Best of LinkedIn: AI in B2B Marketing CW 43/ 44

00:00:00: This deep dive is provided by Thomas Allgeier and Frennis, based on the most relevant LinkedIn posts about AI and B to B marketing in calendar weeks, forty-three and forty-four.

00:00:10: 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 analyses and buying sender insights.

00:00:24: Welcome back, everyone.

00:00:25: So our mission today really is to sift through all that LinkedIn chatter.

00:00:28: We want to pull out what B to B GTM leaders were actually doing and talking about with AI in late October, early November.

00:00:36: Right.

00:00:36: We're looking past the hype, past the sort of theoretical stuff.

00:00:39: Exactly.

00:00:39: We're focused on the practical blueprints people are sharing.

00:00:42: And looking across those couple of weeks, the conversation definitely shifted.

00:00:45: It's not really, should we use AI anymore?

00:00:48: It's more like, OK, we are using it.

00:00:50: How do we govern it properly?

00:00:52: Success seems to hinge much more on system design, orchestration, and putting the right guardrails in place.

00:00:58: That's really the heart of it.

00:01:00: And probably the most heated area of discussion was right at the sharp end, sales and SDR automation.

00:01:05: Makes sense.

00:01:05: That's where the systems seem most developed, but maybe where the risks are highest too.

00:01:09: Precisely.

00:01:10: So let's unpack that first theme, the shift in sales and SDR automation.

00:01:15: Okay.

00:01:15: And the big takeaway seems to be, it's not about replacing SDRs, it's about multiplying their impact, kind of redefining the role.

00:01:23: Exactly.

00:01:24: It's shifting from just raw activity volume to, well, intelligence orchestration.

00:01:30: And the detail people are sharing now is pretty incredible.

00:01:32: Oh yeah, like what?

00:01:34: Well, Priyanka S, for instance, she laid out this whole AI SDR blueprint.

00:01:38: It automates lead gen across the lake.

00:01:41: LinkedIn, email, acts, even voice calls.

00:01:43: Wow, okay.

00:01:44: The whole workflow.

00:01:45: Yeah, finding leads with Google search, enriching the data, using GPT to qualify them against the ideal customer profile of the ICP, and then generating personalized messages.

00:01:54: It's quite a system.

00:01:55: And that usually involves stringing together different tools, right?

00:01:57: Like using things like NADN for workflow automation, maybe LGM for sales in GTM for the engagement part.

00:02:04: That's the key, the connectivity.

00:02:06: It's less about one magic tool.

00:02:08: and more about how they work together.

00:02:09: Got it.

00:02:10: And it's about intelligence payoff.

00:02:13: Jan Benedict Mundorf mentioned closing sixty deals in twenty twenty-five partly thanks to AI.

00:02:19: But he really stressed, you know, treat AI as a multiplier, not a shortcut.

00:02:24: So how's he using it?

00:02:25: Things like generating meeting recaps, summarizing pain points, timeline, next steps in like ninety seconds.

00:02:31: Okay,

00:02:31: that's useful.

00:02:32: But also strategically.

00:02:34: Like.

00:02:34: Prepping for calls by asking the AI, what are the top three priorities for a CFO at this specific company likely to be?

00:02:41: Ah, that's the smart leverage, not just automation.

00:02:44: Ryan Staley had some actual numbers on this too, didn't he?

00:02:46: He did.

00:02:47: Companies using these AI agents, they're seeing about sixty percent more demos booked.

00:02:51: Sixty

00:02:52: percent?

00:02:52: Yeah.

00:02:53: And maybe more importantly, saving reps around ten hours a week.

00:02:56: Ten hours.

00:02:57: And that time presumably goes back into the stuff AI can't do well, like complex deals, building relationships.

00:03:02: Exactly.

00:03:03: It multiplies the team's capacity almost instantly.

00:03:05: But

00:03:05: if you change capacity that much, the role itself must change.

00:03:09: Which, uh, seems to be happening.

00:03:11: Definitely.

