Best of LinkedIn: AI in B2B Marketing CW 49/ 50

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, forty nine and fifty.

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.

00:00:23: Welcome back to the deep dive.

00:00:24: You've given us a fantastic stack of recent expert material from LinkedIn and our mission today is to, well, to cut through all that noise.

00:00:32: Yeah,

00:00:32: there's a lot of it.

00:00:33: There is.

00:00:34: We're synthesizing what we think are the most critical strategic shifts happening in AI and BB marketing right now, really focusing on what leaders are actually doing, not just what they're theorizing about.

00:00:45: And that's

00:00:46: the key distinction, isn't it?

00:00:47: We saw it across those two weeks.

00:00:48: We are, I think, definitively moving past the generic AI hype.

00:00:52: Finally.

00:00:53: Yeah, finally.

00:00:53: And we're moving straight into concrete operating models.

00:00:56: The whole conversation has matured from, what if AI could replace X to something more like, how do we wire AI into our GTM system to compound value?

00:01:05: and those areas where value compounds are very specific.

00:01:09: We're talking about data foundations, how we orchestrate outbound, redesigning the go-to-market architecture itself, and maybe most urgently, figuring out brand visibility in this new generative search world.

00:01:22: It's all about integration, not isolation.

00:01:25: Exactly.

00:01:25: And you see it in the new products and partnerships.

00:01:27: They just reinforce that AI has to be tightly connected to existing strategy and systems.

00:01:32: I mean, so many posts warned, if your underlying process is broken, AI just guarantees you fail faster.

00:01:37: And

00:01:38: louder.

00:01:38: And louder.

00:01:39: Definitely louder.

00:01:40: OK,

00:01:40: let's unpack this.

00:01:41: And I think we have to start with what was arguably the biggest flash point across all the channels.

00:01:45: AI.

00:01:46: SDRs and the whole outbound motion.

00:01:49: It feels like the SDR role is being completely redefined as we speak.

00:01:53: It is.

00:01:53: The initial hype cycle, that idea that AISDRs would just replace humans wholesale, that's completely finished.

00:01:59: Thank goodness.

00:02:00: The entire conversation is now focused on hybrid augmentation.

00:02:03: These systems are framed as force multipliers for teams that are already effective, not some kind of bandaid for a weak GTM model.

00:02:11: Okay, but here's where the data gets really interesting.

00:02:14: George Vitko shared evidence that AI-written emails can actually outperform human ones.

00:02:20: But there's a massive caveat, right?

00:02:22: A

00:02:22: huge one.

00:02:23: They only succeed when they follow specific, time-tested frameworks.

00:02:27: You know, things like relevance, a bit of humor, authority, and just perfect timing.

00:02:31: So the AI is just scaling better fundamentals.

00:02:34: It's not inventing them.

00:02:35: Exactly.

00:02:35: But this all rests on the quality of your data foundation.

00:02:38: I mean, Saad Khan delivered a major warning here, talking about the danger of building spam cannons.

00:02:44: I love that analogy.

00:02:45: Tell us more about this GTM Maslow's hierarchy of needs he described.

00:02:49: Okay, so he says AISDRs or, you know, fully autonomous DUTM, that's level five.

00:02:55: That's self-actualization.

00:02:56: The top of the pyramid.

00:02:57: Right at the top.

00:02:57: But level one, the absolute foundational need is identity, and that means clean, accurate CRM data.

00:03:03: Of course.

00:03:04: And if you skip that, if you're working with garbage data duplicates, old emails, whatever, the AISDR just confidently engages the wrong person with the wrong context.

00:03:13: It's automated confidence, but it's aimed squarely at failure.

00:03:17: And that's a costly mistake.

00:03:19: It doesn't matter how sophisticated your language model is, if it's emailing a duplicate contact who left the company six months ago.

00:03:26: It's just getting louder, not smarter, as Khan puts it.

00:03:30: And we saw this play out in the real world, too.

00:03:32: Amir Gausi mentioned Ramp actually shut down a very successful AI outbound program.

00:03:38: Which

00:03:38: is fascinating.

00:03:39: And why?

00:03:40: Because the returns just plateaued.

00:03:42: Once everybody in their industry was using the same tools on the same data, The edge was gone.

00:03:47: Automation becomes a commodity that fast.

00:03:49: Instantly.

00:03:50: When everyone sounds the same, nobody cuts through the noise.

00:03:53: So the strategic lesson there has to be.

00:03:56: Yeah.

00:03:56: What?

00:03:56: A hybrid approach?

00:03:57: It has to be.

00:03:58: Chris Ritzen summarized the winning model perfectly.

00:04:01: He said, AI handles the busy work.

00:04:03: You know, the list building, the CRM updates, the first follow-ups.

00:04:06: All grunt work.

00:04:07: Exactly.

00:04:08: And the human handles the relationship, the complex stuff, the negotiation, and that deeper personalization you need to build trust.

