Demand gen’s new frontier: AI-era buyers and the dual-track strategy
Senior B2B marketers have heard the proclamations like “the MQL is dead” or “the funnel is obsolete.” Yet day-to-day, your pipeline still relies on capturing leads and nurturing them into opportunities. So, what’s really happening? Our President, Americas, Ricky Abbott sheds some light on the future of demand gen.
This blog is the first in a four-part series exploring the intricacies of today’s AI-enhanced landscape and how to best leverage LLMs and AI tools to create business advantage.
Demand generation is evolving – rapidly – due to the rise of AI and large language models (LLMs) like ChatGPT. But that doesn’t mean traditional marketing qualified leads (MQLs) and lead gen methods no longer matter. We’re just entering a dual-track era: one that still runs on search-driven content and classic funnel metrics, and a new one where AI-driven research journeys shape buyer decisions.
This provocative deep dive explores how demand gen’s role is changing in the age of AI, how LLMs are influencing buyer behavior (especially mid-funnel), the elevated role of brand building going forward, and why marketers must master a two-pronged strategy to succeed today to lay the foundations for a heavily search-reduced future.
Buckle up – the rules of B2B marketing are being rewritten in real time and this'll be a long one.
The changing role of demand gen (and brand) in the age of AI
For years, B2B demand generation has centered on attracting prospects via content (often through Google search), converting them into MQLs (say, via a whitepaper download or demo request), then feeding those leads to sales. This model isn’t disappearing overnight – but it is under pressure. Why? Because the way buyers search, learn, and evaluate is shifting in fundamental ways.
What used to bookend the customer journey – brand and sales – are changing in significant ways. Buyers go farther on their own. Today’s B2B buyers spend ~83% of their buying journey researching independently, without sales. They educate themselves through digital content, peer reviews, and now AI tools, before ever talking to a vendor.
Brand used to lay the foundations for the conversation, and demand gen would then guide this self-education mainly via SEO, content marketing, and email nurture. Now there’s a new educator in the mix: intelligent AI assistants.
Enter the AI advisor
Generative AI tools (like ChatGPT, Gemini, Claude, etc.) have quickly become go-to research aids. In fact, nearly 90% of B2B buyers already use generative AI tools during the buying phase. Let that sink in – almost 9 in 10 buyers are asking AI questions at some stage of a B2B purchase.
What does that mean for demand gen? Your content is often being read by an AI before the buyer ever sees it. The marketing funnel now has a new kind of intermediary. But that doesn’t mean traditional search is done – at least, not yet.
Google Search remains dominant in 2025, and even saw ~22% growth in query volume in 2024. On average, a B2B researcher still performs about 12 searches prior to engaging a vendor. Classic SEO-driven content and SEM campaigns remain vital to capture that interest.
AI is just supplementing how buyers search. Instead of combing through multiple webpages, a buyer might pose a complex query to an AI and get a synthesized answer in one go. Forrester finds that AI Q&A is indeed supplementing (not fully replacing) traditional search at this point. In other words, many buyers now search in two ways – they Google and they ask ChatGPT.
In today’s transitionary landscape, marketers must influence two parallel research behaviors: the old-school way (human uses a search engine, reads content, fills out form) and the new way (human asks AI, AI reads your content, human maybe never fills a form).
The mission – driving awareness, consideration, and lead capture – is the same, but the tactics to accomplish it are diverging into a dual-track approach. What works for one track won’t work for the other. And that means a lot for how B2B organizations approach their brand-building and sales enablement strategies.
Before we detail that, let’s examine how exactly LLMs are changing buyer behavior – especially in the critical mid-funnel where prospects narrow choices and compare options.
LLMs in the buyer journey: Mid-funnel is morphing
By now, we’ve all seen how AI chatbots can answer trivia or draft an email. But how are they specifically changing B2B buying? The biggest impact is in the research and consideration stages – the ‘mid-funnel’ where prospects have identified a problem and are evaluating solutions. Here’s what’s happening:
Wider consideration sets
Historically, a busy buyer might only seriously consider 2-3 vendors before making a shortlist. Now, an LLM makes it easy to ask, “Who are all the top providers of X solution?” and get a broad, unbiased list. AI is widening the funnel, and with analysts predicting buyers will consider ~5 or more vendors on average with GenAI, alternative suppliers buyers might have originally missed via search are also being surfaced. It’s here that the strength of your brand will make or break whether you’re among the initial consideration set.
Accelerated info gathering
Mid-funnel research that used to take days of reading can now happen in minutes. Forrester anticipates that even in complex B2B deals, AI-augmented buyers will come to decisions faster than before because they can remove a lot of friction in learning. The funnel is compressing in time – a prospect might reach a conclusion in weeks instead of months, armed with AI-curated insights.
