycle.

00:01:23: yeah We're not just talking about what these tools might do someday

00:01:26: right now?

00:01:26: We're looking at how top-tier firms or actively tearing down their legacy models you know restructuring pricing and ironically enough placing an unprecedented premium on raw human judgments.

00:01:39: I

00:01:39: love that And I want to start by just, you know throwing out the old playbook entirely because The first major shift we are seeing is Just the death of static strategy.

00:01:47: Oh absolutely.

00:01:48: The traditional cycle Is collapsing under its own weight Right

00:01:51: like that old corporate planning Cycle where leadership just vanishes To some off-site retreat in November and then they produce this beautifully formatted fifty page PDF In January

00:02:01: Which they then blindly execute for twelve months.

00:02:04: It's too slow.

00:02:05: Yeah, the market moves way too fast for a yearly PDF.

00:02:08: Honestly by the time that document even clears the final compliance review The macroeconomic assumptions it's built on are usually completely obsolete Which

00:02:17: is why Ben Jones over at PA Consulting Is championing this really cool concept of live strategy.

00:02:22: Oh yeah I saw using AI agents to monitor global market signals, twenty-four seven.

00:02:27: Exactly!

00:02:28: But the mechanism of how they actually test this strategy is what really caught my eye.

00:02:32: Jones talks about using... he calls them synthetic personas and vibe coded prototypes

00:02:37: which are such a wild term vibe coated prototype.

00:02:40: it's just to clarify for you listening A synthetic persona isn't just your traditional buyer persona.

00:02:46: slide with a stock photo and fake name.

00:02:49: Right, they're not making up marketing merit.

00:02:51: No

00:02:51: firms are using large language models trained on massive lakes of their actual customer behavioral data.

00:02:57: you know support tickets purchasing history.

00:03:00: They build highly nuanced digital twins of the actual customer base

00:03:04: Which changes entire feedback loop.

00:03:07: I mean instead spending six months in millions dollars building product Just to see if it resonates.

00:03:12: You just run it through the synthetic personas instantly.

00:03:16: Right, The AI simulates thousands of complex customer reactions.

00:03:20: It stress tests the move before you ever deploy real capital

00:03:24: And the vibe-coded prototypes.

00:03:26: take a step further.

00:03:27: Because you aren't debating bullet points on us anymore.

00:03:31: The AI rapidly spins up functional mockups or entirely synthesized brand campaigns

00:03:37: So the stakeholders can actually interact with a strategy in real time.

00:03:40: Exactly, they get a visceral feel for the direction not just this dry intellectual understanding.

00:03:46: and when you scale that capability up to the executive suite The role of leadership completely transforms.

00:03:52: like You.

00:03:52: stop spending board meetings looking at the rearview mirror.

00:03:54: Yeah no more debating last quarter's variance against a plan built a year ago.

00:03:58: Right the executive conversation becomes a live response to signals happening today.

00:04:03: The AI synthesizes the market noise, flags the anomalies that actually matter and just it frees up cognitive load so leaders can focus on the horizon.

00:04:13: Okay but I have to play devil's advocate here for a second.

00:04:15: if your strategy is entirely alive aren't we just inviting absolute chaos?

00:04:21: How do you mean?

00:04:22: Well, it sounds dangerously close to day trading your corporate strategy.

00:04:26: Like You see a trending topic on social media the AI flags at competitors press release and suddenly you're pivoting Your entire supply chain On a random Tuesday afternoon.

00:04:35: that is yeah.

00:04:36: That's the most critical risk of adopting this model And it forces a much deeper question about what a corporation actually optimizing for pure go bro shared some deeply relevant insights.

00:04:46: looking at the GCC that addresses this tension perfectly.

00:04:49: Oh, the Gulf Cooperation Council right?

00:04:51: Yeah

00:04:51: he points out that for the last decade corporate strategy was utterly obsessed with just one metric which is efficiency.

00:04:58: Right!

00:04:58: The whole lean management era strip-out the fat eliminate redundancy minimize inventory

00:05:03: Which is a fantastic strategy if you live in a perfectly stable world.

00:05:07: But the reality of a live strategy means you are hyper aware of market shocks.

00:05:12: So Goebbrel argues we have to shift from pure efficiency toward resilience and

00:05:17: anti-fragility.".

00:05:18: So what does that look like in practice?

00:05:20: Well, he uses this Strait Of Hormuz crisis as real world stress test.

00:05:25: when tanker traffic in that region plummeted by ninety percent The companies running those highly centralized ultra lean operations were completely paralyzed.

00:05:35: they had zero buffer.

00:05:36: Oh wow, so the pursuit of maximum efficiency is actually what made them fragile.