00:04:15: Speed plus trust equals more revenue.

00:04:17: That's

00:04:17: the formula.

00:04:18: If you try to fully automate the trust part, you are going to fail.

00:04:22: And David Meyer argued, You shouldn't even choose between AISDRs and in-house SDRs.

00:04:28: Right.

00:04:29: She says you design a fluid hybrid system.

00:04:31: And Scott Stringfellow even predicted the SDR role itself splits.

00:04:35: Splits into what?

00:04:36: Into tactical callers who focus on that high value human touch, like the cold calls and nurturing relationships, and GTM engineers who are the system builders.

00:04:46: They handle the data enrichment and targeting systems that feed the tactical callers.

00:04:51: That makes so much sense.

00:04:52: The GTM engineer.

00:04:54: builds the Ironman suit.

00:04:55: And the tactical collar is the highly skilled pilot inside it.

00:04:58: That's

00:04:58: a great way to put it.

00:04:59: And when you build that system right, the results are pretty hard to ignore.

00:05:03: Submit and share results from a pilot.

00:05:06: Six hundred dollars in pipeline in three weeks.

00:05:08: With zero human outreach.

00:05:09: Zero.

00:05:10: And they jump from a one point four percent reply rate to five point two percent.

00:05:14: And

00:05:14: that success was all about orchestration.

00:05:16: He talked about wiring together tools like clay, clear bit, and smart led.

00:05:20: It moves beyond simple automation.

00:05:23: The system is now acting with autonomy, making decisions in real time.

00:05:27: Which brings us directly to our next theme.

00:05:29: It

00:05:29: does.

00:05:29: The success summit saw wasn't just about better emails.

00:05:32: It was about the underlying system, the wiring.

00:05:35: And that leads us to theme two.

00:05:38: GTM strategy, and seeing AI as an operating system, not just another tool.

00:05:43: And

00:05:43: the core warning here, it came from leaders like Allon even, was that AI amplifies whatever GTM structure you already have.

00:05:51: For

00:05:51: better or for worse.

00:05:52: Exactly.

00:05:53: If your ideal customer profile is fuzzy or your positioning is weak, AI just makes those broken processes faster and frankly, more expensive.

00:06:02: Ali Qureshi noted this leads to AI panic.

00:06:05: not AI maturity.

00:06:06: Right.

00:06:06: So the message is still, master the fundamentals first.

00:06:09: So for leaders redesigning their systems, where is the most unexpected leverage?

00:06:13: Where are the big gains?

00:06:15: It's in unlocking what David Crager called previously uneconomic work.

00:06:19: He said the biggest gains aren't in replacing common tasks, but in enabling work that was just too expensive or tedious for humans before.

00:06:26: Okay, give me a concrete example of that.

00:06:27: Sure.

00:06:28: His example was having AI automatically review five hundred new leads a week just to filter out the bad fits before they ever hit in SDRSQ.

00:06:35: That single process saved eighty-three hours of manual work.

00:06:39: That level of meticulous, continuous filtering was just too slow and expensive for a human team to do consistently.

00:06:45: So it's high value, previously impossible work that the system now handles.

00:06:50: But for this AIOS to work, it has to be structured across the entire customer journey.

00:06:55: Absolutely.

00:06:56: Yannasek detailed the need to map AI across the entire bowtie model from awareness all the way through to expansion.

00:07:03: Pre-requisites

00:07:03: at each stage.

00:07:04: Exactly.

00:07:05: For the selection stage, for instance, you need things like AI note takers and call recordings to standardize discovery and flag risks.

00:07:12: It forces that structured integration.

00:07:14: And what

00:07:14: happens if you skip that?

00:07:16: Yeah.

00:07:16: Jerry Farr highlighted some really crucial failure

00:07:18: points.

00:07:19: Yeah, his list is essential.

00:07:20: First, treating AI as another damn tool.

00:07:23: He says it should be invisible to the rep, not another login.

00:07:25: Makes

00:07:25: sense.

00:07:26: Second, neglecting the behavior change required from the human team.

00:07:30: Third, Poor data hygiene, which is our old friend.

00:07:33: Garbage in, garbage out.

00:07:34: And the last one.

00:07:35: Missing GTM domain expertise among the people building the AI systems.

00:07:39: That's a huge risk.

00:07:40: If your system is built by engineers who don't deeply get sales cycles or customer pain points, you just end up with expensive automation theater.

00:07:49: A perfect transition to our third theme.

00:07:51: the expanding AI stack and platform convergence.

00:07:55: It feels like the real competition isn't over who has the best model, but who controls the integration layer.

00:08:00: It

00:08:01: definitely seems like the CRM is becoming that core AI engagement layer.

00:08:05: Absolutely.

00:08:06: Shashi Bellenponda pointed out that the Salesforce acquisition of Qualified validates this shift from conversational marketing to agentic marketing.

00:08:14: Agentic marketing.

00:08:15: I like that.

