AI Buyers, AI Natives, and the New B2B Playbook

From shifting buying journeys to reskilling and AEO, here’s how marketers adapt before the ground moves under them.

Sep 25, 2025

Dear readers, in today’s edition:

AI Is Rewriting the B2B Buying Process – Are You Ready?
The AI skills gap: why 50% of roles may vanish within 18 months
B2B marketing in the AI era: the curator advantage
The AEO Shift: The SEO Deep Dive Worth Your Time
Newsletters beat social: own your audience and design for AI triage

AI Is Rewriting the B2B Buying Process – Are You Ready?

In making decisions and designing marketing strategies and processes, I’ve always leaned on a principle I must have heard countless times from Szymon Negacz: “start with how the client buys.” That principle is even more crucial now - because the way clients buy is shifting under our feet.

Both Szymon Negacz in his podcast episode on AI in B2B sales and marketing (in Polish), drawing on years of experience with Polish industrial and service companies, and Sydney Sloan, CMO of G2, reflecting the U.S. tech market - arrive at the same conclusion: AI is no longer just a tool for sellers. It has become a co-pilot for buyers.

The biggest shift? Autonomous client research, powered by AI, happening long before we even know the client exists. A buying process we once influenced through education and relationship-building now unfolds inside the black box of LLMs. Clients approach us later, better informed, and far less susceptible to our narrative.

Szymon Negacz observes:

“AI… will be the early advisor. Instead of calling a friend or browsing LinkedIn, executives already type the question into ChatGPT to diagnose their problem.”

This reframes the first stage of every buying journey. Instead of discovering a pain point in conversation with a vendor, buyers increasingly arrive already briefed, already comparing options. Sydney Sloan sees the same on the other side of the Atlantic:

“They’re going to LLMs first for research and discovery. They trust it. The second step is peer reviews, then websites. SEO was about clicks; now it’s about answers.”

For marketers, this means the familiar playbook of demand generation gets rewritten. Education still matters - but much of it happens in dialogue with an AI agent, not a blog or a sales deck. As Sloan notes, marketers must think in terms of Generative Engine Optimization (GEO) (or as another expert prefers: AEO) – creating content that LLMs can parse, trust, and recommend.

Negacz warns that the implications go further. AI doesn’t just surface problems - it proposes solutions, simulates ROI, and even compares offers:

“On the stage of concepts… AI already generates multiple strategic options with costs in minutes. That used to take weeks of vendor presentations.”

And at the moment of decision, he emphasizes:

“AI will be the comparison engine. The firm that hides behind vague claims - ‘we’re high quality, we’ve existed for year ’ - will lose. Models don’t care about fluff.”

Both experts underline a universal truth: trust becomes the decisive factor. Buyers will rely on AI to flag risks, aggregate peer experiences, and highlight brands with credible social proof. That’s why Sloan emphasizes:

“Trust starts with brand. Marketers must invest again in brand building, influencers, and the voice of the customer - because that’s what LLMs index as credible.”

Whether you sell software in San Francisco or industrial systems in Katowice, the message is clear: the client’s buying journey is mediated by AI, not you. Your strategy has to adapt - structuring content for algorithms, investing in brand trust, and preparing sales teams for far more educated, AI-briefed buyers.

If the buying process is changing this fast, the real question is: how quickly will your marketing adapt?

Watch the full content here: Sydney Sloan video and Szymon Negacz podcast (in Polish)

The AI skills gap: why 50% of roles may vanish within 18 months

Many leaders know they must adapt their organizations to AI but are hesitant to start. The scale of the change is enormous, and organizational transformation is inherently difficult. Compounding this fear is the lack of proven, off-the-shelf frameworks; the technology is simply evolving too quickly for best practices to emerge.

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The stakes of inaction, however, are higher than the discomfort of change. Jason Lemkin’s framework for team performance distribution reveals the uncomfortable truth about where the impact will be felt first:

The tough, honest start-up truth:
1% of your team is epic
5% of your team is great
15% of your team gets sh*t done
50% of your team does OK-to-solid work
30% of your team adds little value at all
This has honestly always been true. It’s just in 2021, there was so much organic demand for everything in business software, it masked things. And the 50% and midpack could, e.g., still be decent closers.
Not today.
AI is coming for the last two groups. Faster than most want to be honest about.