Non-linear journeys
In reality, the classic funnel was never linear (Google calls it the ‘messy middle’), and with AI it’s even less so. Buyers can now jump around with AI’s help. The journey becomes on-demand and non-sequential. Whenever a question arises, the buyer asks the AI, at any stage. This means every piece of content (early, mid, late funnel) could be pulled into the conversation at any time. Marketers – and what will increasingly become the norm, Sales – must ensure answers are ready for a buyer’s random-access information needs, and aligned to your brand marketing strategy.
Greater self-service, later sales engagement
AI is effectively acting as an automated research assistant for the buyer. That pushes the point of contacting a sales rep even later. With AI handling Q&A, buyers feel even more empowered to self-serve. Routine questions that might have prompted a call now get answered by a chatbot.
The result? By the time a buyer finally reaches out to your sales team, they might already have a rich understanding of your (and your competitors’) offerings – potentially even misconceptions that came from an AI. It’s critical that your digital content and tools (blogs, knowledge bases, FAQs, chatbots) address those mid-funnel questions, because human reps won’t get a chance until later.
Brand will be crucial for trust
B2B buyers purchase from brands they trust. The less direct research they do themselves, the less likely they are to have encountered enough touchpoints to be truly aware and engaged with your brand.
One great way to do just that is to use brand storytelling to establish more than a professional relationship with your audience. Building more than surface-deep relationships with your buyers and prospects will give you the edge when your name inevitably appears in a list next to your competitors. And for that to succeed, it requires ensuring every customer-facing function – and especially Sales – understands who you are, what you offer, and how you offer it.
Learn more about the risks and big rewards of brand storytelling.
“Content as conversation”
Perhaps the most radical shift is the notion that buyers may literally converse with your content. Imagine a prospect doesn’t read your 10-page case study PDF, and instead asks an AI (which has ingested that PDF), “Give me the key results this vendor achieved for a finance industry client.”
The AI pulls the answer from your case study and responds with a short summary. This scenario is already possible – tools can train on your content and answer buyer questions in a conversational manner. In effect, your content becomes a dynamic chatbot.
The implication? Content needs to be structured and tagged for easy retrieval by AI. If your content is a tangled mess or locked in ungainly PDFs, AI might struggle to use it, and you’ll be absent from that Q&A. (One technical note: LLMs have a much easier time reading content that is clear, well-structured, and semantically, so investing in content structure and schema pays off.)
We’ll be releasing more content on this topic very soon, watch this space 👀
Collectively, these changes signal that the mid-funnel is being heavily disrupted by AI. Buyers are relying on AI for discovery, for education, and even for validation. And notably, LLMs don’t just inform buyers – they can actively recommend products. A well-prompted AI acts almost like a personal consultant: “Given my needs, which solution is best?”.
We’re already seeing evidence of AI-driven recommendations influencing deals. In one analysis, ChatGPT-driven suggestions led to a 436% spike in conversions for certain offers. And buyers trust these AI outputs more than you might think: 38% of B2B buyers trust generative AI platforms for assessing solutions, and 34% trust AI advice when shortlisting vendors. That means a sizable chunk of your audience might believe what the AI tells them about you or your competitor – for better or worse.
The bottom line is, the AI-empowered buyer is more informed, considers more options, and moves at a brisker pace than ever. They’re conducting a ‘chat-driven’ journey alongside the traditional web-driven journey.
For marketing leaders, this raises a critical question – how do we ensure our brand is front-and-center in these AI-mediated research processes, without abandoning the traditional funnel that still brings in leads? The answer lies in adopting a dual-track demand gen strategy.
The (temporary) dual-track approach: Serving search & AI
Given these twin realities – (1) the enduring importance of traditional search-driven funnels and (2) the rapid rise of AI-driven research journeys – B2B marketers must now operate on two parallel tracks. Neglect either one at your peril. Let’s break down what each track entails:
Track 1: Master the traditional funnel (MQLs still matter)
Despite rumors of its demise, the classic funnel is alive and kicking. MQLs, SQLs, opportunity stages – they’re still how most B2B revenue engines run. We’re just entering a transition period where LLM usage is in its infancy. But if the numbers are anything to go by, it’s only a matter of time before it supersedes search volume.
The first track is doubling down on modern best practices of traditional demand gen:
Win the searchers
Continue investing in SEO and content marketing to capture those researching the old-fashioned way. High-quality blog content that ranks on Google, thought leadership that gets shared, and informative assets will ensure you don’t lose the organic search game. Remember, search volume isn’t declining YET – people still turn to Google heavily for B2B queries (and often after getting a primer from AI).
Offer value for data
Gated content and lead magnets should still play a role, but use them judiciously. Buyers are tired of shallow eBooks. Make sure what you offer in exchange for contact info is genuinely valuable (research reports, benchmarks, deep how-to guides). Just because AI can summarize content doesn’t mean buyers won’t fill out forms – they will, if the payoff’s worth it.
