Best of LinkedIn: Strategy & Consulting CW 48/ 49

00:00:00: provided by Thomas Allgeier and Frennis, based on the most relevant LinkedIn posts about strategy and consulting in CW-Forty-Eight and Forty-Nine.

00:00:07: Frennis specializes in B-to-B market research for strategy and consulting teams with a focus on tech and ICT.

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00:00:32: Welcome to the deep dive.

00:00:34: Our mission today is, well... Pretty laser focused.

00:00:37: We are tracking a fundamental shift happening right now in the strategy and consulting world.

00:00:41: For the past year, it's all been about AI experimentation, you know, the fun, fast proofs of concept.

00:00:46: The playground phase.

00:00:47: Exactly.

00:00:48: But now the pivot is happening.

00:00:49: We're moving from that playground to full business model redesign.

00:00:52: And that

00:00:53: is the critical difference.

00:00:54: The sources we've been tracking over the last two weeks, they all point to this.

00:00:57: We're shifting from thinking of AI as just another feature to realizing it has to be the core operating system.

00:01:03: So the conversation is no longer if

00:01:05: No, it's all about how.

00:01:07: How you redesign your governance, how you rethink your talent needs, and how you define these new value-based economics.

00:01:15: The firms making those hard choices right now are the ones pulling ahead.

00:01:17: Okay, let's unpack that.

00:01:19: Theme one.

00:01:20: agentic AI as the enterprise operating system.

00:01:24: This came up a lot.

00:01:25: We saw a huge consensus coming out of Reuters and XST.

00:01:28: And I thought Daniel Vieca's Rogers summarized it perfectly.

00:01:31: The new horizontal.

00:01:32: The new horizontal.

00:01:33: Yes.

00:01:33: It's not a vertical feature that just sits in marketing or HR anymore.

00:01:37: It's this foundational layer that cuts across everything.

00:01:40: And that framing is just essential.

00:01:42: It dictates where the budget and frankly where the attention needs to flow.

00:01:45: Christian Klein, the CEO of SAP, he really hammered this point home.

00:01:49: Right.

00:01:49: He's stressed that to get any tangible impact, you know, beyond the hype, AI has to be deeply embedded in the business processes.

00:01:58: Yeah.

00:01:58: In the core model itself.

00:02:00: It's so much more than just plugging in some sophisticated LLM.

00:02:03: And that commitment, it immediately slams into the data foundation problem, doesn't it?

00:02:07: And LLM is only as smart as...

00:02:08: Well, the wealth of knowledge it's built on.

00:02:10: Absolutely.

00:02:11: Ilya Kurishko made this point and pretty bluntly, he said, AI without a connected data layer is just a proof of concept.

00:02:18: Ouch, but true.

00:02:19: It is.

00:02:20: If you try to scale AI on a foundation of messy siloed enterprise data, all you're doing is scaling noise.

00:02:27: You're not scaling value.

00:02:29: You create a data trust problem before you even get to the intelligence problem.

00:02:33: This focus on efficiency and clean data, it naturally leads to the whole debate around model size.

00:02:38: We saw a really interesting distinction being drawn here.

00:02:49: smaller versions of big LLMs.

00:02:52: And that distinction is profound for an enterprise.

00:02:54: So break that down.

00:02:55: What's the actual operational difference for a company trying to embed AI and to say an invoice approval workflow?

00:03:01: Well, SLMs are purpose-built.

00:03:03: They are task-specific, extremely lightweight, and they offer superior, often much faster performance for those specific applications.

00:03:10: A huge generalized model is overkill.

00:03:13: So it's about using the right tool for the job.

00:03:15: Precisely.

00:03:16: Reimov cited Polygraph AI's PII extraction model.

00:03:21: It's a tiny hundred and sixty megabytes.

00:03:23: Think about that for a second.

00:03:25: That small fives means you can deploy it locally, which cuts down your cloud latency and cost dramatically.

