Best of LinkedIn: AI in B2B Marketing CW 39/ 40

00:00:00: This episode is provided by Thomas Allgaier and Frennis based on the most relevant LinkedIn posts about AI and B to B marketing in calendar weeks, thirty nine and forty.

00:00:09: Frennis is a B to B market research company helping enterprise marketing teams sharpen their strategies and outreach with customer segmentation, ideal customer profiles and deep dives, customer needs analysis and buying center insights.

00:00:22: Okay, let's let's unpack this.

00:00:23: We're doing a deep dive into the latest in B to B marketing, really focusing on the AI trends we've spotted across LinkedIn over the last couple of weeks, calendar weeks, thirty nine and forty.

00:00:33: And looking at the chatter, there's this clear pretty seismic shift happening, wouldn't you say?

00:00:38: B to B seems to finally be moving away from that kind of hesitant experimentation phase and more into, you know, committed, dedicated execution.

00:00:47: Exactly.

00:00:48: And what's really fascinating, I think, is how the focus has narrowed.

00:00:51: It's quite traumatic, actually.

00:00:52: It's not really if we should use AI anymore.

00:00:54: Right.

00:00:55: It's all about how we make it work, like right now.

00:00:58: We're seeing leaders leaning heavily into, well, three main areas, getting ready for AI search, deploying these agentic workflows and making some pretty pragmatic bets on where to put the talent and the budget.

00:01:13: So we've kind of synthesized those top insights for you, aiming to give you a sort of clear strategy playbook.

00:01:19: And the central tension we're kind of exploring today, I think, is that AI has just... amplified production speed like crazy, hasn't it?

00:01:26: Oh, yeah.

00:01:26: Beyond anything we've seen.

00:01:28: But that speed, it's exposing these huge bottlenecks in two really crucial areas, visibility and originality.

00:01:36: That's

00:01:36: a great way to put it.

00:01:37: So let's start with visibility.

00:01:38: OK, so here's where that visibility piece gets, well, critical.

00:01:42: We absolutely need to talk about generative engine optimization.

00:01:45: Geo.

00:01:45: Geo, yeah.

00:01:46: It's being positioned almost universally now as the new SEO, right?

00:01:50: But for this AI-led discovery world, think, chat GPT, Gemini, Perplexity.

00:01:56: So if that traditional search volume is shifting away from the classic ten blue links, what are we actually optimizing for now?

00:02:04: And how different is this game, really?

00:02:07: Well, it's a total game changer.

00:02:09: Because the objective, it's fundamentally shifted.

00:02:12: The core difference isn't about getting a click anymore.

00:02:14: It's about earning a citation, getting mentioned within the AI's answer.

00:02:19: Rob Wynn pointed this out recently, that these AI assistants are sort of quietly becoming the new gatekeepers.

00:02:26: They're deciding which brands you hear about first.

00:02:29: Sometimes even before you realize you're properly searching, you don't get the traffic directly, you get the credit, the mention.

00:02:35: Okay,

00:02:35: that sounds massive.

00:02:37: But let's try and quantify the stakes here.

00:02:38: Andrew Yan shared some pretty potent insights, didn't he?

00:02:41: He did.

00:02:42: Predicting that traditional search volume could drop.

00:02:44: get this.

00:02:45: It's a fifty percent.

00:02:46: Fifty percent.

00:02:47: Wow.

00:02:47: By twenty twenty eight.

00:02:49: Replaced by traffic coming entirely from AI answers and you know synthetic content.

00:02:54: Okay

00:02:54: just think about the practical implications of a fifty percent drop.

00:02:57: That's that's not a slow decline.

00:02:59: No it's a cliff.

00:03:00: That's a budget emergency.

00:03:01: A personnel emergency potentially.

00:03:04: If your whole content strategy relies on organic clicks from traditional search.

00:03:09: You

00:03:09: could become invisible.

00:03:10: Yeah, digitally invisible within what, five years?

00:03:12: None.

00:03:13: So that means B to B. brands really need to start treating these generative engines as like primary distribution channels.

00:03:19: Absolutely, right now.

00:03:21: not just some little downstream amplification tactic.

00:03:23: So, okay, if the mechanism is citation, not click through rate, what specific tactical changes do B to B content teams need to make, like, today?

00:03:32: Well, it really boils down to structuring your content for machine consumption first, and maybe human consumption second.

