Best of LinkedIn: AI in B2B Marketing CW 45/ 46

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

00:00:10: Frenes 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.

00:00:21: Customer needs analysis and buying center insights.

00:00:25: Welcome back to the deep dive.

00:00:27: looking at our source material for this analysis.

00:00:30: curated from the top BDB mines on LinkedIn these last few weeks.

00:00:33: It feels like something really crucial is happening with AI.

00:00:36: It does.

00:00:36: We're definitely past that initial, hey, look what chat GPT can do phase.

00:00:39: Right, the novelty is wearing off.

00:00:41: Exactly.

00:00:41: So our mission today is really to cut through all that noise around generative AI and pinpoint where B to B leaders are actually seeing measurable business outcomes.

00:00:51: We're seeing this major shift from just isolated experiments to building real, repeatable, go-to-market systems.

00:00:57: So we're going to get into where AI is actually delivering revenue where it's friendly falling flat and what you need to be doing right now with your data and your culture to even stay in the game.

00:01:05: Let's jump in.

00:01:06: Okay, so let's start at the top at the strategy level.

00:01:08: The whole conversation has shifted.

00:01:10: It's no longer about AI as just another tool.

00:01:13: The

00:01:13: bigger than that.

00:01:14: Much bigger.

00:01:14: We saw a lot of posts framing AI as, well, the new operating system for how you build a company marketing sales everything by twenty twenty six.

00:01:24: This isn't just a tweak.

00:01:26: It's a complete architectural overhaul of GTM.

00:01:29: And we have some pretty compelling proof that this isn't just theory anymore.

00:01:33: It's actually producing massive results.

00:01:36: Ayman Buzade shared this incredible case study.

00:01:38: Oh,

00:01:38: the one with the AI agents?

00:01:39: Yes.

00:01:40: A GTM team used over thirty five custom AI agents and the results were, I mean, seven million dollars in pipeline and half a million in closed revenue.

00:01:49: in just six months.

00:01:50: That's

00:01:50: a production level number, not some little pilot project.

00:01:53: It really validates the potential.

00:01:54: And when you look at how they did it, Amon explained, these agents handled something like forty to fifty of the most repetitive BDR tasks.

00:02:02: And with human level quality.

00:02:04: Exactly.

00:02:04: So this isn't about, you know, generic email blasts.

00:02:07: We're talking automation.

00:02:08: that's handling list filtering, spotting intent signals in real time, and doing hyper-personalization based on fresh news.

00:02:16: And that speed of follow-up.

00:02:18: That's something a human team just can't sustain.

00:02:20: Impossible.

00:02:21: But here is the massive, massive caveat.

00:02:24: And we saw this stressed by people like Michael Lovegrove and Shira Guderman remote.

00:02:29: AI is an accelerator.

00:02:31: It will either accelerate your success or it's going to amplify your existing operational chaos.

00:02:35: It all depends on the quality of your foundation.

00:02:37: And especially your data.

00:02:39: Above all else, your data.

00:02:40: If you have a messy CRM, AI is just going to personalize garbage faster.

00:02:43: So the advice isn't go build thirty five agents.

00:02:46: No, absolutely not.

00:02:47: The unified advice was start simple, pick one, single pain point, test one low friction use case and measure one metric.

00:02:55: That's it.

00:02:55: Get that right before you

00:02:56: scale.

00:02:57: It seems the ones who get that foundation right are already pulling away from the pack.

00:03:01: Kieran Flanigan pointed out that AI mature marketers are seeing about sixty percent higher revenue growth.

00:03:06: Sixty percent.

00:03:07: That's a huge gap.

00:03:09: And he said they do it by combining three things.

00:03:11: Creator-led content, something called AI Engine Optimization, or AEO, and AI-driven prospecting.

00:03:18: It's a real competitive advantage.

00:03:19: It is.

00:03:20: And that demands a mindset shift.

00:03:22: Scott Brinker had a great post about this.

00:03:23: He warned that just using AI for efficiency gains, you know, doing the same work twenty percent faster, that's being commoditized.

00:03:30: So the advantage isn't saving a bit of time on writing content.

00:03:33: Nope.

00:03:34: Brinker calls it the abundance mindset.

00:03:37: The real advantage comes from pursuing transformation.

00:03:40: Don't just save money.

00:03:41: Think about how you can achieve a tenfold expansion of your target segments or run ten times the campaigns.

00:03:47: That's where the long-term value is.

00:03:49: Okay, let's move from strategy down to the sales floor.

00:03:52: There's this one topic that seems to ignite more debate than anything else right now.

00:03:56: I think I know where you're going with this.

00:03:57: The AISDR.

00:03:59: The AISDR.

00:04:00: Yes.

00:04:00: Sam Jacobs highlighted the appeal, and it's so compelling, right?

00:04:04: They're cheaper, follow-up is instant, and meeting conversion rates can jump from, say, fifteen percent to over twenty-five.

00:04:10: That's just pure velocity.

00:04:12: That conversion jump is a huge incentive.

00:04:14: But then you have to look the other side at the heavy skepticism.

00:04:18: Marie Robert, for instance, pretty much called the AISDR pitch a scam for qualification.