00:03:31: That's a huge

00:03:32: deal.

00:03:32: It is.

00:03:33: The future isn't just about accessing massive compute power.

00:03:36: It's about deploying this purpose built, super efficient intelligence right where the work is actually happening.

00:03:43: And that realization is driving the next big architectural shift in consulting.

00:03:48: Brahman and Dagoche noted that enterprises aren't just becoming digital anymore, they're becoming intelligent.

00:03:53: The key difference.

00:03:54: Which means your traditional workflows.

00:03:56: They're evolving into decision flows, all orchestrated by these agents.

00:04:00: And that's how we get to this self-driving enterprise trend.

00:04:03: Nina Eisenman, citing Joe Deepa of EY, highlighted this vision.

00:04:07: It's not about simple automation scripts anymore.

00:04:09: We're talking about AI agents orchestrating themselves, managing complex processes autonomously.

00:04:14: So the agent goes from being a helper tool

00:04:16: to a core part of the automation layer itself.

00:04:18: And that's where you see the measurable gains in throughput and cycle time.

00:04:22: Okay, so if that's the architectural shift in theme one, it completely changes the business equation.

00:04:27: If agentic AI is the new OS, Then, theme two has to be, how on earth do we price this?

00:04:35: Exactly.

00:04:36: The consulting model is getting a huge reset in its economics and in talent.

00:04:40: James O'Dowd observed that the industry is basically splitting in two.

00:04:44: And the split is based on structure.

00:04:46: It's

00:04:46: based on structure.

00:04:47: You have the legacy partnership models often saddle with high SG&A costs.

00:04:51: It makes them slow to innovate, locks them into these fixed cost structure.

00:04:54: Eurocratic.

00:04:55: Fairy.

00:04:55: Yeah.

00:04:55: 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.

00:05:06: The people who want to build something modern, not fight legacy systems.

00:05:10: And that structural split is putting a ton of pressure on the old pricing model.

00:05:14: Pierre Fitter brought up Rita McGrath's argument here.

00:05:16: Which is

00:05:17: so compelling.

00:05:18: that the billable hour is just completely incompatible with AI efficiency.

00:05:22: If AI lets a senior consultant do in two hours what used to take a whole team of juniors ten hours.

00:05:28: How do you bill for that?

00:05:29: The client won't pay the old rate.

00:05:31: The whole game changes from tracking effort to capturing value.

00:05:35: It's pushing firms hard toward value-based pricing.

00:05:38: toward retainers subscriptions.

00:05:40: This is about achieving what Maximilian Fink called commercial maturity.

00:05:44: Commercial maturity.

00:05:45: Yeah.

00:05:45: 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.

00:05:52: I have to push back on that just a bit.

00:05:53: Pricing for impact in strategy consulting can be so tricky to find up front, right?

00:05:58: It's not like a software implementation with clear ROI.

00:06:01: How do firms show this maturity without just, you know, repackaging a retainer?

00:06:05: It demands a level of transparency and data rigor that just wasn't required before.

00:06:11: 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.

00:06:19: So it's about the secret sauce.

00:06:21: It is.

00:06:22: If you're selling a governance redesign, the outcome is measured in risk production or faster decision cycles, not just hours spent in meetings.

00:06:29: You have to embed your AI tool, your IP, into the client's operations long term.

00:06:36: And that naturally leads to subscriptions.

00:06:38: Okay, now this is where it gets fascinating on the customer side.

00:06:41: The zero-click threat.

00:06:43: Casey Lobo from Deloitte Digital was talking about the immediate rise of agentic commerce.

00:06:48: This is a game changer.

00:06:49: Because the consumer is no longer a human browsing a website.

00:06:53: The consumer is now an autonomous AI agent.

00:06:56: Exactly.

00:06:57: And what does that mean in practice?

00:06:58: It means retailers have to build a second storefront.

00:07:02: This story is in visual.

00:07:04: It's engineered for machine logic structured data, APIs.