00:03:12: Spencer Perrick had this interesting take.

00:03:14: He suggests the FDR is morphing into the XDR.

00:03:17: XDRs.

00:03:18: Yeah, the Experience or Execution Development representative.

00:03:20: Yeah.

00:03:20: The idea is shifting from high volume outreach to high precision.

00:03:24: orchestrating buyer journeys based on intense signals, not just cold calls.

00:03:27: So more targeted, more intelligent outreach.

00:03:30: Right.

00:03:31: And Jason M. Limkin kind of echoed this.

00:03:33: He observed that AISDRs, they've basically beaten any human SDR who's just doing spray and pray.

00:03:40: Okay.

00:03:41: But, and this is key.

00:03:44: the absolute best account executives.

00:03:46: They still crush AI on the big creative relationship heavy deals.

00:03:51: The AI handles the, let's call it smaller stuff.

00:03:54: That distinction makes a lot of sense.

00:03:55: AI for volume and routine, humans for strategy and relationships.

00:03:59: But okay, if we're aiming for precision and orchestration, we really need to talk about the ethics and the guard reels.

00:04:04: That was a huge part of the conversation too.

00:04:06: Precision without governance is

00:04:08: danger.

00:04:09: Oh, absolutely.

00:04:09: Because when that precision fails, you get brand damage.

00:04:12: Fast.

00:04:12: Well, I'd have if it shared a, well, a pretty painful example.

00:04:15: What happened?

00:04:15: An AISDR system cold-cold an existing customer.

00:04:20: An eight-year customer trying to sell them the product they already use.

00:04:23: Ouch.

00:04:24: Because it didn't check the CRM first.

00:04:26: Exactly.

00:04:27: Failed to check the CRM.

00:04:28: It's not just annoying.

00:04:29: It actively damages the relationship and wastes everyone's time.

00:04:32: Yeah.

00:04:33: Automating sloppy work just makes the problems bigger and that ties into transparency too, right?

00:04:37: Benjamin Scoog brought that up.

00:04:39: He did.

00:04:40: He argued strongly that AISDRs shouldn't pretend to be human.

00:04:45: Buyers, he thinks, care more about getting fast, relevant answers than who provides them.

00:04:50: And they feel tricked if they find out later it was a bot pretending.

00:04:53: Yeah, that feeling of being duped really undermines trust.

00:04:56: So it all comes back to what good outbound actually is.

00:04:59: I think Yuri Zaremba put it

00:05:01: well.

00:05:01: What was his take?

00:05:02: That good outbound isn't about volume, it's about contacting the right people, those most likely to engage.

00:05:08: Better to focus an AISDR on, say, three hundred high-quality contacts than burn through three thousand low-quality ones with spray and pray.

00:05:17: Quality

00:05:18: over quantity powered by intelligence.

00:05:20: Exactly.

00:05:21: Which actually tees up our next big theme perfectly.

00:05:24: Because all that precision, or the lack of it, it all relies on the underlying data and systems.

00:05:29: Right.

00:05:30: We're moving into GTM strategy, intelligence, and infrastructure.

00:05:34: And the big realization here seems to be that the tech itself isn't the main bottleneck anymore.

00:05:39: It's more an intelligence problem.

00:05:41: and an infrastructure problem.

00:05:42: That's what the data suggests.

00:05:44: Much of OJ highlighted this low ROI from AI investments.

00:05:48: Like less than five percent often stems from that intelligence gap, not an automation gap.

00:05:53: Then the numbers are stark, aren't they?

00:05:54: They really are.

00:05:55: According to a Zoom info report, she cited, AI usage is up.

00:05:59: Like almost nine hundred percent since twenty-twenty-two.

00:06:02: Massive jump.

00:06:03: Wow.

00:06:03: But only nineteen percent of companies felt their data was actually AI ready.

00:06:07: Nineteen percent.

00:06:08: So for the other eighty-one percent, just adding a new AI tool on top isn't going to magically fix things if the data underneath is messy.

00:06:14: Exactly.