00:03:39: It sounds a bit weird, but Lee Matthews really hammered this point home.

00:03:42: Okay.

00:03:42: The new mandate is structuring content so precisely, so verifiably, that AI models don't just find you, they actively trust you recommend you and cite you as the authority on a topic.

00:03:53: So less narrative, more structure.

00:03:55: Exactly.

00:03:56: It probably means moving away from those long verbose kind of monolithic blog posts towards, you know, highly structured, maybe semantic Q&A formats.

00:04:04: Things that feed the models.

00:04:05: clean, direct answers.

00:04:06: That makes a lot of sense.

00:04:07: And the market's clearly reacting to this urgency, right?

00:04:10: We're already seeing tools pop up specifically for this.

00:04:13: Yeah.

00:04:13: Ryan McKenzie detailed the launch of Meridian's new GEO offering.

00:04:17: That's right.

00:04:18: Designed to automate tracking brand visibility across these generative platforms.

00:04:23: It goes beyond just checking keywords, doesn't it?

00:04:25: It does.

00:04:26: Meridian's tool, as I understand it, monitors the brand mentions, gives you a visibility score, and this is the crucial bit, gives you real-time actionable steps.

00:04:35: Excepts you can actually take to win those recommendations.

00:04:39: So it's not just tracking, it's prescriptive strategy.

00:04:41: Right.

00:04:42: Prescriptive.

00:04:43: And this rapid shift, it must create a real first mover advantage, especially for smaller teams, maybe.

00:04:49: Oh, absolutely.

00:04:50: I'm afraid he noted this too.

00:04:51: It's kind of a rare window where, you know, early adopters, even sharp solo consultants, they genuinely have a chance to outperform the bigger, maybe slower incumbents.

00:05:01: The ones still trying to force fit old SEO rules onto this new generative system.

00:05:06: It's like you're racing to get cited first to build that trust layer before everyone else catches on.

00:05:12: Okay, so that visibility piece, that imperative, it sets the stage perfectly for the next big shift we're seeing,

00:05:19: execution.

00:05:20: If AI agents are going to consume all that nicely structured content, we need to understand how they're actually doing the work.

00:05:28: Agenic AI, it seems to be moving rapidly from just being slideware.

00:05:31: Yeah,

00:05:31: slideware, exactly.

00:05:32: To having real revenue use cases.

00:05:34: Audrey DeSisto summarized it.

00:05:36: Well, these AI agents are essentially starting to replace entire apps and fundamentally reshaping that B to B discovery process.

00:05:43: Okay, but here's the question I keep hearing.

00:05:45: Isn't this just... another buzzword, sophisticated automation.

00:05:49: I mean, we've had workflow automation for years.

00:05:52: What makes agentic AI different?

00:05:54: That's the critical distinction, isn't it?

00:05:56: It's really about orchestration, not just linear automation.

00:05:58: Nishant Gupta framed it really well.

00:06:00: I thought he called it the bridge between imagination and intelligence.

00:06:04: Standard automation just executes a predefined sequence, you know, A, then B, then C. An agent, though.

00:06:12: It holds a goal in mind.

00:06:13: It performs internal reasoning, it learns from its mistakes, and it autonomously figures out complex, multi-step actions to reach that

00:06:21: goal.

00:06:21: So it acts with intent.

00:06:23: Exactly.

00:06:23: Intent.

00:06:24: And we're seeing some... Pretty undeniable results from that autonomy already.

00:06:28: Homie Delias-Crimani shared this fantastic plot twist moment.

00:06:31: Oh yeah.

00:06:32: Yeah, they basically admitted they realized almost by accident that their AI agents had generated actual tangible leads

00:06:39: for over

00:06:40: a hundred clients.

00:06:41: Wow.

00:06:42: The agents were working so seamlessly in the background they were almost invisible.

00:06:46: They actually had to revamp their sales decks just to finally make the agents the heroes of the story.

00:06:51: Huh,

00:06:52: that's brilliant.

00:06:52: The engine itself became the differentiator.

00:06:54: Exactly.

00:06:55: But you know, when you hear stories like that, these complex successes, it's easy for B to B marketers listening to feel like, oh god, I need to build an entire bespoke AI system overnight.

00:07:04: And it can feel overwhelming.

