7 AI SEO Insights for B2B Marketing Execs

More buyers are discovering and researching solutions entirely within LLMs, reaching traditional search and your website only when they're ready to validate and commit.

For B2B marketing leaders, this isn't a future trend. It's happening now.

Here are seven insights on how to adapt your search strategy for 2026 while protecting the SEO foundation that still drives the majority of your pipeline.

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1. SEO is not “dead”

Let's address the elephant in the room.

AI search isn't killing SEO. It's expanding it.

SEO has always been about one thing: helping brands get discovered where target audiences research, evaluate, and make decisions.

Google. Bing. YouTube. G2. Reddit. Marketplaces. Social platforms. Local search.

The surface changes. The goal doesn't.

Get discovered by the right people, at the right moment, in the right place.

AI search is another surface. Another touchpoint for discovery and evaluation in the buyer journey.

Which means it needs to be part of your search strategy. Not a replacement for it.

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2. Success rests at the intersection of SEO and GEO

AEO. GEO. LLMO. AISEO. E-I-E-I-O. :)

Call it whatever you want.

But understand this: it's not a zero-sum game.

GEO isn't competing with SEO. They work together.

Much of what drives strong SEO performance also fuels visibility in LLMs:

Creating well-structured content that incorporates expert insights and internal data. Content that can't be easily replicated.

Owning multiple SERP touchpoints-your website, YouTube, Reddit, third-party listicles, aggregators-for high-priority search terms.

Earning mentions in credible industry publications.

All of these efforts drive visibility in both organic search and AI search results.

Now, I’m not saying SEO = GEO.

There are nuances.

For example, we can analyze which sources LLMs cite most often and prioritize content placements there. These insights also inform PR strategy.

Think of it as a Venn diagram.

A small slice is SEO-only. Another small slice is GEO-only.

The largest portion sits at the intersection.

Your SEO strategy can, and should, fuel AI search visibility.

GEO doesn't require a completely new skill set or separate service line.

Your SEO team is still best positioned to guide you through this evolution.

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3. SEO has moved downstream

2025 was the year CTR collapsed.

LLMs and AI Overviews absorbed clicks at the top of the funnel, where buyers discover and evaluate solutions.

More people are using LLMs to research, compare, and shortlist options without visiting a single website.

Decision-shaping activity. Zero clicks.

By the time your ICP returns to traditional search, they've already built a consideration set.

They're using search to validate choices, gather perspectives, narrow shortlists, and take action. Book demos, start trials, schedule consultations.

This explains why we're seeing higher conversion rates from LLM sources, branded search, and direct traffic across our B2B client base.

Visitors arrive more informed and ready to act.

Here's what this means for your SEO strategy:

Traditional search now serves two key functions:

First, it's evolved into the commitment layer where buyers validate and convert after AI-driven discovery.

Second, it remains the index that LLMs use to retrieve and cite information. When users ask high-intent, down-funnel questions in LLMs, these models search live indexes such as Google and Bing to ground their responses.

If your content doesn't rank in the search index, it's unlikely your brand will be mentioned or cited in AI search results.

This means you need visibility in traditional search to capture conversions and to feed the AI discovery layer that shapes decisions upstream.

The question you need to ask isn't "How do we get more clicks?"

It's "How do we shape the decision before the click ever happens and ensure we're the source LLMs cite when it matters?"

Win upstream visibility in AI search, where buyers form opinions, and downstream rankings in organic search, where they convert.

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4. Content strategies need to be “grounded”

There is little value in targeting top-funnel topics that are already baked into LLM training datasets and rarely lead to citations or brand mentions in AI search results.

Instead, we recommend focusing on the topics that can rank well in organic search and require grounding in LLMs.

The grounding piece is important.

LLMs use retrieval-augmented generation (RAG) to pull relevant information from trusted sources and use it as context for the model’s response.

Instead of relying only on what the model already knows, it grounds answers in up-to-date, specific data.