Optimize lead qualification and speed
One valid criticism of the MQL model is that it can be slow or misaligned with sales. Use automation (even AI tools like chatbots or AI SDRs) to respond faster to inquiries. Studies show the first vendor to respond wins the deal 78% of the time, and responding within 5 minutes makes leads 21x more likely to convert. It’s not that MQLs are obsolete; you just have to respond to them in real-time.
Nurture and educate
Long sales cycles aren’t vanishing overnight; prospects will still appreciate helpful content over months. What will happen though, is that sales journeys will become compressed, more intense.
Marketing will no longer be the sole vanguard of a business’ brand; it’ll rest on sales teams to ensure the brand experience, message, and value prop is consistent across touchpoints – if and when buyers get to them. The twist is, you need to start incorporating AI personalization (for instance, AI-written follow-up emails tailored to the lead’s behavior) today to give your brand a chance for success.
Track 1 is about refining the classic demand gen playbook with new tools, not discarding it. MQLs still matter because they represent engaged individuals showing intent. Focusing only on this track would be a grave mistake in an increasingly AI-driven world. But it’s also not going to last forever – B2B marketers need to be prepared for a heavily search-reduced future.
That’s where Track 2 comes in.
Track 2: Embrace the AI-driven journey (content for LLMs)
This second track is newer territory for marketers: making sure your brand is visible, influential, and accurate within AI-driven conversations. Call it SEO for AI, LLM Optimization (LLMO), Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), whatever you want; the goal is to serve the AI-assisted buyer who might not engage the same way as a traditional lead.
Keep an eye out for more content in this series on optimizing for GEO!
LLM visibility and ‘ranking’
Just as you fight to rank on the first page of Google, you now need to ‘rank’ in the answers of ChatGPT, Gemini, Claude, and other LLMs. Harvard Business Review notes that just as SEO emerged in the era of browser search, a new science of LLM optimization is now emerging. The more places your expertise appears (website, blogs, press articles, forums, even Wikipedia), the higher the chance an LLM will ‘know’ about you and mention you.
Provide AI-ready content
LLMs love concise answers, definitions, FAQs, and data points. If your website has an obvious FAQ section answering common questions about your product/category, an AI is more likely to pick those up than if the answers are buried in prose. Likewise, publishing things like How-to Guides, Top 10 Considerations for X articles, or straightforward fact sheets can feed AI knowledge. The mantra here is structure and clarity: if your content is structured as clear answers and data, it’s AI gold.
Monitor your AI presence
Just as you might track your search rankings or brand mentions, you should periodically check what AI chatbots are saying about your product or category – it can be be eye-opening. You might find outdated info or missing details, and that’s a signal to publish better content on that topic (or in extreme cases, to consider fine-tuning a custom AI model with correct info for your sales team or customers).
Influence the AI algorithm (ethically)
No, you can’t log into ChatGPT and tweak the answers. But you can influence AI outputs indirectly. Think of it like digital PR. Brand mentions across reputable sites act like the inbound links of the AI world – they signal that your brand is relevant to certain topics. The more an LLM sees your name associated with ‘leading solution in X,' the more likely it might include you in its answer to “What are the leading solutions in X?”.
In essence, Track 2 involves a hybrid of content marketing, SEO, and PR geared toward an AI readership as much as a human one.
The future belongs to the adaptable
We are at a crossroads in B2B marketing. On one side, the tried-and-true methods continue to drive results. On the other, a brave new world of AI-driven buyer behavior is challenging us to rethink how we get found and how we persuade. This isn’t a zero-sum choice. The future belongs to marketers who can do both.
Embrace the dual-track approach for the time being. Audit your current funnel and your ‘AI readiness.’ Start ensuring your content is AI-friendly and your brand is present in those AI-driven dialogues, and consistent with everywhere else it appears. You can’t control what GenAI platforms say about you directly; but you can influence how your audience perceives and interacts with your brand.
At the same time, look for opportunities to inject AI into your own marketing operations – from content creation to lead follow-up – to accelerate the old funnel where you can. It’s analogous to when social media emerged; it didn’t kill email marketing, but it did add a new dimension. AI is just adding yet another that will become the dominant platform in the future.
Next steps: As you plan for the coming year, dedicate effort to this new track. Train your team on the basics of LLMs. Perhaps most importantly, consider leveraging tools that can help you execute on both fronts.
One such solution is our AI-Powered Content Engine, which we’re excited to introduce soon. This platform was built to help B2B marketing teams create and optimize content for both search engines and AI algorithms simultaneously.
It uses advanced LLM technology to generate expertly written content (so you can scale up your output for SEO and thought leadership), automatically structuring and tagging content in a way that’s easily digestible by AI models. The result? You get human-friendly, SEO-friendly blog posts, whitepapers, and FAQs that are also AI-ready out of the box. It’s like having an SEO specialist and an AI whisperer embedded in every content piece.
Learn how our new AI-Powered Content Engine can equip you to dominate both search and AI-driven channels. Start ensuring your brand is unmissable wherever your buyers’ journey takes them by getting in touch! 🚀