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Best of LinkedIn: Strategy & Consulting CW 48/ 49 · Best of LinkedIn: Strategy, M&A & Investments

• 0:00
  Speaker 1: provided by Thomas Allgeier and Frennis, based on the most relevant LinkedIn posts about strategy and consulting in CW-Forty-Eight and Forty-Nine.
• 0:07
  Speaker 1: Frennis specializes in B-to-B market research for strategy and consulting teams with a focus on tech and ICT.
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  Speaker 1: This edition is brought to you by our partner Deal Room.
• 0:17
  Speaker 1: Help shape their state of M&A's twenty-twenty-six report by taking their survey.
• 0:21
  Speaker 1: This is your chance to share how you approach sourcing.
• 0:24
  Speaker 1: diligence and integration and see how your experience compares to peers.
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  Speaker 1: Find the link to the survey in the description.
• 0:32
  Speaker 1: Welcome to the deep dive.
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  Speaker 1: Our mission today is, well... Pretty laser focused.
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  Speaker 1: We are tracking a fundamental shift happening right now in the strategy and consulting world.
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  Speaker 1: For the past year, it's all been about AI experimentation, you know, the fun, fast proofs of concept.
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  Speaker 0: The playground phase.
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  Speaker 0: Exactly.
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  Speaker 1: But now the pivot is happening.
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  Speaker 1: We're moving from that playground to full business model redesign.
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  Speaker 1: And that
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  Speaker 0: is the critical difference.
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  Speaker 0: The sources we've been tracking over the last two weeks, they all point to this.
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  Speaker 0: We're shifting from thinking of AI as just another feature to realizing it has to be the core operating system.
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  Speaker 1: So the conversation is no longer if
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  Speaker 0: No, it's all about how.
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  Speaker 0: How you redesign your governance, how you rethink your talent needs, and how you define these new value-based economics.
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  Speaker 0: The firms making those hard choices right now are the ones pulling ahead.
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  Speaker 1: Okay, let's unpack that.
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  Speaker 1: Theme one.
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  Speaker 1: agentic AI as the enterprise operating system.
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  Speaker 1: This came up a lot.
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  Speaker 1: We saw a huge consensus coming out of Reuters and XST.
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  Speaker 1: And I thought Daniel Vieca's Rogers summarized it perfectly.
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  Speaker 0: The new horizontal.
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  Speaker 1: The new horizontal.
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  Speaker 1: Yes.
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  Speaker 1: It's not a vertical feature that just sits in marketing or HR anymore.
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  Speaker 1: It's this foundational layer that cuts across everything.
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  Speaker 0: And that framing is just essential.
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  Speaker 0: It dictates where the budget and frankly where the attention needs to flow.
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  Speaker 0: Christian Klein, the CEO of SAP, he really hammered this point home.
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  Speaker 0: Right.
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  Speaker 0: He's stressed that to get any tangible impact, you know, beyond the hype, AI has to be deeply embedded in the business processes.
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  Speaker 0: Yeah.
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  Speaker 0: In the core model itself.
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  Speaker 0: It's so much more than just plugging in some sophisticated LLM.
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  Speaker 1: And that commitment, it immediately slams into the data foundation problem, doesn't it?
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  Speaker 1: And LLM is only as smart as...
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  Speaker 0: Well, the wealth of knowledge it's built on.
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  Speaker 0: Absolutely.
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  Speaker 0: Ilya Kurishko made this point and pretty bluntly, he said, AI without a connected data layer is just a proof of concept.
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  Speaker 1: Ouch, but true.
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  Speaker 0: It is.
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  Speaker 0: If you try to scale AI on a foundation of messy siloed enterprise data, all you're doing is scaling noise.
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  Speaker 0: You're not scaling value.
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  Speaker 0: You create a data trust problem before you even get to the intelligence problem.
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  Speaker 1: This focus on efficiency and clean data, it naturally leads to the whole debate around model size.
