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Best of LinkedIn: Strategy & Consulting CW 46/ 47 · Best of LinkedIn: Strategy, M&A & Investments

• 0:00
  Speaker 0: Provided by Thomas Allgaier and Frennus.
• 0:02
  Speaker 0: Based on the most relevant LinkedIn posts about strategy and consulting in CW-Forty-Six and Forty-Seven.
• 0:08
  Speaker 0: Frennus specializes in B-to-B market research for strategy and consulting teams with a focus on tech and ICT.
• 0:16
  Speaker 0: And before we jump into the material, just a quick note.
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  Speaker 0: This edition is brought to you by our partner Dealroom.
• 0:21
  Speaker 0: They're gathering insights for their state of M&A twenty-twenty-six report, and you can actually help shape it by taking their survey.
• 0:28
  Speaker 0: This is your chance to share how you approach sourcing, diligence, and integration, and see how your experience stacks up against your peers.
• 0:35
  Speaker 0: You can find the link to the survey right in the description.
• 0:39
  Speaker 0: Welcome back to the Deep Dive.
• 0:41
  Speaker 0: Today, we are tearing into a really dense stack of sources covering the latest in strategy and consulting from calendar weeks forty-six and forty-seven.
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  Speaker 0: Our mission is to distill actionable knowledge for anyone in M&A, private equity, venture capital, or, well... the consulting space itself.
• 0:56
  Speaker 0: We're looking beyond the headlines to see what's actually happening with AI, with agentic systems and all these organizational pivots.
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  Speaker 1: It's a fascinating stack of material.
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  Speaker 1: I mean, it really confirms this major thematic shift we've been seeing.
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  Speaker 1: We are well past the experimentation phase with generative AI.
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  Speaker 1: The entire conversation has moved into a much harder, much more challenging implementation in governance phase.
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  Speaker 1: And
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  Speaker 0: that impacts everyone.
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  Speaker 1: It impacts everyone.
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  Speaker 1: From M&A targets that have to prove their AI is safe during diligence to the consulting firms themselves who are frankly grappling with how to deliver value when their old tools are being digitized.
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  Speaker 0: Exactly.
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  Speaker 0: It's not about testing the tech anymore.
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  Speaker 0: It's about adaptation and really liability.
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  Speaker 1: Which brings us straight to our first theme.
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  Speaker 1: This tension at the very heart of the modern consulting model.
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  Speaker 0: The one.
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  Speaker 1: AI is supposed to be this.
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  Speaker 1: Ultimate productivity booster, you know, but at the same time it directly challenges the two things consultants sell most aggressively.
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  Speaker 1: Their credibility and their human expertise.
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  Speaker 0: And we saw a perfect almost painful real-world example of that tension.
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  Speaker 0: It was reported by Sahitya Setu.
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  Speaker 0: Oh,
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  Speaker 1: the Deloitte slip-up.
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  Speaker 0: The Deloitte slip-up.
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  Speaker 0: A major one.
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  Speaker 0: They produced a one point six million dollar report for the Newfoundland and Labrador government and it had multiple citations to research papers that.
• 2:16
  Speaker 0: Well, they just don't exist.
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  Speaker 1: Pure AI hallucinations.
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  Speaker 1: It's
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  Speaker 0: completely made up.
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  Speaker 1: The reputational damage from that kind of error is just immense.
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  Speaker 1: I mean, in an industry built entirely on trust that the advice you're getting is fact-checked and verified, these aren't just mistakes.
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  Speaker 0: No, they're existential threats.
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  Speaker 0: They
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  Speaker 1: really are.
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  Speaker 1: It exposes this lack of human oversight, which is the exact failure M&A professionals are terrified of when they do diligence on an AI-enabled target.
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  Speaker 1: The real edge right now isn't just using AI.
• 2:44
  Speaker 0: proving you can use it responsibly.
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  Speaker 1: Exactly.
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  Speaker 1: Responsible AI paired with rigorous human quality control.
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  Speaker 0: In that failure of verification, it leads directly to this broader, sharper critique of the traditional consulting career path.
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  Speaker 0: James O'Dowd argued pretty forcefully that the generalist career consultant is, in his words, dying.
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  Speaker 1: That really resonates.
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  Speaker 1: I mean, the whole economic model of the generalist firm, that pyramid structure, it was built on leveraging junior consultants for all the low and mid pyramid work.
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  Speaker 0: Research, data synthesis, making the slide decks.
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  Speaker 1: All of that.
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  Speaker 1: And AI has essentially just eaten that work.
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  Speaker 1: It can do it faster, cheaper, and it never gets tired.