00:07:07: A machine readable store.

00:07:08: Right.

00:07:09: The AI agent doesn't care about your beautiful homepage.

00:07:11: It queries three vendors for specs, compares them, and executes the purchase based on pure logic.

00:07:17: It bypasses the entire traditional consumer journey.

00:07:20: If your architecture is locked behind an old website, you're invisible to that AI scout.

00:07:24: And that machine first thinking applies internally too.

00:07:28: to the consultants themselves.

00:07:29: Christian Rouch outlined this whole new skill set for future ERP consultants.

00:07:34: They

00:07:34: have to move way beyond being system fixers.

00:07:37: The job is now to be a trusted strategic advisor.

00:07:40: So what does that require?

00:07:41: Three things.

00:07:42: First, think business before technology.

00:07:44: Second, be fluent in data interpretation.

00:07:47: And third, you have to master change management.

00:07:50: It's about connecting the systems to the bigger strategy.

00:07:53: As David Garfield noted, the focus shifts to wisdom, empathy, and judgment skills.

00:07:57: AI can enhance, but it can't replicate.

00:07:59: Okay, let's pivot.

00:08:00: How is this actually impacting day-to-day work?

00:08:03: Theme three, work and leadership.

00:08:06: We're seeing these workflows appear first in high volume areas, right?

00:08:09: Like procurement.

00:08:10: Tanya W shared a very clear breakdown of the impact there.

00:08:13: Yeah, in procurement, AI is taking over the transactional tasks.

00:08:16: Your purchase order processing, invoice approvals, basic spend analysis, that's critical for efficiency.

00:08:21: But, and this is a big, but the strategic functions remain firmly human led.

00:08:25: Critical contract negotiations, complex supplier relationship management, and very importantly, ethical procurement.

00:08:32: Which means the upskilling has to go in a very specific direction.

00:08:36: Absolutely.

00:08:37: If AI handles the speed in the volume, The humans have to master the values and the complexity.

00:08:43: So you upskill in advanced analytics and, crucially, in ESG environmental, social, and governance.

00:08:49: You need people who can assess the risk and reputation of a supply chain, while the AI just handles the velocity.

00:08:55: This level of integration is changing how people even think about technology.

00:08:59: Hassan Benothman cited research showing seventy-six percent of executives now describe a gented AI as a coworker, not just a tool.

00:09:07: That's a huge number.

00:09:08: It is, but here's the gap.

00:09:09: 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?

00:09:17: Probably not seventy-six percent.

00:09:19: Not even close.

00:09:20: Lucas-Corta highlighted the core problem.

00:09:22: Agenetic systems have partial eponomy.

00:09:24: They shape decisions.

00:09:25: They adapt.

00:09:26: That behavior doesn't fit into our old models of ownership or accountability.

00:09:30: You have to change the decision rights before you flip the switch on the system.

00:09:33: And the human adoption challenge is still massive, even with clear benefits.

00:09:38: Valentino Coaster mentioned HBS research that showed AI users deliver forty percent higher quality results and are twenty-five percent quicker.

00:09:46: And yet.

00:09:46: And yet, real adoption needs practical, guided ways to integrate AI.

00:09:51: You have to respect the diversity of a multi-generational workforce.

00:09:55: It's not just a skills gap, it's a management problem.

00:09:57: It's fundamentally cultural.

00:09:58: Martin Reeves from BCG said, the key bottlenecks to creating these intelligent hybrid organizations, they're cultural, not technical.

00:10:07: Leaders get distracted by the shiny new tech and they ignore the internal resistance it creates.

00:10:11: Right.

00:10:12: And Mark Diorlich added a critical insight for leaders here.

00:10:15: Enduring competitive advantage doesn't come from having the smartest CEO.

00:10:19: It comes from deep discipline engagement in the operational systems where value is actually created.

00:10:24: You have to get out of the strategy to exit into the engine room.