00:05:40: Exactly!

00:05:41: The organizations that actually thrive in this environment.

00:05:44: they don't day trade their strategy based on every little blip.

00:05:47: They use live signals to build strategic redundancy.

00:05:50: Ah, okay.

00:05:51: so intentionally absorbing the costs of localized capabilities and supply chain buffers?

00:05:56: Right it's a fundamental shift from an just-in time philosophy to adjusting case philosophy.

00:06:00: The live strategy gives you early warning And antifragile structure ensures that you survive it and capture market share while your lean competitors are scrambling.

00:06:09: Okay, so if corporate strategy needs to be that alive and that resilient then the consulting firms and private equity advisors guiding these companies have a massive

00:06:17: problem.

00:06:18: Oh!

00:06:18: A total structural collapse of their traditional model?

00:06:20: Yeah because you cannot advise a real-time live strategy corporation If your own operating model requires a twelve week engagement cycle just to mobilize a team.

00:06:31: Right, Gaz Tahr framed this beautifully on LinkedIn.

00:06:33: He calls AI a meteor for the consulting industry.

00:06:37: I love that analogy, it's like the asteroid that wiped out the dinosaurs.

00:06:39: Exactly!

00:06:40: The fundamental laws of business physics haven't changed but the species that survive this impact are going to look completely different.

00:06:47: He says.

00:06:48: the industry built its fortunes on baking pies.

00:06:51: Massive

00:06:51: monolithic labor intensive engagements Like dozens of consultants over many months.

00:06:56: But client appetite has fundamentally changed.

00:07:01: it demands cupcakes.

00:07:03: Cupcakes, yes!

00:07:04: Clients want smaller highly modular incredibly fast outcome-driven work.

00:07:09: they want a problem solved in three weeks not a sprawling transformation program that takes three years.

00:07:14: and delivering cupcakes completely breaks the traditional consulting pyramid

00:07:18: because the old model relies on a partner at the top selling Passing it down to managers

00:07:24: who then leverage an army of junior analysts and offshore developers at the bottom To actually grind out the deliverables.

00:07:31: It naturally creates this massive telephone game Of information loss,

00:07:35: right?

00:07:36: The strategic intent gets totally diluted by the time it Meaches the junior analyst formatting the slides

00:07:41: exactly so Rupesh Dandekar Proposes a new framework that entirely bypasses This he calls with the intelligence arbitrage POD

00:07:50: .This is such a cool concept.

00:07:51: Walk us through how a POD actually functions like on a Tuesday afternoon.

00:07:56: Okay, so instead of deploying a twenty-person team you deploy highly concentrated PODs just three to five senior practitioners partners or directors with deep battle tested domain expertise.

00:08:07: Right

00:08:07: because they know exactly what broken processes look Like.

00:08:10: They don't need a month To conduct interviews

00:08:12: Exactly!

00:08:13: They drop directly into the client environment and Instead of delegating to junior staff They use advanced AI agents to execute the grunt work themselves.

00:08:22: They analyze financial models, draft technical requirements and generate dashboards

00:08:27: autonomously.".

00:08:27: So they're compressing a three-month twenty person engagement into a three week sprint just by scaling their own senior judgment.

00:08:35: instead of human headcount?

00:08:37: The AI becomes the leverage!

00:08:39: The Senior Partner is suddenly doing the work of ten analysts but with thirty years of strategic context applied.

00:08:47: But wait, here is where the entire business model hits a wall.

00:08:50: If a senior partner finishes their work in three weeks instead of three months... The traditional time and materials billing structure completely implodes!

00:08:57: Oh it's a disaster for billable

00:08:59: hours….

00:08:59: Right if you bill by hour deploying AI means that your aggressively penalizing yourself for being efficient—the faster you deliver – the less money you make.

00:09:07: It is an existential pricing crisis.

00:09:09: Rajeev Pazhai points out many firms are panicking trying to pivot directly into saucepricing

00:09:14: treating consulting services like a fixed monthly software subscription.

00:09:18: Yeah,

00:09:18: which completely ignores how professional services actually work.

00:09:22: SAAS assumes as standardized repeatable product but in M&A advisory value is co-created with the client

00:09:29: Right.

00:09:29: if the clients internal data isn't absolute disaster.

00:09:32: A standardized AI tool isn't going to save engagement.

00:09:36: You can offer flat subscription fee when the client side variables are that volatile.

00:09:41: It'll destroy your margins.

00:09:42: So Uppani suggests the industry will land on a hybrid model to survive.

00:09:46: You charge a fixed base fee that covers the premium, human elements governance accountability strategic judgment

00:09:52: and then you attach bounded outcome components.