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  Speaker 0: So if you're a private equity firm relying on consultants for a due diligence report, you have to understand that the person writing it is fundamentally leveraging a machine.
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  Speaker 0: The value has to come from somewhere else now.
• 3:36
  Speaker 1: Absolutely.
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  Speaker 1: Odoud's point is that the future consultant has to be a creator.
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  Speaker 1: Someone who builds proprietary IP or designs digital products or architects, AI-enabled delivery systems.
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  Speaker 1: The value has to shift beyond just billable hours.
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  Speaker 0: Which feeds into that deeper critique from Sean Jones.
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  Speaker 0: He called it the big con.
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  Speaker 0: Right.
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  Speaker 0: He highlighted the hidden cost of relying too much on external consultants.
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  Speaker 0: He said it can infantilize the client organization.
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  Speaker 1: It creates a dependency loop.
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  Speaker 1: The knowledge walks out the door when the project ends, so you never build that internal muscle.
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  Speaker 0: It's a tough assessment.
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  Speaker 1: It is, but the firms are fighting back.
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  Speaker 1: You have Rob Hornby.
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  Speaker 1: and also Nina Probst and Andreas S. from McKinsey pointing out the counter argument.
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  Speaker 1: Which is?
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  Speaker 1: That while AI tools like McKinsey's own tool, Lily, handled the routine stuff, the core of consulting, you know, managing complexity, creating real change, that still relies on human trust and critical thinking.
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  Speaker 1: And crucially, the ability to question what the AI gives you.
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  Speaker 0: The skepticism.
• 4:37
  Speaker 0: the human judgment layer.
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  Speaker 0: That's
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  Speaker 1: the part that's irreplaceable.
• 4:40
  Speaker 0: Okay, so let's pivot to the technology that is driving all of this, agentic AI.
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  Speaker 0: I think this is the key differentiator that M&A and digital transformation pros have to get their heads around right now.
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  Speaker 1: Yes, we have to define it properly.
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  Speaker 0: What makes it so different from just you know, regular automation.
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  Speaker 1: Garf Coley completely nailed this distinction.
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  Speaker 1: He emphasized this is a revolutionary shift.
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  Speaker 1: It is not just an evolution of RPA robotic process automation.
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  Speaker 1: What was
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  Speaker 0: his comparison?
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  Speaker 1: A self-driving car versus cruise control.
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  Speaker 1: It's perfect, right?
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  Speaker 1: RPA is deterministic.
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  Speaker 1: It just follows a script.
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  Speaker 1: Agentic AI is probabilistic.
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  Speaker 1: It understands the objective and then figures out the path to get there on its own.
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  Speaker 1: It transforms entire functions, not just processes.
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  Speaker 0: So it's a quantum leap in autonomy.
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  Speaker 0: And the investment data really reflects that urgency.
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  Speaker 0: Diana Kearn's Manolato's shared Deloitte survey findings.
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  Speaker 0: And they were pretty striking.
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  Speaker 0: Nearly three quarters of leaders funded AI or Gen AI in the last year.
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  Speaker 0: and thirty-nine percent, a huge number-funded agent to AI specifically.
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  Speaker 1: And their projection for twenty-twenty-six is that over half of all digital transformation budgets will go toward AI automation.
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  Speaker 0: So where is that money going?
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  Speaker 1: Well, when you look at the opportunities, they are just staggering.
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  Speaker 1: Ian Kahn detailed the rise of what he calls agentic commerce, calling it a potential trillion-dollar opportunity, especially in retail.
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  Speaker 0: This is where it gets really interesting for the consumer side, I think.
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  Speaker 0: We're moving beyond chatbots to fully autonomous transactions.
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  Speaker 1: Exactly.
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  Speaker 1: Khan gave examples of AI agents that can build your wish list, actively compare prices across different stores, and then just execute the purchase for you.
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  Speaker 0: Think about the friction that solves.
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  Speaker 0: Building a diet-specific shopping list that follows strict rules, and then optimizing that cart for the best price across three different grocery stores.
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  Speaker 1: Tasks that people find genuinely burdensome.
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  Speaker 1: The agents excel at that.
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  Speaker 0: And that shift from simple automation to autonomous decisions has radical implications for organizational design.
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  Speaker 0: This is critical for any PE operational team.
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  Speaker 1: Absolutely.
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  Speaker 1: There was new research from BCG and MIT Sloan Management Review from Sylvain Durant and Dr.
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  Speaker 1: Ann Klepp and Aziz Sawadogo, and it revealed that a remarkable seventy-six percent of people view agentic AI as a colleague.
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  Speaker 0: Not a tool.
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  Speaker 0: A colleague.
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  Speaker 1: A colleague, and that fundamentally changes your org chart.