00:08:16: Yeah.

00:08:16: Qualified's AI, Piper.

00:08:18: It acts autonomously.

00:08:19: It engages visitors, books meetings instantly.

00:08:22: It's basically killing the passive contactless form.

00:08:25: And HubSpot is moving in the same direction.

00:08:27: Juliana Garcia highlighted their new Run Agent Workflow Actions feature.

00:08:32: Built right into workflows.

00:08:33: That's key.

00:08:34: It lets the agent can rich leads, qualify them, and personalize emails automatically without eating a bunch of third-party hacks.

00:08:40: And this move towards agents is about more than just content, right?

00:08:45: Ilya Azubsev.

00:08:46: detailed using Claude's model context protocols, or MCPs, to make AI operate tools.

00:08:52: Right, we're talking about AI actually querying HubSpot, building NAN automation flows, prioritizing LinkedIn follow-ups.

00:08:59: So the AI isn't just generating texts anymore, it's becoming the operational executor.

00:09:04: Which means the marketer's job is fundamentally shifting.

00:09:07: Kieran Flanagan said the winning marketers are building a personal army of apps with models like Opus and Gemini.

00:09:13: They're turning their domain expertise into a software advantage.

00:09:16: An advantage that competitors can't just copy.

00:09:19: Exactly.

00:09:20: And that's why Philip Alexa stressed the need for durable AI skills focused on workflows, not just one-off prompt tricks.

00:09:25: It's that marriage of proprietary knowledge and personalized software that creates a massive competitive mode.

00:09:31: Okay, let's finish with our last theme, which honestly had the most shocking numbers.

00:09:35: A truly seismic shift.

00:09:37: AI era SEO or AEO.

00:09:39: This is huge and it impacts every single marketer creating content.

00:09:45: Tom Jacobs takeaways from the GEO conference, they show that visibility in AI answers is now just as critical as old school search rankings.

00:09:54: The numbers really do flip the whole playbook on its head.

00:09:56: They

00:09:57: do.

00:09:57: It's just sit with us for a second.

00:09:59: Tom Jacobs stated that only one percent of users click the links inside an AI answer.

00:10:04: One percent.

00:10:05: Just think about the gravity of that.

00:10:07: If your brand gets cited, ninety nine out of a hundred people don't even visit your site.

00:10:11: They just trust the summary.

00:10:13: So driving traffic via traditional links is becoming almost secondary to just making sure your brand narrative is present and model ready.

00:10:20: And it gets even worse for traditional SEO.

00:10:22: Brand websites account for less than ten percent of AI citations.

00:10:26: Ninety percent come from third party sources.

00:10:28: News articles, LinkedIn posts,

00:10:30: reviews.

00:10:31: Exactly.

00:10:32: So if your brand only exists on your own website, you are effective.

00:10:35: invisible to these models.

00:10:45: So

00:10:51: the measurement changes completely.

00:10:52: We're moving away from optimizing for keyword rankings, which was the foundation of SEO for

00:10:59: And we're moving toward optimizing for brand mentions and share of voice within the generated answers themselves.

00:11:05: That's AEO, AI search optimization.

00:11:08: Which raises a really important question that a lot of posts were debating.

00:11:12: If these agents become so powerful, what's left as the human differentiator?

00:11:16: Melissa Wildstein summarized it perfectly.

00:11:19: She said, power without judgment is just risk.

00:11:23: Even with these powerful agents handling the operational work, humans still have to define the intent, set the direction, and decide what good even looks like.

00:11:31: So the future is AI handling the scale.

00:11:33: But human judgment, ensuring it's used ethically, that it's aligned with strategy, and most importantly, that it builds trust.

00:11:40: It's about building systems where AI accelerates scale.

00:11:43: But human guidance keeps the entire GTM function focused on building real conviction and trust in those high stakes B to B relationships.

00:11:50: That was a tremendous deep dive.

00:11:52: The core takeaway seems undeniable.

00:11:54: AI is not a magic fix.

00:11:56: It's an amplifier.

00:11:57: That's the word?

00:11:58: You have to prioritize clean data in a clear integrated GTM strategy first.

00:12:03: Only then should you invest in this human AI operating system.

00:12:07: If you try to scale broken processes or use garbage data, AI won't just fail.

00:12:11: It will amplify those bad outcomes and fast.

00:12:14: If you enjoyed this deep dive, new episodes drop every two weeks.

00:12:18: We cover everything from account based marketing, field marketing, channel marketing, mark tech, go to market and social selling.

00:12:24: Thank you for joining us for this deep dive into AI and B to B marketing.

00:12:27: And here's a final provocative thought for you to mull over as you start designing your new GTM system.

00:12:33: If AI is making the coal transactional side of B to be easier and faster to automate, does that mean the next great competitive advantage will be the human salesperson's ability to demonstrate genuine empathy and build conviction in high-stakes deals?

00:12:46: Remember to subscribe.