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  Speaker 1: We saw a really interesting distinction being drawn here.
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  Speaker 0: smaller versions of big LLMs.
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  Speaker 0: And that distinction is profound for an enterprise.
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  Speaker 1: So break that down.
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  Speaker 1: What's the actual operational difference for a company trying to embed AI and to say an invoice approval workflow?
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  Speaker 0: Well, SLMs are purpose-built.
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  Speaker 0: They are task-specific, extremely lightweight, and they offer superior, often much faster performance for those specific applications.
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  Speaker 0: A huge generalized model is overkill.
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  Speaker 1: So it's about using the right tool for the job.
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  Speaker 0: Precisely.
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  Speaker 0: Reimov cited Polygraph AI's PII extraction model.
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  Speaker 0: It's a tiny hundred and sixty megabytes.
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  Speaker 0: Think about that for a second.
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  Speaker 0: That small fives means you can deploy it locally, which cuts down your cloud latency and cost dramatically.
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  Speaker 1: That's a huge
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  Speaker 0: deal.
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  Speaker 0: It is.
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  Speaker 0: The future isn't just about accessing massive compute power.
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  Speaker 0: It's about deploying this purpose built, super efficient intelligence right where the work is actually happening.
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  Speaker 1: And that realization is driving the next big architectural shift in consulting.
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  Speaker 1: Brahman and Dagoche noted that enterprises aren't just becoming digital anymore, they're becoming intelligent.
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  Speaker 0: The key difference.
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  Speaker 1: Which means your traditional workflows.
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  Speaker 1: They're evolving into decision flows, all orchestrated by these agents.
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  Speaker 0: And that's how we get to this self-driving enterprise trend.
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  Speaker 0: Nina Eisenman, citing Joe Deepa of EY, highlighted this vision.
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  Speaker 0: It's not about simple automation scripts anymore.
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  Speaker 0: We're talking about AI agents orchestrating themselves, managing complex processes autonomously.
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  Speaker 1: So the agent goes from being a helper tool
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  Speaker 0: to a core part of the automation layer itself.
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  Speaker 0: And that's where you see the measurable gains in throughput and cycle time.
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  Speaker 1: Okay, so if that's the architectural shift in theme one, it completely changes the business equation.
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  Speaker 1: If agentic AI is the new OS, Then, theme two has to be, how on earth do we price this?
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  Speaker 0: Exactly.
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  Speaker 0: The consulting model is getting a huge reset in its economics and in talent.
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  Speaker 0: James O'Dowd observed that the industry is basically splitting in two.
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  Speaker 1: And the split is based on structure.
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  Speaker 1: It's
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  Speaker 0: based on structure.
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  Speaker 0: You have the legacy partnership models often saddle with high SG&A costs.
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  Speaker 0: It makes them slow to innovate, locks them into these fixed cost structure.
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  Speaker 1: Eurocratic.
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  Speaker 0: Fairy.
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  Speaker 0: Yeah.
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  Speaker 0: And then you have these... New agile platforms, they're built for speed, they use focused M&A to add capabilities, and crucially, they're becoming magnets for that ambitious mid-level and senior talent.
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  Speaker 0: The people who want to build something modern, not fight legacy systems.
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  Speaker 1: And that structural split is putting a ton of pressure on the old pricing model.
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  Speaker 1: Pierre Fitter brought up Rita McGrath's argument here.
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  Speaker 1: Which is
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  Speaker 0: so compelling.
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  Speaker 1: that the billable hour is just completely incompatible with AI efficiency.
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  Speaker 1: If AI lets a senior consultant do in two hours what used to take a whole team of juniors ten hours.
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  Speaker 1: How do you bill for that?
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  Speaker 1: The client won't pay the old rate.
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  Speaker 0: The whole game changes from tracking effort to capturing value.
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  Speaker 0: It's pushing firms hard toward value-based pricing.