00:06:15: Garbage in, garbage out, just faster.

00:06:17: Daniel Remedios argued pretty forcefully that just bolting AI on a broken GTM systems, that just leads to stalled growth.

00:06:24: So what's the alternative?

00:06:25: He says you need a new foundation.

00:06:28: A GTM intelligence infrastructure.

00:06:30: He called it a GPM brain.

00:06:31: A GTM brain.

00:06:33: I like that.

00:06:33: Yeah, the idea is it provides the essential context, intelligence, a crucially memory that AI needs to power specialized analysts and execution agents effectively.

00:06:42: Two hundred and four seven.

00:06:43: Context seems key.

00:06:45: Chris Liu was talking about that too, right?

00:06:47: That the real transformation is rethinking the data layer itself.

00:06:51: Absolutely.

00:06:51: Making sure rich, dense context gets fed to the LLMs.

00:06:55: That's what separates truly useful, specific AI outputs from just generic fluff.

00:07:02: Okay, so we're moving beyond just using AI for basic productivity boosts.

00:07:06: That's phase one, according to Coco Sexton.

00:07:07: He noted, yeah, maybe two thirds of GTM teams use AI daily for productivity.

00:07:11: That was the appetizer.

00:07:12: And

00:07:13: phase two.

00:07:13: Phase

00:07:13: two is where the real winners are moving.

00:07:15: They're using AI to do things better, focusing on pipeline growth as the main course, not just efficiency gains.

00:07:21: Better, not just faster.

00:07:22: But if context is king, there's a big warning sign here too.

00:07:25: Stephanie has pointed this out.

00:07:27: What was that?

00:07:27: That just blindly copying a competitor's AI strategy is really dangerous.

00:07:32: Your GTM success depends so much on your unique context, your ICP maturity, your typical deal speed, how clean your data is.

00:07:40: Right.

00:07:41: What works for them might totally fail for you if your starting point is different.

00:07:45: So you can't just copy paste AI tactics.

00:07:48: No.

00:07:49: Which means leaders need to be, well, brave internally.

00:07:54: Drew Neiser had some practical advice on budgeting for this.

00:07:56: Oh yeah.

00:07:57: He basically said GTM leaders need to kill programs that just feel good, but aren't actually delivering measurable results.

00:08:03: Be ruthless there.

00:08:04: Free up budget.

00:08:05: Exactly.

00:08:06: And then deliberately allocate maybe five to ten percent of that budget specifically for experiments, targeted bets that could lead to breakthroughs in how you use AI next year.

00:08:14: You have to actively fund that shift.

00:08:16: Funding the future.

00:08:17: Okay.

00:08:18: That focus on breakthroughs and doing things better brings us nicely to our third major theme.

00:08:23: Content, creativity, and responsible AI use.

00:08:26: Yeah, because even with all this focus on automation and infrastructure, content is still king or queen.

00:08:31: Still

00:08:32: the number one priority.

00:08:33: Seems like it.

00:08:34: Anjali Mullins cited a CMO Alliance report finding eighty percent of marketers are prioritizing content marketing in twenty twenty five.

00:08:42: It's the top channel focus.

00:08:43: And is that because of AI?

00:08:45: in a way?

00:08:46: Partly.

00:08:46: Yes.

00:08:47: Because these LLMs, these GPTs, they apply sophisticated web scrapers.

00:08:52: So you need a steady stream of consistent, authentic content just to rank well within these emerging AI tools and search interfaces.

00:08:58: So we're not just doing SEO for Google anymore.

00:09:01: We need AEO, AI Engine Optimization.

00:09:04: That's

00:09:04: the term Karen Flanagan used.

00:09:05: He called AEO a must have investment now.

00:09:08: And get this, he shared data showing traffic coming from LLMs converts four times better than standard organic search.

00:09:15: Four times?

00:09:15: Okay, that's significant.

00:09:16: Huge.

00:09:17: But he also cautioned that to stand out from all the generic AI generated stuff, what he called AI slop, you need human led content, not just brand led content.