00:09:55: exactly because AI makes The execution highly predictable.

00:09:58: firms can confidently tie A big portion of their fees To measurable KPIs like specific cost reduction percentages And

00:10:05: the pressure to restructure around this is intense.

00:10:08: James Ardoud highlighted that PWC just merged its global risk and consulting businesses into one platform.

00:10:15: We're talking about twenty four billion dollars in revenue

00:10:17: massive integration, And the official corporate line cited client complexity.

00:10:22: but O'Dowd hit the nail on the head.

00:10:24: It happened because AI compresses delivery times so drastically right.

00:10:29: clients won't tolerate slow internal hand-offs between silo departments anymore.

00:10:33: if The tech integrates this solution in seconds.

00:10:35: the organization has to match that

00:10:37: And delivering these rapid outcomes requires a radically different approach to technology, like we are moving way beyond just pasting text into a chat interface.

00:10:46: Oh

00:10:46: the tooling evolution is staggering!

00:10:49: Some do make an outline this practical workflow replacing traditional analysts.

00:10:53: You start with Gemini to rapidly synthesize external market search.

00:10:56: Then you feed those insights onto a Chat GPT Excel plugin.

00:11:00: So it acts as a quantitative junior analyst.

00:11:02: Yeah, you can literally converse with your financial models to spot anomalies.

00:11:06: then You use lovable which is a rapid prototyping tool To spin up tangible software interfaces instantly.

00:11:11: but the client visualizes The solution immediately rather than looking at wireframes.

00:11:15: and finally Claude steps in to generate the highly visual branded slide narratives.

00:11:21: It's a huge productivity leap But it is still fundamentally linear.

00:11:25: Indra Prasad-Godtok's approach takes us into the next paradigm.

00:11:28: Right,

00:11:29: he built that structured external brain a private ecosystem detailing all his proprietary frameworks and past project successes.

00:11:36: Exactly!

00:11:37: So when a massive RFP lands on his desk His AI assistant accesses that external brain And drafts a tailored response in about forty minutes.

00:11:47: But the autonomous agent he built is The Real Game Changer.

00:11:50: The one that reads the news at six a.m.. Yes,

00:11:52: it monitors regional news and competitor press releases.

00:11:55: overnight It woke him up with a briefing that a competitor was opening A local AI office in a city where He Was bidding.

00:12:02: Wow And he had the intelligence to completely reprice his proposals and secure local partnerships before His very first client meeting of the day.

00:12:11: That perfectly illustrates a critical warning from Matthias Elcesser regarding the AI bubble.

00:12:16: He notes that, The vast majority of corporate world is still stuck in one-to-one relationship with AI.

00:12:22: A human types of prompt?

00:12:23: The machine gives an output

00:12:24: It's faster but it's still linear

00:12:26: Exactly!

00:12:27: The organizations will achieve exponential dominance are runs building what he calls end to M systems

00:12:33: meaning multiple humans interacting with multiple autonomous agents.

00:12:37: An agentic ecosystem, one senior partner orchestrates five specialized AI agents.

00:12:43: they independently query databases draft code and crucially the interact with each other.

00:12:48: They validate work and challenge assumptions without human intervention.

00:12:52: Okay, I have to jump in here because the idea of an agent-to-agent economy is fascinating but also kind of terrifying.

00:12:59: How

00:12:59: so?

00:12:59: Well if my firm deploys an end-to-'em system And...my client deploys one We essentially have bots negotiating with bots.

00:13:07: It sounds exactly like algorithmic trading on Wall Street where two bots get confused and trigger a flash crash that wipes out billions.

00:13:13: Yeah, if my digital twin and a vendor's digital twins start independently negotiating a master services agreement aren't we just accelerating towards a hallucinated disaster?

00:13:22: That nobody actually authorized.

00:13:24: it's a profound structural risk.

00:13:26: Peter Jonathan Jameson explored the dark side of this agent to agent economy And he warns have too massive pitfalls.

00:13:34: The first is the trust deficit.

00:13:36: Trust

00:13:36: stuff's it, meaning what exactly?

00:13:37: In M&A private equity and consulting trust is the actual product being sold.

00:13:43: An AI agent can perfectly mimic your tone in format emails but it cannot replicate genuine human intent.

00:13:51: you can't build a resilient client relationship through proxy bots.

00:13:54: right when things go wrong a client needs to look a human in the eye

00:13:58: Exactly!

00:13:58: And The second risk Jameson points out might be even more dangerous long term...the learning paradox.

00:14:04: Okay, break that down for us.

00:14:05: Professional growth in these high-stakes environments is entirely driven by discomfort.

00:14:10: a junior analyst learns to read the room By sitting at a tense negotiation.