00:07:06: But

00:07:06: Oren Greenberg provided a really great kind of grounding framework for scaling this execution piece.

00:07:12: He advises starting small.

00:07:14: Level one.

00:07:15: Level

00:07:15: one.

00:07:15: Okay.

00:07:16: Simple chat driven agents connected directly to your existing CRM or maybe internal databases.

00:07:22: So the quick wins.

00:07:23: Exactly.

00:07:24: That's where you get immediate value things like pulling lead data faster or simple internal reporting.

00:07:29: And his warning is probably even more critical.

00:07:32: Resist that temptation to jump straight to level three or four.

00:07:35: The complex stuff.

00:07:36: Yeah.

00:07:36: The proprietary custom built apps.

00:07:39: Building those really complex costly solutions before you've even validated the need at level one or two.

00:07:46: That's just the fastest way to burn through your budget on infrastructure, solving maybe theoretical problems.

00:07:51: Validate first and scale.

00:07:53: Makes sense.

00:07:53: And this shift towards these intent-driven agents, it's also driving specialization, isn't it?

00:07:58: We're moving way beyond just generic chatbots.

00:08:00: Definitely.

00:08:01: Rachel Roundy described creating these incredibly powerful persona agents at Intel.

00:08:06: Persona agents, tell me about those.

00:08:08: Yeah, so these were custom GPTs, but loaded with really dense specific buyer insights, pain points, competitive Intel objections.

00:08:18: Okay.

00:08:19: And they used them internally to basically role play objections and pressure test marketing messages before they even went out the door.

00:08:27: Ah,

00:08:27: so like an internal sparring partner.

00:08:29: Exactly.

00:08:30: You train the sophisticated AI agent to be your absolute toughest critic.

00:08:35: It drastically derisks your messaging before you spend millions on a campaign.

00:08:39: That's smart.

00:08:40: And this whole agentic mindset, it's now shaping how new platforms are being built from the ground up too.

00:08:45: Tammy H. Nam announced the brief.

00:08:47: Right, the campaign management product.

00:08:49: Yeah, it debuted positioning itself not just as another tool, but as an agentic AI control center.

00:08:56: The goal is to transform that whole campaign lifecycle into one connected flow that learns and adapts in real time.

00:09:02: So moving the marketer from just siloed insights?

00:09:04: A continuous

00:09:05: learning impact without dropping the context between steps.

00:09:08: That's the idea.

00:09:09: OK, so if AI is handling more of the execution, writing briefs, tracking GEO visibility, even generating leads, what's left for the human marketer?

00:09:19: What skills should we be hiring?

00:09:21: for next year.

00:09:21: That's the million-dollar question, isn't it?

00:09:23: Arorial Hans made a really strong case that human creativity that remains the ultimate differentiator, it's what's needed to elevate content above that baseline stuff that AI generates so quickly and predictably.

00:09:36: And I think Daniel Chifty really synthesized this whole debate quite nicely.

00:09:40: He argued that, look, Jini AI hasn't really elevated originality much at all.

00:09:45: What it has done is drastically lower the floor for execution speed.

00:09:50: anyone can produce passable content at machine speed now.

00:09:53: Right.

00:09:53: Table stakes.

00:09:54: Exactly.

00:09:55: But if everyone's using the same models, well, everyone starts getting predictable kind of average results.

00:09:59: So this means judgment, taste, ethical decision making, high level strategy.

00:10:04: Yeah.

00:10:04: That's the real differentiator now.

00:10:06: That's where the value creation happens.

00:10:07: Which basically rewrites the job description, doesn't it?

00:10:11: Especially for leadership.

00:10:13: Carolyn Healy detailed, I think it was thirteen critical shifts for CMOs navigating this.

00:10:18: Thirteen.

00:10:18: Two really stood out to me.

00:10:20: First, moving from static personas to really dynamic micro segments based on continuous AI analysis.

00:10:27: Okay.

00:10:28: And second, this bold mandate to actively shift twenty percent one-fifth.

00:10:33: of the marketing budget, specifically to AI identified opportunities.

00:10:37: That's a direct instruction to trust the machine's insights.

00:10:40: Wow, twenty percent.

00:10:41: That's significant.

00:10:42: And it ties into why Zubin Kutar believes the future AI marketer really needs more of a product manager mindset.

00:10:48: Product

00:10:48: manager.

00:10:49: Interesting.