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  Speaker 0: toward retainers subscriptions.
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  Speaker 0: This is about achieving what Maximilian Fink called commercial maturity.
• 5:44
  Speaker 1: Commercial maturity.
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  Speaker 1: Yeah.
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  Speaker 0: Winning firms are the ones that design for measurable outcomes and price for actual impact, not just, you know, being the fastest or the cheapest.
• 5:52
  Speaker 1: I have to push back on that just a bit.
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  Speaker 1: Pricing for impact in strategy consulting can be so tricky to find up front, right?
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  Speaker 1: It's not like a software implementation with clear ROI.
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  Speaker 1: How do firms show this maturity without just, you know, repackaging a retainer?
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  Speaker 0: It demands a level of transparency and data rigor that just wasn't required before.
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  Speaker 0: It means the firm has to have strong proprietary IP, their own data, their own models, their own processes that are crucial to delivering that outcome.
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  Speaker 1: So it's about the secret sauce.
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  Speaker 0: It is.
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  Speaker 0: If you're selling a governance redesign, the outcome is measured in risk production or faster decision cycles, not just hours spent in meetings.
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  Speaker 0: You have to embed your AI tool, your IP, into the client's operations long term.
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  Speaker 0: And that naturally leads to subscriptions.
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  Speaker 1: Okay, now this is where it gets fascinating on the customer side.
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  Speaker 1: The zero-click threat.
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  Speaker 1: Casey Lobo from Deloitte Digital was talking about the immediate rise of agentic commerce.
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  Speaker 0: This is a game changer.
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  Speaker 1: Because the consumer is no longer a human browsing a website.
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  Speaker 1: The consumer is now an autonomous AI agent.
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  Speaker 0: Exactly.
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  Speaker 0: And what does that mean in practice?
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  Speaker 0: It means retailers have to build a second storefront.
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  Speaker 1: This story is in visual.
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  Speaker 1: It's engineered for machine logic structured data, APIs.
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  Speaker 0: A machine readable store.
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  Speaker 1: Right.
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  Speaker 1: The AI agent doesn't care about your beautiful homepage.
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  Speaker 1: It queries three vendors for specs, compares them, and executes the purchase based on pure logic.
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  Speaker 1: It bypasses the entire traditional consumer journey.
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  Speaker 1: If your architecture is locked behind an old website, you're invisible to that AI scout.
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  Speaker 1: And that machine first thinking applies internally too.
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  Speaker 1: to the consultants themselves.
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  Speaker 1: Christian Rouch outlined this whole new skill set for future ERP consultants.
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  Speaker 1: They
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  Speaker 0: have to move way beyond being system fixers.
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  Speaker 0: The job is now to be a trusted strategic advisor.
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  Speaker 1: So what does that require?
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  Speaker 0: Three things.
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  Speaker 0: First, think business before technology.
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  Speaker 0: Second, be fluent in data interpretation.
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  Speaker 0: And third, you have to master change management.
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  Speaker 0: It's about connecting the systems to the bigger strategy.
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  Speaker 0: As David Garfield noted, the focus shifts to wisdom, empathy, and judgment skills.
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  Speaker 0: AI can enhance, but it can't replicate.
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  Speaker 1: Okay, let's pivot.
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  Speaker 1: How is this actually impacting day-to-day work?
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  Speaker 1: Theme three, work and leadership.
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  Speaker 1: We're seeing these workflows appear first in high volume areas, right?
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  Speaker 1: Like procurement.
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  Speaker 1: Tanya W shared a very clear breakdown of the impact there.
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  Speaker 0: Yeah, in procurement, AI is taking over the transactional tasks.
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  Speaker 0: Your purchase order processing, invoice approvals, basic spend analysis, that's critical for efficiency.
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  Speaker 0: But, and this is a big, but the strategic functions remain firmly human led.
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  Speaker 0: Critical contract negotiations, complex supplier relationship management, and very importantly, ethical procurement.