00:04:23: A scam?

00:04:24: Why?

00:04:24: She had a client who spent two thousand dollars a month on an agent that booked zero qualified demos.

00:04:31: Zero.

00:04:32: Because the AI just fails at the complex stuff.

00:04:35: The moment a prospect goes off script or asks a nuanced question, it just spits out a generic, awkward response.

00:04:41: It fails the sniff test, as she put it.

00:04:44: It does.

00:04:44: If you automate a bad conversation, you just fail faster.

00:04:48: And yet... Scott Findon, she had some fascinating counter-evidence.

00:04:51: Oh, right, the live call.

00:04:52: Yeah, he listened to a live AISDR call and said it outperformed seventy-five percent of the humans he's heard.

00:04:58: It wasn't robotic at all.

00:05:00: It showed empathy.

00:05:01: It asked for context.

00:05:02: It dug beneath the surface to build real interests.

00:05:04: There's

00:05:04: a gap between the bad tools and the good ones is just astronomical.

00:05:08: It is, which explains all the confusion.

00:05:10: But the consensus we're seeing for twenty-twenty-five from people like Yuri Varemchuk and Margot Malarm, it's all pointing to a hybrid formula.

00:05:18: machine partnership.

00:05:19: Exactly!

00:05:20: Let the AI crush the grout work, the research, lead validation, first drafts, the instant follow-up, and that frees up the human SDR to do what they do best.

00:05:30: Build trust, navigate complex buying committees, and handle those tricky conversations.

00:05:35: And setting up those workflows is getting easier.

00:05:38: Chase Diamond showed how he built a whole outbound campaign in just ten minutes using Apollo's AI assistant.

00:05:44: Ten minutes.

00:05:45: That's a game changer.

00:05:46: Now, there was another really crucial point here about prioritization.

00:05:49: Laura Baranavich argued that the biggest immediate revenue impact from AI might not even be an outbound.

00:05:55: Oh.

00:05:56: Where then?

00:05:57: In customer success.

00:05:58: Her point is we should be using AI to monitor expansion signals funding rounds, leadership changes for our CSMs.

00:06:04: That's

00:06:04: a fantastic insight.

00:06:05: CSMs are close to the revenue, but they're often not trained to spot those proactive sales opportunities.

00:06:10: Right.

00:06:11: AI gives them.

00:06:11: the intelligence, CSM provides the human context, and suddenly customer success becomes a powerful proactive revenue driver.

00:06:18: Okay, so that brings us to marketing content and this idea of a visibility crisis.

00:06:23: It really is a crisis.

00:06:25: Thomas Ross had this direct, pretty urgent warning for CMOs.

00:06:29: By twenty twenty-six, the AI engines, chat GPT, Gemini, Proplexity, they will be the ones who decide who gets discovered and trusted.

00:06:37: So if you're not building a strategy for AI engine optimization or AEO right now, you're

00:06:42: actively choosing to become invisible.

00:06:44: It's that simple.

00:06:45: And we need to be clear.

00:06:47: AEO is not the same as SEO.

00:06:49: Right.

00:06:50: SEO is about ranking on a search results page.

00:06:52: AEO is different.

00:06:53: It's about being optimized for citation and summarization inside the LLMs.

00:06:58: You want your brand to be the authoritative source the AI uses to answer a query directly.

00:07:03: They might not even click through to your site.

00:07:05: And we saw proof that you can get results here fast.

00:07:07: David Zelliden shared that his team got the number one Google ranking for a term like AI GTMB to be in under forty eight hours.

00:07:14: Forty

00:07:14: eight hours.

00:07:15: No long link building campaigns.

00:07:17: Just pure focus on user intent, page architecture and technical hygiene.

00:07:21: It proves.

00:07:22: which brings us to content strategy in this new

00:07:24: world.

00:07:25: Yeah, Michael Steele gave us a really useful framework for this.

00:07:27: He talks about AI push and AI pull.

00:07:30: Okay, break that down for

00:07:31: us.

00:07:31: AI push is using AI to augment your content production drafting, localizing, just getting more velocity.

00:07:40: AI pull is the strategic work you do to make sure your digital presence is so authoritative that the LLMs pull your content in as the source of truth for their answers.

00:07:49: You need to do both.

00:07:50: You feed the machine, but you also have to be the machine's most trusted source.

00:07:54: Exactly.

00:07:55: And if AI is generating so much of this push content, the need for human differentiation just becomes paramount.

00:08:02: Vasalina Valchinova wrote about something she calls monument marketing.

00:08:06: I like this idea.

00:08:07: It's great, right?

00:08:08: Creating content and experiences that simply cannot be automated away.

00:08:12: Deep original points of view, proprietary data.

00:08:15: If an LLM can create a copy of your content in five minutes, it is not a monument.

00:08:18: So the strategy is... create something truly unique, then use AI to distribute that idea everywhere.

00:08:25: That's the play.

00:08:26: And just quickly, on a global note, Hima Day pointed out that with the weaker US dollar, it's become much more cost effective for international companies in Europe, Letam, and Australia to access US-based AI marketing tech and expertise.