00:10:50: How so?

00:10:50: Less just being a campaign pusher, you know.

00:10:52: Yeah.

00:10:53: More about being scientifically rigorous.

00:10:55: Focus first on defining the precise problem you're solving.

00:10:57: then test solutions rigorously.

00:10:59: Use holdouts, measure tangible business outcome.

00:11:02: Like incremental

00:11:03: revenue.

00:11:03: Exactly.

00:11:04: Incremental revenue, not just relying on vanity metrics or, you know, how much stuff you produced.

00:11:07: Of

00:11:08: course the pushback always comes down to ROI, right?

00:11:10: Does this AI stuff actually save money?

00:11:12: Does it drive revenue?

00:11:13: But we do have some hard numbers now proving the value when these strategies are really executed at scale.

00:11:20: Girish J. Kulra shared Tata AIA life insurance's incredible milestone.

00:11:25: Yeah, that was impressive.

00:11:26: They surpassed ten thousand marketing use cases with Gen AI and reported a massive thirty percent reduction in creative development cost.

00:11:34: Thirty percent?

00:11:35: Plus a turnaround time shift from days down to just hours.

00:11:39: I mean a thirty percent creative cost reduction in a large enterprise.

00:11:43: That's a tectonic shift.

00:11:44: And then you pair that with what Shrikant Shraddari demonstrated.

00:11:47: Right.

00:11:47: The near zero marginal cost content.

00:11:50: Yeah.

00:11:50: That campaign quality video and written content can now be produced at almost zero marginal cost.

00:11:56: That's a huge democratization of content production.

00:11:58: The financial barrier to entry for high quality stuff is just collapsing.

00:12:01: However, it's not all smooth sailing, is it?

00:12:04: There are some serious hurdles people are hitting.

00:12:06: Definitely not.

00:12:07: Rose Keen's research highlighted this really stark vision to reality gap across the industry.

00:12:12: Vision

00:12:12: to reality gap.

00:12:13: Yeah.

00:12:14: A staggering ninety six percent of marketers reported a significant disconnect between their gene AI ambitions and what they're actually managing to do in practice.

00:12:23: Ninety six percent.

00:12:24: That's almost everyone.

00:12:26: Why?

00:12:26: What's the disconnect?

00:12:27: Well, that huge gap is usually put down to inadequate training, skills gaps and just plain old organizational friction.

00:12:35: The tools are here.

00:12:37: or they're arriving fast, but the human processes, the skills, they haven't caught up yet.

00:12:42: And this just reinforces what Rachel Roundy was stressing earlier.

00:12:45: The Intel example.

00:12:46: Yeah, proving that critical ROI at scale, it absolutely requires connected workflows and some serious upskilling efforts.

00:12:53: Otherwise, these powerful tools just end up as expensive, isolated experiments.

00:12:56: Instead of being integrated revenue drivers.

00:12:58: Got it.

00:12:59: Exactly.

00:12:59: Hashtag tag outro.

00:13:01: Okay, so we've covered a lot.

00:13:02: The visibility imperative of GEO, the need to build these intent-driven, agentic workflows, and that massive shift in talent strategy required to actually lead in this new landscape.

00:13:11: We are, I think, firmly in an era where the speed of production is just way up right across the board.

00:13:17: Unquestionably.

00:13:18: But

00:13:18: quality... critical judgment, strategic originality, those are rapidly becoming the new bottlenecks.

00:13:25: It really is about building systems now that can think, adapt, and reliably deliver genuine business outcomes, not just, you know, more noise faster.

00:13:33: So the question we really want to leave you with as you plan your strategy for the coming quarters is this.

00:13:38: Are you using AI just to do the same work maybe forty percent faster?

00:13:43: or are you strategically leveraging it to achieve a level of originality and strategic depth that your competitors simply can't copy?

00:13:50: That's the real question.

00:13:51: Because that's the difference between just maintenance and true market leadership.

00:13:55: We certainly hope this deep dive into the focused insights from calendar weeks, thirty nine and forty, gives you the clarity you need to make those crucial platform and strategy bets right now.

00:14:05: If you enjoyed this deep dive, new additions drop every two weeks.

00:14:09: Also check out our other additions on account-based marketing, field marketing, channel marketing, MarTech, go-to-market, and social selling.

00:14:16: Thank you for listening and we'll catch you next time.