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  Speaker 1: Which means the upskilling has to go in a very specific direction.
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  Speaker 0: Absolutely.
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  Speaker 0: If AI handles the speed in the volume, The humans have to master the values and the complexity.
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  Speaker 0: So you upskill in advanced analytics and, crucially, in ESG environmental, social, and governance.
• 8:49
  Speaker 0: You need people who can assess the risk and reputation of a supply chain, while the AI just handles the velocity.
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  Speaker 1: This level of integration is changing how people even think about technology.
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  Speaker 1: Hassan Benothman cited research showing seventy-six percent of executives now describe a gented AI as a coworker, not just a tool.
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  Speaker 0: That's a huge number.
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  Speaker 0: It is, but here's the gap.
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  Speaker 0: If seventy-six percent see it as a co-worker, how many have actually redesigned the governance and the roles around these new hybrid human AI teams?
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  Speaker 1: Probably not seventy-six percent.
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  Speaker 0: Not even close.
• 9:20
  Speaker 0: Lucas-Corta highlighted the core problem.
• 9:22
  Speaker 0: Agenetic systems have partial eponomy.
• 9:24
  Speaker 0: They shape decisions.
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  Speaker 0: They adapt.
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  Speaker 0: That behavior doesn't fit into our old models of ownership or accountability.
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  Speaker 0: You have to change the decision rights before you flip the switch on the system.
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  Speaker 1: And the human adoption challenge is still massive, even with clear benefits.
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  Speaker 1: Valentino Coaster mentioned HBS research that showed AI users deliver forty percent higher quality results and are twenty-five percent quicker.
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  Speaker 0: And yet.
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  Speaker 1: And yet, real adoption needs practical, guided ways to integrate AI.
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  Speaker 1: You have to respect the diversity of a multi-generational workforce.
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  Speaker 1: It's not just a skills gap, it's a management problem.
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  Speaker 0: It's fundamentally cultural.
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  Speaker 0: Martin Reeves from BCG said, the key bottlenecks to creating these intelligent hybrid organizations, they're cultural, not technical.
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  Speaker 0: Leaders get distracted by the shiny new tech and they ignore the internal resistance it creates.
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  Speaker 1: Right.
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  Speaker 1: And Mark Diorlich added a critical insight for leaders here.
• 10:15
  Speaker 1: Enduring competitive advantage doesn't come from having the smartest CEO.
• 10:19
  Speaker 1: It comes from deep discipline engagement in the operational systems where value is actually created.
• 10:24
  Speaker 0: You have to get out of the strategy to exit into the engine room.
• 10:26
  Speaker 0: Into the
• 10:27
  Speaker 1: engine room.
• 10:28
  Speaker 1: Okay, let's move to our final theme, which ties investment to all of this.
• 10:31
  Speaker 1: M&A, the investment landscape and strategic governance.
• 10:35
  Speaker 1: Despite all the economic uncertainty, the deal pipeline seems pretty robust.
• 10:40
  Speaker 0: Surprisingly robust, yeah.
• 10:42
  Speaker 0: Lennon and Guayan reported that Morgan Stanley is seeing strong M&A activity, especially across tech, healthcare, and financials.
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  Speaker 1: And that signal seems consistent.
• 10:52
  Speaker 1: Charles Schwab's CEO, Rick Worcester, he confirmed they're planning more acquisitions.
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  Speaker 1: It points to ongoing consolidation, especially in financial services.
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  Speaker 0: But these deals aren't just for scale.
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  Speaker 0: They're intensely strategic.
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  Speaker 0: They're focused on securing that data in governance backbone.
• 11:09
  Speaker 0: Aziz Sawadogo detailed some of these major moves,
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  Speaker 1: like IBM buying Confluent,
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  Speaker 0: or ServiceNow acquiring Data.World.