This isn’t a secret that can be ignored until the next planning cycle. The pressure to adapt is coming from every direction.

Your board is going to figure this out. Your investors already have. Your competitors definitely will.

The solution begins with re-segmenting the team based on their intrinsic attitude toward AI. This new framework reveals three distinct archetypes, providing a clear lens through which leaders can view their workforce:

The Three Types of People You’ll Discover
The AI Natives (20%): They pick up AI tools instantly. They’re already experimenting with ChatGPT, Midjourney, and automation workflows on weekends. These folks will 10x their output.
The Reluctant Adopters (50%): They’ll use AI tools if forced to, but they’re not innovating with them. They see AI as something that threatens their job security rather than amplifies their capabilities.
The Resisters (30%): They actively avoid AI tools. They have philosophical objections, or they’re just overwhelmed by the pace of change. These are your biggest retention risk.

While the common refrain is to “reskill” the existing team, the author issues a stark warning against this optimistic but often flawed strategy. He points to an interview with Marc Benioff of Salesforce as an example of this disconnect.

Benioff is right that reskilling is possible.
But he’s wrong about the timeline and success rate. Most reskilling programs fail. Not because the technology isn’t there, but because people fundamentally resist changing how they work. And reskilling for AI has to happen faster, with bigger results, than prior transitions.

Shortly after this interview, Salesforce laid off 4,000 employees, reskilling only several hundred of them - reinforcing the author’s point about the profound difficulty and often low success rate of large-scale, rapid reskilling initiatives.

Instead of a top-down, one-size-fits-all training mandate, the author proposes a simple, bottom-up strategy for leaders to drive change and discover their true AI Natives. This approach naturally filters out those who cannot adapt while creating a sense of ownership among those who can.

Here’s what I tell every CEO I advise: Bring in a new AI tool each week if you can, each month at a minimum. And see who rises to the occasion and leverages it. And who stares blankly at the Zoom.
AI is evolving at breakneck speed. What took 6 months to build last year now takes 6 days. The tools that seem impossible today will be table stakes next quarter.
I know a VP of Marketing who introduced a different AI tool every Friday for 3 months. Video editing AI. Social media schedulers. Content generators. Email optimization tools.
The results were brutal and revealing:
3 people dove in immediately, started experimenting over weekends, came back Monday with creative use cases
5 people tried them halfheartedly, used basic features, didn’t see the point
4 people literally ignored every new tool introduction

This simple diagnostic test provides the data needed to execute a more formal transformation. Lemkin provides a concrete framework that leaders can use to navigate the change over a single quarter.

The 90-Day Action Plan
Month 1: Audit every role. What percentage of their time is spent on tasks AI could handle?
Month 2: Start the transformation. Give your team AI tools. Measure output changes. Identify who adapts quickly.
Month 3: Restructure around human+AI hybrid roles. Double down on your adapters. Have tough conversations with those who can’t make the leap.

Your agenda is no longer just about managing projects and people; it’s about executing a deliberate plan to identify and empower the AI Natives who will define your company’s future.

The B2B Marketing Skills You Need to Win in an AI World

AI won’t replace marketers - but it will expose who actually adds value. The article frames the divide not as human vs. machine, but as how strategically humans use the tools.

In this reality, the winning skill isn’t raw creation - it’s curation (remember, ZestScout is the tool for that). Marketers who can filter noise, contextualize, and surface what matters will stand apart. That means reskilling away from mechanical production and doubling down on distinctly human strengths:

Taste and judgment: AI can output a hundred ideas; only you can sense which one resonates six months from now.
Context and purpose: Great marketing isn’t just aesthetics; it’s about timing, audience, and cultural signals AI can’t read.
Strategic integration: Know when AI accelerates iteration vs. when human oversight drives connection.
Storytelling: The timeless differentiator. Narratives rooted in psychology and culture still cut deeper than any algorithm.