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  Speaker 1: If your workforce includes digital colleagues, you suddenly need fewer layers of human managers.
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  Speaker 0: So organizations are already planning for this.
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  Speaker 1: They are.
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  Speaker 1: The sources show that leading organizations are anticipating flatter structures.
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  Speaker 1: Specifically, forty-five percent see a reduction in middle management, and almost a third, twenty-nine percent expect to hire fewer entry-level employees.
• 7:19
  Speaker 0: Because the ages are just absorbing that foundational knowledge work.
• 7:22
  Speaker 1: Right.
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  Speaker 1: For a firm doing M&A integration, this is a mandate to completely rethink your synergy model.
• 7:29
  Speaker 1: You're not just cutting headcount anymore.
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  Speaker 1: You're restructuring how whole departments operate around autonomous digital labor.
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  Speaker 0: Okay, so that brings us to the biggest challenge of all.
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  Speaker 1: Yeah.
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  Speaker 0: How do you connect this powerful autonomous technology back to actual business strategy and resilience?
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  Speaker 1: Right.
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  Speaker 1: What's stopping companies from capturing all this value we just talked about?
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  Speaker 0: The operational bottleneck.
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  Speaker 1: It's the operational bottleneck.
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  Speaker 1: Or what the sources were calling the AI value gap.
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  Speaker 1: Mark Byer Schoder highlighted the scale of this problem.
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  Speaker 1: Nearly ninety percent of leaders think AI will boost innovation.
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  Speaker 1: But only about forty percent are actually seeing a positive impact on their EBIT.
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  Speaker 0: Wow.
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  Speaker 0: That is a staggering gap.
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  Speaker 0: It
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  Speaker 1: is.
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  Speaker 1: And it confirms.
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  Speaker 1: the bottleneck is not the technology.
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  Speaker 1: It's the outdated workflows and operating models that were built for a pre-AI world.
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  Speaker 1: They
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  Speaker 0: just don't fit anymore.
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  Speaker 1: Not at all.
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  Speaker 1: Sundeep Rajasekaran's EUI survey confirmed this misalignment.
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  Speaker 1: Nine out of ten employees might be using AI, but only twenty-eight percent of organizations are getting high value outcomes from it.
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  Speaker 0: So what's the secret sauce for that twenty-eight percent?
• 8:32
  Speaker 1: It's all on the human side.
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  Speaker 1: They found success requires integrating continuous learning, reshaping the culture to actually trust the machine, and aligning rewards with new AI-driven targets.
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  Speaker 1: You can't just buy the tech.
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  Speaker 0: The talent foundations have to be there first.
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  Speaker 0: So the goal isn't just strategy execution, it's what's strategy realization.
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  Speaker 1: Exactly.
• 8:52
  Speaker 1: Mark D. Orlich argued that being seen as not strategic enough is often just a failure of communication.
• 8:59
  Speaker 1: The strategy isn't translated effectively into action down the line.
• 9:03
  Speaker 0: And that's where enterprise architecture, EA, comes in.
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  Speaker 1: It becomes mission critical.
• 9:07
  Speaker 1: Sumit Goenka emphasized that you need EA to link strategy, to capability, to process, transform.
• 9:13
  Speaker 1: Information isn't just software, it's re-architecting your internal capabilities so the strategy is actually executable.
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  Speaker 0: And Christian Rauch noted, this even applies to old school projects like ERP implementations.
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  Speaker 0: Right.
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  Speaker 1: The focus has to shift from pure delivery to capability building so the knowledge stays inside the company instead of walking out the door with the consultants.
• 9:34
  Speaker 0: This strategic shift is also redefining key leadership roles.
• 9:38
  Speaker 0: I'm thinking of the CFO.
• 9:39
  Speaker 1: A huge one.
• 9:40
  Speaker 1: George Logothetis and Bryant Huber detailed this evolution of the CFO from, you know, a scorekeeper to a real strategist who's driving tech adoption AI, ML, RPA, to overhaul the finance function.
• 9:53
  Speaker 0: But there's resistance.
• 9:54
  Speaker 0: Their data showed seventy-two percent of finance leaders are still stuck in that traditional backward-looking mindset.
• 10:00
  Speaker 1: Which just slows everything down.
• 10:02
  Speaker 1: You need that alignment between finance, tech, and product to make anything happen.
• 10:07
  Speaker 0: And all of this autonomy and complexity demands really rigorous governance.
• 10:12
  Speaker 0: Evan Benjamin stressed a crucial point about the EU AI Act.
• 10:15
  Speaker 1: That it's an engineering problem.
• 10:16
  Speaker 0: Right, not just a legal one.