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  Speaker 0: Those moves are clearly focused on data, metadata, and the governance you need for generative and agentic AI.
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  Speaker 0: They are buying the core components, the plumbing, for an AI-first architecture.
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  Speaker 1: And looking at financing, Ilya Karishko observed at Reuters Neckis T that debt markets are aggressively funding these AI infrastructure builds.
• 11:34
  Speaker 1: But he also raised a major concern.
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  Speaker 0: The circular financing issue.
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  Speaker 1: Explain what that means in this context.
• 11:39
  Speaker 0: It describes a potential boom bust dynamic.
• 11:42
  Speaker 0: A firm raises a huge amount of capital, mostly to buy compute GPUs, data centers.
• 11:46
  Speaker 0: They use that to build a product which lets them raise even more money, often from the same investors, in this continuous loop.
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  Speaker 1: A self-feeding cycle.
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  Speaker 0: Exactly.
• 11:55
  Speaker 0: And capital allocators need to watch that very closely for doubles.
• 11:58
  Speaker 0: The underlying value has to be real, not just a measure of your computational capacity.
• 12:03
  Speaker 0: That
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  Speaker 1: cycle really just reinforces the importance of governance.
• 12:07
  Speaker 1: Nina Eisenman pointed to sovereign AI, this push for region-specific models and regulations as a major trend for twenty twenty six.
• 12:15
  Speaker 1: This isn't just politics.
• 12:16
  Speaker 1: it's a whole new compliance layer for global firms.
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  Speaker 0: And that brings us right back to trust.
• 12:22
  Speaker 0: Lucas Biller stressed this is the critical challenge for AI adoption especially in sensitive sectors like pharma or health care.
• 12:29
  Speaker 0: trust has to be the prerequisite for scale.
• 12:31
  Speaker 0: Ramesh Kolapara echoed this.
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  Speaker 0: Without trust, adoption just stalls.
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  Speaker 1: Which is why Nicholas Lealiakis framed Europe's strategic power not as chasing these spectacular moonshots.
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  Speaker 1: But as building infrastructures of trust, like GDPR, these regulations offer long-term stability.
• 12:48
  Speaker 1: And you could argue that's a more valuable strategic asset than pure speed in such a volatile environment.
• 12:54
  Speaker 1: It's about building a structured, habitable future for this intelligence.
• 12:58
  Speaker 0: So the overarching message from these last two weeks of insights is, I think, very clear.
• 13:03
  Speaker 0: AI has stopped being just an opportunity.
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  Speaker 0: It's now becoming a constraint.
• 13:07
  Speaker 0: It's redefining how value is priced, where talent is placed, and which firms are actually going to thrive.
• 13:12
  Speaker 0: The ones who are redesigning their core operating models, their governance, their talent pathways, all around this idea of ambient intelligence, they're the ones securing a real enduring competitive advantage.
• 13:22
  Speaker 0: If
• 13:22
  Speaker 1: you enjoyed this deep dive, new episodes drop every two weeks.
• 13:25
  Speaker 1: Also, check out our other editions on private equity.
• 13:28
  Speaker 1: venture capital, and M&A.
• 13:30
  Speaker 1: Before we go, here's a thought to leave you with.
• 13:32
  Speaker 1: Mark Byer-Schoter made the point that AI won't kill your company.
• 13:36
  Speaker 1: Your politics will.
• 13:37
  Speaker 1: Think about that.
• 13:39
  Speaker 1: If intelligence becomes ambient, if efficiency explodes and decision flows replace workflows, it threatens everyone who relied on information asymmetry and slow processes for their internal power.
• 13:49
  Speaker 1: So the question for you is, if intelligence becomes ambient, who inside your organization loses power?
• 13:54
  Speaker 1: and are you prepared for that internal civil war?
• 13:57
  Speaker 1: Thank you for joining us and don't forget to hit that subscribe button.
• 13:59
  Speaker 1: We'll be back soon with another deep dive.