The reskilling challenge here is clear: marketers must evolve from creators to curators, from executors to editors. AI democratizes production; humans must elevate discernment.

In short: your new edge isn’t faster output - it’s sharper judgment.

The AEO Shift: The SEO Deep Dive Worth Your Time

We’ve shared plenty of articles about SEO, whether it’s dead, and the rise of GEO/AEO. But if you read or listen to just one deep dive - make it this one. Ethan Smith (CEO of Graphite), my go-to expert on SEO after 18 years in the trenches, lays out the clearest playbook I’ve seen. The conversation with Lenny Rachitsky is the definitive guide to understanding how AI is reshaping search.

Smith has been at the forefront of what’s now called AEO (Answer Engine Optimization) - getting your product to appear in ChatGPT, Claude, Gemini, or Perplexity answers. His data is striking: traffic from ChatGPT converts six times better than traffic from Google search. The funnel is still much smaller than traditional search, but it’s growing quickly, and most companies aren’t even aware of the opportunity.

The Playbook

1. See AEO as a new funnel, not a replacement. Search is still dominant, but answer engines are a fast-rising channel. Winning here means being cited, referenced, or recommended in those AI-generated answers.

2. Optimize for citations, not just rankings. Structure your data, mark up FAQs, and link entities so LLMs reliably connect your brand to the right concepts.

3. Engineer for training, not just readers. Brutal truth: a lot of your content may never be read by humans. Its value is in training the engines that decide what answers people get.

4. Track new KPIs. Beyond SERPs, measure:

Reference rate (how often engines mention you).
Attribution depth (whether your product is explained, not just dropped in).
Citation quality (are you listed as a source?).

5. Build AEO loops. The new flywheel: structured mentions → model training → engine recommendations → more citations. Done right, it compounds alongside SEO rather than replacing it.

Reality Checks

If you’re only optimizing for Google, you’re missing a parallel channel that converts better.
LLMs are becoming a new homepage. Being cited there matters, even if volumes are smaller today.
AEO is compounding. Early movers will be hardest to unseat.

The Content Flood Problem

One of the sharpest sections is their discussion of AI-generated spam flooding the web. Ethan Smith shares a practical framework to separate signal from noise:

Valuable content = Information Gain + Authority + Experience

Information Gain: Does it add something new to the conversation?
Authority: Is it published or referenced by a trusted, high-signal source?
Experience: Is there real expertise or context, not just word salad?

At ZestScout, this hit home. Curation is our job, and the hardest part is weeding out AI-generated junk while surfacing content with real info-gain and authority. We love Smith’s framework because it’s the closest thing we’ve seen to a practical filter for the new content ecosystem.

Bottom line: SEO isn’t dead, but the rules have changed. AEO is a smaller funnel today - but one that’s growing, converts better, and compounds fast. Ignore it, and you risk being invisible where tomorrow’s buyers are searching.

Newsletters outperform social: 295x value

Email beats algorithmic rent-seeking. It is permission, identity, and durability in one channel. In a coming AI-filtered inbox, only clear structure and authentic voices survive. Build the list now, design it right, and own your reach.

Own the channel – permission-based, open protocols, high ROI; U.S. firms now spend more on paid email subscriptions than newspapers; Substack hosts 61% more paid newsletters than Medium.
Design for UX – minimal sign-up, instant welcome, clear From and subject, scannable layout, image alt text, one-click unsubscribe, with opt-down choices to cut churn.
Control cadence – offer frequency and topic preferences; 59% unsubscribe due to too many emails, 51% due to sender frequency.
Optimize for AI – craft subjects and preheaders, structured headings, authenticated sending, and unique data that assistants elevate, not discard.

My 25,000 newsletter subscribers generate 44 times more page views than my 166,000 LinkedIn followers. This means that each newsletter subscriber is worth an astronomical 295 times more than a LinkedIn follower. When it comes to reliably reaching your audience, newsletters’ signal-to-noise ratio is hard to beat.

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