This involves pulling information from a live index, such as Google or Bing.

When it does this, it provides citation links that can drive users back to your website.

Here are some of the content types and formats that can drive high-intent visibility across both organic search and LLMs:

• Best [use case/ role] software for X
• Best [use case/ role] software for [industry]
• Competitor alternative listicles
• Competitor comparisons
• Industry studies/reports
• Solution pages that speak to ICP roles/industries
• Product-centric FAQ pages
• Detailed support docs/ help centers (e.g. how to migrate from Competitor X)

This is how we help B2B clients increase visibility, referral traffic, and trials/demos from LLM sources.

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5. Perspective is the real moat

The web is drowning in AI-generated content.

Generic. Surface-level. Regurgitated ideas that everyone else is publishing.

LLMs are getting better at spotting this. Their quality filters will only tighten.

The long-term play: original data, expert insights, real-world experience.

When you bake SME perspectives and internal data into your content, you create something that can’t be easily replicated.

A case study with specific metrics. A survey of your customer base. An expert's take on an industry shift. First-hand implementation advice.

This is what keeps your content ranking and getting cited as LLMs tighten quality standards.

Perspective levels the playing field.

A mid-market SaaS with strong customer insights and original research can outrank enterprise competitors publishing generic content at scale.

You don't need the biggest content budget. You need the most valuable perspective.

Build that moat now.

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6. SEO should be multichannel

Traditional SEO focused on one thing: ranking your website in the top 10 results.

That's no longer enough.

Modern search is fragmented across multiple touchpoints.

Your website, YouTube, Reddit, third-party listicles, comparison sites, social media, review platforms, and LLMs.

Buyers zigzag across touchpoints before deciding. They see your brand in a Reddit thread, watch a YouTube comparison, check G2 reviews, then visit your website through branded search.

Each touchpoint builds familiarity and trust.

When you own multiple SERP positions for high-intent keywords, you create more opportunities to shape buyer perception.

LLMs prioritize brands with diverse, credible mentions across multiple sources.

When your brand appears in YouTube videos, Reddit discussions, third-party reviews, and trusted industry publications (not just your own website), LLMs interpret that widespread presence as proof you're credible.

A multichannel SEO strategy includes:

• Website rankings for priority keywords
• YouTube presence (tutorials, demos)
• Aggregator placements (G2, Capterra, TrustRadius)
• Mentions in industry publications
• Community discussions (Reddit, Quora)

The goal is to own multiple search touchpoints for your most important search terms.

Brand mentions across multiple sources also drive LLM visibility.

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7. KPIs and attribution must evolve

Marketing attribution needs to adapt.

More discovery and evaluation happens in LLMs, where clicks rarely occur.

By the time users reach your website, they've already researched, compared, and narrowed their choices.

This creates a challenge:

How do you measure influence when there's no click to track?

Expand your KPI framework.

Track direct conversions from organic search and LLM sources. But also measure directional signals that indicate upstream influence:

• Qualified traffic over volume
• Brand mentions and citations in LLMs
• Branded search lift
• Direct traffic increases
• Home page entrances
• Conversion rate improvements
• AI Overview placements
• Self-reported attribution ("How did you hear about us?")

Beyond new KPIs, attribution models themselves need to evolve.

Multi-touch and assisted-attribution models provide a more accurate picture than last-touch models. These approaches give credit to first-touch discovery, acknowledging the role organic search plays early in the journey.

Last-click models consistently undervalue organic search when AI surfaces shape decisions upstream.

Measurement must reflect the full journey, not just the final click.

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Organic and AI search should work together

AI search didn't replace SEO. It expanded it.

The brands winning in 2026 treat organic and AI search as complementary, not competing channels. They're building strong visibility upstream, where buyer decisions are made, and downstream, where conversions occur. And they’re adapting their measurement frameworks to reflect influence across both surfaces.

Want to drive more pipeline from organic and AI search? Let’s talk.

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