Koka Sexton

TL;DR

• The B2B buying cycle has gone invisible. Buyers now complete 60-70% of their purchase research before ever talking to a sales rep. AI search tools and agentic assistants are accelerating this shift.
• The traditional funnel model is obsolete. Linear stages (awareness, consideration, decision) do not capture how AI-augmented buyers actually make decisions in 2026. They show up already informed, already compared, and already skeptical.
• Signal-driven engagement replaces funnel-driven nurturing. Instead of sending the same nurture sequence to everyone, track the digital signals that indicate real buying intent and engage on the buyer’s timeline, not yours.
• The companies that win are the ones whose content surfaces where AI sends buyers to validate decisions. If your brand does not appear in the research layer, you do not exist to buyers who never fill out a form.

I have been in B2B marketing for over 15 years. The funnel was already breaking before AI showed up. Buyers were doing more independent research, involving more stakeholders, and stretching timelines longer. Then large language models entered the picture, and the buying cycle went from broken to unrecognizable.

Here is what changed and how to adapt before your pipeline notices the difference.

The Funnel Was Always a Useful Fiction

Let me be direct about this. The marketing funnel (awareness to consideration to decision) was never an accurate description of how people buy. It was a model that made us feel in control. It gave marketing teams a framework to build campaigns around and revenue leaders a way to forecast.

Real buying behavior is messy. Buyers loop back. They compare. They get distracted. They involve their CFO at the last minute. The funnel smoothed over all of that complexity into something we could put on a slide. It was useful, but it was never true.

AI makes the fiction unsustainable. When a buyer can ask an AI assistant to compare five vendors, surface pricing, identify gaps in each product, and recommend the best fit, they are compressing what used to be a multi-week research process into a single afternoon. By the time they reach your website or talk to your sales team, 70% of the decision is already made. Your funnel never captured any of it.

Three Shifts That Are Already Happening

1. AI Is the New First Touch

Two years ago, a B2B buyer’s first step was a Google search. Today, it is increasingly an AI query. “What are the best B2B marketing automation platforms for a 50-person SaaS company?” “Compare HubSpot and Marketo for mid-market.” “What questions should I ask during a CRM demo?”

AI search engines like Perplexity, ChatGPT, and Claude are becoming the front door to B2B purchase research. If your company and your content are not showing up in those AI-generated answers, you are invisible to the most informed buyers in your market. The traditional SEO playbook (rank for keywords, drive traffic, capture leads) assumes the buyer is using Google. When they use AI instead, your ranking does not matter because the AI synthesizes its own answer.

This has profound implications for your content strategy. If your best-performing blog post is invisible to AI answer engines, it might as well not exist for buyers who start their research with an AI query. You need to audit your content not just for Google rankings but for AI retrievability: does your content answer specific questions with specific answers that an AI can surface and cite? Generic thought leadership that ranks on Google may be invisible to an AI that is looking for structured, authoritative, and differentiated information.

“The first touch in B2B is no longer a Google search. It is an AI query. If your brand does not surface in the AI answer layer, you were never in the deal.”

2. Content Must Be Built for AI Retrieval, Not Just Human Reading

Most B2B content is written for humans: blog posts, whitepapers, case studies, webinars. That content still matters, but it now serves a second audience: AI systems that index, summarize, and recommend.

AI retrievers look for structured information: clear claims backed by data, specific comparisons, authoritative sources. Fluffy thought leadership pieces with no data, no specific claims, and no clear point of view get ignored. The AI cannot summarize something that says nothing.

This changes how you write. Your content needs to answer specific questions with specific answers. It needs to include data points that AI can cite. It needs to differentiate clearly from competitors because the AI comparison will flatten nuance into bullet points. If your differentiation is vague, it disappears in the AI summary.

3. Nurture Sequences Are Dead — Signal Detection Replaces Them

The traditional nurture track assumes the buyer moves through predictable stages over a predictable timeline. It sends Email 1 after 3 days, Email 2 after 7 days, Email 3 after 14 days. The sequence is pre-written. The timing is fixed. The content is the same for everyone.

AI-augmented buyers do not move predictably. They may spend two weeks in silent research, then suddenly reach out ready to buy. Sending them Email 2 of a nurture sequence they enrolled in three weeks ago is worse than useless. It signals you do not understand where they are in the process.

The alternative is signal-driven engagement. Instead of pre-written sequences, you monitor digital signals (website visits, content engagement, LinkedIn activity, intent data) and engage when the buyer shows readiness, not when your calendar says it is time for the next email. I have been applying this framework across my content properties for years. I wrote about the methodology behind it in my piece on Visibility Creates Opportunity.

This is a hard transition for marketing teams that have spent years building nurture sequences, scoring models, and automated workflows. The infrastructure you built assumes a linear buyer journey. When the buyer stops moving linearly, the infrastructure stops working. The fix is not more sequences. It is fewer sequences and more signal detection.

Think of it this way. A nurture sequence is a script. A signal-driven system is a radar. The script says what to say and when to say it, regardless of what the buyer is actually doing. The radar listens for behavior and responds to it. In an AI-augmented buying cycle, the radar beats the script every time. The buyer is generating signals constantly (page visits, content engagement, social activity, intent data). The question is whether your marketing infrastructure is listening.

What to Do About It Right Now

This is not a future problem. It is happening today. Here is where to start.

Action	Why	Time Investment
Audit your content for AI retrievability	If AI cannot parse your content, it cannot recommend you	1-2 hours
Add structured data to key pages	Schema markup helps AI understand your offering	30 min per page
Build a signal-tracking system	Replace nurture sequences with intent-based engagement	1-2 days initial setup
Create comparison content	AI comparison queries need source material — be the source	4-6 hours per piece
Monitor AI answer engines for your category	Know what buyers are seeing before they ever contact you	Weekly 15-min check

The Companies That Win

The gap between companies that adapt to this and companies that do not is going to widen faster than most people expect. The old playbook still works for now because most buyers still use a mix of Google and AI. But the ratio is shifting. Every quarter, more purchase research moves to AI. Every quarter, the buyers who show up to your demo are more informed and have already eliminated more of your competitors.

The winners will be the companies that understand this shift and build for it: content that feeds AI retrievers, sales processes that meet buyers where they are instead of where the funnel says they should be, and signal-driven engagement that activates when the buyer is ready — not when the sequence calendar says so.

The funnel was always a useful fiction. AI just made it impossible to pretend otherwise. That is not a threat. It is an advantage for the teams that stop optimizing a broken model and start building for how buyers actually make decisions in 2026. The data infrastructure required to make this work is significant. I broke down the full framework in my piece on building an AI-ready marketing foundation.

Ready to build a signal-driven pipeline instead of funnel-driven wishful thinking? Let’s talk. I help B2B teams redesign their go-to-market for how buyers actually buy.