00:08:39: So this adoption curve is accelerating globally.

00:08:43: All these changes are obviously rewriting job descriptions.

00:08:46: Sander Avik pointed out that some companies are already redefining the SDR role into what they call a GTM engineer.

00:08:53: And this is a huge distinction.

00:08:54: A GTM engineer isn't just sending emails.

00:08:57: They're on the front lines, but they're also building and running their own automation systems and data workflows.

00:09:03: They're part seller, part analyst.

00:09:04: Tyler John added to that, saying, the next GTMA leaders are probably sitting on your sales floor right now building their own workflows.

00:09:11: You have to find those people and elevate them fast.

00:09:13: It speaks directly to Oren Greenberg's analysis of which skills are at risk.

00:09:17: Right.

00:09:17: Anything repetitive and procedural is on the chopping block.

00:09:20: The skills that are soaring in value are strategic.

00:09:22: judgment, critical thinking, and real domain expertise.

00:09:26: And we're seeing this play out in hiring.

00:09:29: Jessica Aries observed that law firms, for example, aren't downsizing their marketing teams, but they are, hesitating to backfill junior coordinator roles.

00:09:38: They're just assuming AI can absorb that entry-level work.

00:09:42: That's a fundamental change.

00:09:43: Those entry-level jobs used to be the training ground.

00:09:46: Which brings up the culture piece.

00:09:48: If everyone has the same tools and the same data, what's the differentiator?

00:09:52: Michael Ocean cited Kelly Wright from Tableau and Gong

00:09:55: on this.

00:09:56: And she says the ultimate competitive advantage is culture.

00:09:59: A team that trusts each other will always outperform a team with the same tech stack.

00:10:04: Which is a real challenge.

00:10:05: As Josh Braun pointed out, he just said, humans won't change.

00:10:08: Right.

00:10:08: People need trust and autonomy.

00:10:10: But if you're building systems that replace the junior staff, how do you build that trust?

00:10:14: It's a huge strategic tension.

00:10:16: Let's talk practical application and tools.

00:10:18: We saw a great example from Luke Shalom about running a lean stack.

00:10:21: His business does a hundred K a month while spending only fifteen hundred on tools.

00:10:25: It proves you don't need a massive budget.

00:10:28: He's relying heavily on things like chat GPT Atlas for competitor audits and building prospect lists.

00:10:34: Bethany Staschenfeld also showed how those tools are automating things like LinkedIn requests.

00:10:39: But we do need to be realistic about fully autonomous agents.

00:10:42: Ryan Staley made a strong argument that twenty twenty five is not the year of the AI agent.

00:10:47: Yeah, his point is that most agents are just fancy chatbots with massive integration problems.

00:10:53: For today, his advice is to focus on task specific automation and co-pilots that help humans.

00:11:00: The true multi-step autonomous stuff is still a little ways off.

00:11:03: And the cost of getting that wrong can be huge.

00:11:06: Carolyn Healy was very candid about a two hundred fifty thousand dollar mistake.

00:11:10: A painful lesson.

00:11:11: She said they went all in on an AI solution without really understanding their customers' needs.

00:11:16: Her takeaway was that complexity kills adoption, and innovation without insight is just gambling.

00:11:20: That speed of innovation also demands a new kind of business agility.

00:11:24: Brad Pitts recommended only using monthly billing for AI tools.

00:11:28: It makes so much sense.

00:11:29: Why lock into an annual license when a better, cheaper tool could launch in thirty days?

00:11:35: You need to be able to swap out your stack

00:11:36: fast.

00:11:37: And finally, let's touch on the human learning curve.

00:11:40: Liza Adams said the biggest gap for marketers isn't technical skill.

00:11:45: It's the mental model.

00:11:46: People are struggling to think beyond their own individual productivity and start orchestrating different GPTs together to improve a whole workflow.

00:11:54: Orchestration, not just output, that is the key distinction.

00:11:57: John Miller built on this perfectly.

00:12:00: He urged a shift from simple prompt engineering to what he calls context

00:12:04: engineer.

00:12:04: So not just asking a better question.

00:12:06: No, it's about giving the AI, he calls it the tactician.

00:12:10: All the business context, the goals, the behavioral data it needs to then sequence the right touches for an entire buying group.

00:12:17: The human's most valuable input is now that strategic context.

00:12:21: You know, this whole deep dive really highlights a central tension.

00:12:24: The incredible acceleration we're getting from AI actually demands a stronger, clearer human element than ever before.

00:12:31: In culture, in strategy, in context, the machine handles the production, the human has to handle the insight.

00:12:38: If you enjoyed this episode, new episodes drop every two weeks.

00:12:41: Also, check out our other editions on account-based marketing, field marketing, channel marketing, mar-tech, go-to-market, and social selling.

00:12:48: Thanks for joining us.

00:12:49: So here's a final thought for you.

00:12:51: Given the incredible speed of AI development, if you had to place a bet, which do you think will improve faster?

00:12:57: The AI tools themselves or our human ability to create the strategic context, those tools need to actually drive revenue.

00:13:05: Make

00:13:05: sure to subscribe so you don't miss our next deep dive.