00:09:25: AI

00:09:26: slop, I can see that becoming a problem.

00:09:28: If everyone's automating content, how do you differentiate?

00:09:30: That's

00:09:30: the challenge.

00:09:31: Robert Cooper voiced that exact concern.

00:09:33: If your core brand messaging is kind of weak or incomplete to begin with, AI will just amplify that weakness everywhere.

00:09:40: So differentiation comes back to human strategy, human creativity, authenticity.

00:09:45: Exactly.

00:09:46: Telling stories only you can tell.

00:09:48: Which leads right into responsible use.

00:09:50: Anaboretto was really strong on this.

00:09:52: What was your main point?

00:09:53: Transparency is crucial.

00:09:56: Marketers must be clear when content is AI generated, and purpose has to outweigh just chasing efficiency.

00:10:02: Like with UGC.

00:10:04: user-generated content.

00:10:05: Perfect example.

00:10:06: UGC is powerful because it's about real customer stories, real experiences, using AI to just create replicas.

00:10:14: that completely misses the point and erodes trust.

00:10:16: Authenticity matters.

00:10:18: But creating authentic human-led content takes resources, right?

00:10:22: Internal knowledge.

00:10:23: It does.

00:10:24: And teams often get stuck thinking they need perfect internal documentation before they can even start using AI effectively for content or support.

00:10:31: Which can feel paralyzing.

00:10:33: Yeah, but Liza Adams offered a really practical way around this.

00:10:36: She said, you don't actually need perfect internal knowledge to build effective AI teammates.

00:10:40: Oh,

00:10:41: so how do you bridge that gap?

00:10:42: You can build custom AI tools by blending external research things like industry benchmarks, frameworks you can find using deep research tools with whatever internal best practices you do have documented.

00:10:54: Ah, so you use solid external data to supplement the patchy internal stuff.

00:10:58: Exactly.

00:10:59: It lets you get started and get value from AI much faster, without waiting months or years to perfectly organize all your internal

00:11:06: knowledge.

00:11:06: That's a really useful actionable tip for teams feeling stuck.

00:11:10: Yeah.

00:11:11: And, you know, looking across all these themes... the SDR evolution, the GTM brain, the content challenges.

00:11:17: What really stands out is AI isn't just changing tasks, it's fundamentally changing roles.

00:11:23: How so?

00:11:23: I mean, Rangan made this point.

00:11:25: AI is actively creating new kinds of jobs, new roles within organizations.

00:11:30: Okay, like what kind of roles?

00:11:31: Reorganization almost.

00:11:32: Sort of, yeah.

00:11:33: She sees two main groups emerging.

00:11:35: First, you have the super orchestrators, think AI ops roles, GTM engineers, the people building and maintaining that GTM brain, the systems, the governance, the architect.

00:11:44: All right.

00:11:44: And second, you have the super contributors.

00:11:47: These are your AEs, your content marketers who are using the tools the orchestrators build to achieve, like Ten X the output and impact.

00:11:54: The super users who leverage the system.

00:11:56: Exactly.

00:11:57: That

00:11:57: is a provocative thought to end on.

00:11:59: AI isn't just tech, it's a catalyst for career evolution.

00:12:03: It's forcing everyone to decide maybe which side of that equation they want to be on.

00:12:08: Precisely.

00:12:09: The question isn't if AI will change your job in B to B. It's becoming.

00:12:14: Are you building the skills to be an orchestrator designing the systems or are you becoming a contributor mastering the tools to drive massive impact?

00:12:22: Definitely something for all of us in B to B to think about.

00:12:25: Which role are you building for?

00:12:26: If you enjoyed this deep dive, new deep dives drop every two weeks.

00:12:29: Also, check out our other editions on account-based marketing, field marketing, channel marketing, mark tech, go to market, and social selling.

00:12:36: Thanks

00:12:36: so much for tuning in.

00:12:37: Make sure you subscribe or follow so you don't miss our next look at the key shifts happening in B to B.