00:10:26: Into the

00:10:27: engine room.

00:10:28: Okay, let's move to our final theme, which ties investment to all of this.

00:10:31: M&A, the investment landscape and strategic governance.

00:10:35: Despite all the economic uncertainty, the deal pipeline seems pretty robust.

00:10:40: Surprisingly robust, yeah.

00:10:42: Lennon and Guayan reported that Morgan Stanley is seeing strong M&A activity, especially across tech, healthcare, and financials.

00:10:50: And that signal seems consistent.

00:10:52: Charles Schwab's CEO, Rick Worcester, he confirmed they're planning more acquisitions.

00:10:56: It points to ongoing consolidation, especially in financial services.

00:11:00: But these deals aren't just for scale.

00:11:03: They're intensely strategic.

00:11:05: They're focused on securing that data in governance backbone.

00:11:09: Aziz Sawadogo detailed some of these major moves,

00:11:11: like IBM buying Confluent,

00:11:13: or ServiceNow acquiring Data.World.

00:11:16: Those moves are clearly focused on data, metadata, and the governance you need for generative and agentic AI.

00:11:22: They are buying the core components, the plumbing, for an AI-first architecture.

00:11:26: And looking at financing, Ilya Karishko observed at Reuters Neckis T that debt markets are aggressively funding these AI infrastructure builds.

00:11:34: But he also raised a major concern.

00:11:35: The circular financing issue.

00:11:37: Explain what that means in this context.

00:11:39: It describes a potential boom bust dynamic.

00:11:42: A firm raises a huge amount of capital, mostly to buy compute GPUs, data centers.

00:11:46: They use that to build a product which lets them raise even more money, often from the same investors, in this continuous loop.

00:11:53: A self-feeding cycle.

00:11:54: Exactly.

00:11:55: And capital allocators need to watch that very closely for doubles.

00:11:58: The underlying value has to be real, not just a measure of your computational capacity.

00:12:03: That

00:12:04: cycle really just reinforces the importance of governance.

00:12:07: Nina Eisenman pointed to sovereign AI, this push for region-specific models and regulations as a major trend for twenty twenty six.

00:12:15: This isn't just politics.

00:12:16: it's a whole new compliance layer for global firms.

00:12:20: And that brings us right back to trust.

00:12:22: Lucas Biller stressed this is the critical challenge for AI adoption especially in sensitive sectors like pharma or health care.

00:12:29: trust has to be the prerequisite for scale.

00:12:31: Ramesh Kolapara echoed this.

00:12:33: Without trust, adoption just stalls.

00:12:35: Which is why Nicholas Lealiakis framed Europe's strategic power not as chasing these spectacular moonshots.

00:12:41: But as building infrastructures of trust, like GDPR, these regulations offer long-term stability.

00:12:48: And you could argue that's a more valuable strategic asset than pure speed in such a volatile environment.

00:12:54: It's about building a structured, habitable future for this intelligence.

00:12:58: So the overarching message from these last two weeks of insights is, I think, very clear.

00:13:03: AI has stopped being just an opportunity.

00:13:05: It's now becoming a constraint.

00:13:07: It's redefining how value is priced, where talent is placed, and which firms are actually going to thrive.

00:13:12: 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.

00:13:22: If

00:13:22: you enjoyed this deep dive, new episodes drop every two weeks.

00:13:25: Also, check out our other editions on private equity.

00:13:28: venture capital, and M&A.

00:13:30: Before we go, here's a thought to leave you with.

00:13:32: Mark Byer-Schoter made the point that AI won't kill your company.

00:13:36: Your politics will.

00:13:37: Think about that.

00:13:39: 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.

00:13:49: So the question for you is, if intelligence becomes ambient, who inside your organization loses power?

00:13:54: and are you prepared for that internal civil war?

00:13:57: Thank you for joining us and don't forget to hit that subscribe button.

00:13:59: We'll be back soon with another deep dive.