• 10:18
  Speaker 0: The technical controls, traceability, audit logs, they have to be built into the systems from the start.
• 10:23
  Speaker 1: You can't just bolt on compliance later, and that governance failure starts right at the top.
• 10:27
  Speaker 1: Carol W. Strycher highlighted KPMG findings.
• 10:30
  Speaker 0: The board oversight numbers.
• 10:32
  Speaker 1: They're lagging badly.
• 10:33
  Speaker 1: Only twenty-seven percent of directors and private companies were satisfied that their board truly gets the impact of Gen AI on their business model.
• 10:40
  Speaker 0: And this extends to global mobility and tax too, right?
• 10:43
  Speaker 0: Which is vital for any international M&A.
• 10:46
  Speaker 1: It is.
• 10:47
  Speaker 1: Eric Duvoisen highlighted the twenty-twenty-five OECD model tax convention update.
• 10:52
  Speaker 1: It's clarifying permanent establishment, or PE, risks for remote work.
• 10:57
  Speaker 0: And just to be clear for everyone, we mean permanent establishment here, not private equity.
• 11:01
  Speaker 1: Precisely.
• 11:01
  Speaker 1: A crucial distinction.
• 11:03
  Speaker 1: The update suggests a fifty percent plus working time threshold could trigger a taxable presence.
• 11:09
  Speaker 1: That has to be in your post-MNA integration plan.
• 11:11
  Speaker 0: And on the geopolitical front.
• 11:13
  Speaker 1: Alexander Borsch noted that German companies aren't seeing Germany as a safe haven anymore, they're prioritizing expansion toward the rest of Europe, India and Southeast Asia.
• 11:22
  Speaker 1: A big signal.
• 11:23
  Speaker 0: So if the technology is changing everything, the imperative for consulting firms has to be differentiation.
• 11:29
  Speaker 0: Where should they be focusing their efforts?
• 11:31
  Speaker 1: The consensus across all the sources was really clear.
• 11:34
  Speaker 1: Depth.
• 11:35
  Speaker 1: Beat's breadth.
• 11:35
  Speaker 0: Be a specialist, not a generalist.
• 11:37
  Speaker 1: Exactly.
• 11:38
  Speaker 1: Henry Leon from BCG argued that gen AI value comes from strategic focus and deep application, not from scattered pilots across fifteen different departments.
• 11:48
  Speaker 1: You have to pick your spot and go deep.
• 11:50
  Speaker 0: That makes sense from the client's perspective too.
• 11:53
  Speaker 0: Lux Meyers observed that specialized consulting firms are the ones thriving right now.
• 11:57
  Speaker 1: Because they can articulate their value.
• 11:59
  Speaker 1: The generalists are struggling with that.
• 12:01
  Speaker 1: A specialist offers a clear problem, a repeatable approach, and a consistent outcome.
• 12:07
  Speaker 1: That reduces risk for the buyer.
• 12:09
  Speaker 0: And to be a specialist, you need very specific talent.
• 12:11
  Speaker 1: You do.
• 12:12
  Speaker 1: Zenis Lim defined the key traits for an AI product manager.
• 12:16
  Speaker 1: He said they need to be a learn-it-all, not a know-it-all, and really prioritize empathy and the human side of product design.
• 12:22
  Speaker 0: which brings us full circle right back to the human element.
• 12:25
  Speaker 0: We've seen this massive shift to agentic AI requires a complete organizational and governance rethink.
• 12:31
  Speaker 1: A total overhaul.
• 12:32
  Speaker 0: But the enduring value of consulting, whether it's an M&A or digital transformation, still hinges on human expertise, on critical judgment, and that deep specialization that tech alone.
• 12:44
  Speaker 0: just can't replace.
• 12:46
  Speaker 0: If you enjoyed this deep dive, new deep dives drop every two weeks.
• 12:50
  Speaker 0: Also check out our other editions on private equity, venture capital and M&A.
• 12:54
  Speaker 1: You know, the most profound insight for me from these two weeks is just the sheer organizational challenge.
• 12:59
  Speaker 1: It's not about the tech anymore.
• 13:01
  Speaker 0: It's about the structure.
• 13:02
  Speaker 1: It's about the structure.
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  Speaker 1: If agentic AI truly transforms entire business functions, moving past just automating a process, how can leaders possibly restructure their organizations fast enough?
• 13:13
  Speaker 1: How do you manage and train and trust these new digital colleagues before your competitors build fully autonomous functions that just accelerate out of sight?
• 13:22
  Speaker 1: That's
• 13:22
  Speaker 0: the question.
• 13:23
  Speaker 1: That internal rearchitecture is the critical strategic question facing every single C-suite leader heading into twenty
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  Speaker 0: twenty six.