00:14:14: A manager develops judgment by navigating pushback from a hostile stakeholder.

00:14:18: So friction is the mechanism For building expertise.

00:14:21: Yes so if we deploy AI agents To absorb all of daily friction Drafting tough emails Smoothing over data discrepancies Low level negotiations We remove the mechanism Of learning.

00:14:31: Oh, wow.

00:14:32: So if junior professionals never experience the friction how do they ever develop this strategic judgment required to become senior partners?

00:14:40: We risk creating a lost generation of professionals who know how to prompt an AI but have zero intrinsic judgement.

00:14:52: brings us to the ultimate constraint in fields like M&A and private equity.

00:14:56: AI gives you speed, but it cannot manufacture courage trust or strategic honesty.

00:15:01: Exactly.

00:15:02: Tanya W brought up a chilling point about how this plays out in procurement and due diligence.

00:15:07: Yeah, she said the biggest risk isn't just hallucinations because those are easy to spot.

00:15:11: if you're paying attention The much more insidious threat is AI bias validating bad human decisions

00:15:16: The confirmation bias loop.

00:15:18: Precisely Let's say an executive has a gut feeling they want to acquire specific target.

00:15:23: They feed that biased premise into an AI agent.

00:15:26: The AI doesn't challenge the

00:15:27: premise.

00:15:28: It just instantly generates a beautifully formatted, deeply convincing fifty-page due diligence report supporting it.

00:15:35: Right!

00:15:35: It adds illusion of rigorous math to bad idea without actually adding any objective truth.

00:15:41: And in past A poorly thought out M&A thesis usually looked messy.

00:15:47: Spreadsheet had errors Narrative was thin.

00:15:50: Today bad decisions look dangerously polished.

00:15:54: So if an investment committee won't aggressively challenge a flawlessly written AI report, billions get deployed based on very fast highly confident utterly wrong assumptions

00:16:05: which completely elevates the premium.

00:16:09: Tobias Blazer shared a perfect example regarding private equity firms executing carve-outs of family owned businesses.

00:16:15: Right, because family business don't usually fail from bad strategy.

00:16:18: they fail because no one challenges the sacred cows!

00:16:21: Exactly.

00:16:22: and internal employees never gonna walk into the boardroom until The Founding Family need to sell off the legacy plant their grandfather built.

00:16:28: it's political suicide

00:16:29: And an AI agent can highlight the inefficiency in seconds but It Can't Look A Proud Founder In The Eye and Navigate The Emotional Weight Of That Legacy?

00:16:38: That requires immense human courage and empathy.

00:16:41: Jonathan Flack highlighted another deeply human limitation when advising family offices on location strategy.

00:16:48: Yeah, choosing a location isn't just a mathematical optimization problem for tax rates.

00:16:52: Right Does the location align with the families culture?

00:16:55: Can you attract a star chief investment officer who actually wants to move their life into that city?

00:17:00: An AI agent optimizing for tax efficiency does not care where your kids go to school.

00:17:05: The human factors ultimately dictate the success and Tiger Tiagrajean and Antonio Cusimano synthesize this perfectly,

00:17:15: because AI flattens the execution layer.

00:17:18: Anyone with the right tools can crunch the data and build the slides now.

00:17:21: So execution isn't the bottleneck anymore, The real leadership differentiators are now deeply human traits authentic connection inclusive listening intense curiosity And the courage to provoke uncomfortable thinking in your clients.

00:17:35: AI handles that tactical heavy lifting but the leaders of tomorrow master the vision and the relationships.

00:17:42: as we wrap up this exploration of live strategy, the meteor hitting consulting want to leave you with one final thought.

00:17:48: To consider

00:17:49: let's hear it

00:17:50: if AI agents are constantly monitoring market signals and evaluating competitor moves twenty four seven then The entire concept of the traditional deal cycle is dead.

00:18:00: wait really?

00:18:00: The whole deal cycle.

00:18:01: yeah

00:18:02: in M&A due diligence has always been a frantic thirty-day sprint after signing a letter of intent.

00:18:08: But if your end-to-end system is continuously analyzing every target in real time, due diligence no longer an event.

00:18:15: It's a continuous stream!

00:18:16: Oh wow so you're effectively underwriting companies months before they even go up for sale?

00:18:20: Exactly consider this what happens to your market share when you already know the exact value of a Target Before The Investment Bank Even prints the teaser?

00:18:28: yeah You can't just optimize the past anymore.

00:18:32: If you enjoyed this episode, new episodes drop every two weeks.

00:18:36: Also check out our other editions on private equity Venture Capital and M&A.

00:18:40: Thanks so much for listening to This Deep Dive And don't forget to subscribe!