How GEO is changing the marketing playbook

Generative Engine Optimisation (GEO) is rapidly evolving the traditional marketing funnel. To win in this new AI-driven landscape, B2B tech brands must fundamentally restructure their approach. Brand, PR and/or product marketing should lead your GEO strategy - not your SEO. Furthermore, marketing and comms teams must shift their focus away from high-volume content production and prioritise information gain - providing the unique data, expert perspectives, and fresh insights that Large Language Models (LLMs) actually reward.

Search used to dominate the traditional B2B tech marketing funnel. Why? Because search was essentially the supermarket shelf of the tech industry. It was our key channel to create physical availability. So, marketing teams and budgets were structured to mirror that reality. The playbook was set. SEO owned the search rankings. The content team churned out articles to feed the SEO machine. And paid media swept up whatever organic missed, while expanding the reach of the content produced 'en masse'.

The goal: to get the buyer to click a blue link and eventually submit a form.

Now AI is changing the game. Instead of crawling through blue links to find answers, buyers are skipping the process entirely, using AI tools to support them through discovery, consideration and selection. 

In fact, AI now validates almost every deal, with 94% of buyers relying on AI tools to validate purchasing decisions (according to Forrester research). Babel’s own research - The Mental Av-AI-lability Index - suggests that AI is not just validating purchases but starting to initiate those purchasing decisions, with upwards of 5% of all tech purchases being made on an AI recommendation.

The conventional click-and-capture funnel is disappearing, and fast!

Now commentators and industry experts are turning their attention to how marketing teams and budgets should be restructured for Generative Engine Optimisation. But before you jump on the bandwagon, there are a few things you should be mindful of.

Why Brand PR and Product Marketing must lead AI Search, not SEO

SEO teams are built to guide users through web directories, while AI search acts as a consultative assistant. Because LLMs reward category-level influence and brand narratives, brand, PR and/or product marketing teams are far better equipped to lead a GEO taskforce than traditional SEO teams.

One of the primary recommendations Babel sees time and again is restructuring to make SEO the new AI search lead. This is a mistake, in my view.

While GEO and SEO are similar in regards to their acronym, they are fundamentally different. While SEO was built to guide users through a web directory, AI search acts as an holistic, consultative assistant. Keywords, rankings and clicks don’t exist in the same way. And, if you are optimising for “citations” you are trying to rank for the bottom of the funnel.

According to research from Demand Genius, 84% of prompts in the B2B buying journey do not cite any brand. Yet, your AI consultant is still actively shaping a buyer’s perception by describing categories, defining requirements and summarising market options. Yes - you want to be the brand that appears in those 16% of answers where a citation is included, but perhaps what is more important is exerting category level influence on the preceding conversation the buyer is having with their AI tool.

Let me explain it another way. It’s like sitting down with a prospect and working through their challenges, requirements and needs to support them in writing the RFP. If you are the brand helping them before the RFP is sent to market, you are likely to be the brand that puts in the winning bid.

This is a far more complex challenge than ranking for prompt clusters or updating the technical structure of your web pages.

It requires a deep understanding of the potential category entry points, a controlled and clear brand narrative, and to consistently deliver quality content that provides the LLMs with information gain - information that introduces net new understanding to a problem space.

Brand, PR and product marketing teams are far more experienced in driving these narratives around broad industry topics and shaping categories. So, I would lean on one of them to lead your GEO task force, not SEO. 

This does not mean SEO is dead or irrelevant. SEO teams will still be an essential part of your multi-function GEO taskforce. They just should not lead it.

Content volume should be traded for quality

Quality content is what will help brands influence and reframe how an LLM views your category. And, in the new AI landscape, quality is vastly better than volume. Why? because AI doesn’t care if you post four times a week if the content just covers familiar ground in familiar ways. 

What it does care about is if you are adding anything new to its knowledge base - a differentiated perspective, a unique data point or analysis, or a new mental model, framework or taxonomy. This is information gain working in full force and is critical to your AI strategy.

Therefore, content teams shouldn’t focus on how many content pieces they create. Instead they should focus on how they can genuinely provide something new. 

Unique data points and research are often the most talked about way of achieving this. And while they are a sure fire way to improve an LLMs understanding (if the data point isn’t something that’s been covered before), you don’t always need it. There are tiers of information gain and differentiated opinions and deep industry insights can help shift LLM framing without adding new data.

The key: your content must provide something the model cannot easily scrape from a dozen other websites. So spend more time on developing less content with better and stronger perspectives.

How content debt confuses LLMs and damages AI search visibility

Content debt is the accumulation of outdated, inconsistent, or conflicting information across your historical content estate that actively confuses how Large Language Models (LLMs) perceive your brand.

If an old blog post from 2022 positions your brand differently than a piece published today, you are actively adding confusion to the models' understanding of your brand. This is a major issue facing content teams looking to optimise for AI, particularly for companies that have undergone multiple acquisitions or several brand evolutions. At Babel, we view this not just as an SEO issue, but as a critical brand protection exercise.

To ensure AI engines get a single, unified view of who you are, the solution requires a strategic cleanup effort:

• Audit the entire estate: Map and review all historical content across your digital footprint to identify messaging inconsistencies.
• Align the narrative: Update, consolidate, or remove legacy assets to ensure your brand is articulated the same way consistently.
• Maintain unified positioning: Ensure that every piece of content moving forward aligns perfectly with the singular brand identity you want the LLM to learn and retrieve.

How to reallocate B2B tech marketing budgets for AI search

As we enter the 2027 planning season, the complex question of how to appropriately budget for this new buyer journey will take centre stage. Do we continue to invest in the same playbook of the search era? Or do we need to reallocate budgets?

There is no simple answer. Each company is different, has different objectives, challenges, targets and funnel problems. But the budget does need to be carefully considered and reallocated to match the new way buyers discover, consider and select vendors.

What remains true? The marketing split. Whether you’re targeting human memorability or algorithmic availability, you still need to balance budgets between long-term brand building and short-term sales activations. According to LinkedIn’s B2B Institute, it should be about a 46/54 split. This division gives your brand the financial fuel it needs to build algorithmic authority over the long term, while still capturing immediate, short-term demand.

What changes? Perhaps your tactical executions. Here are a few I’d consider:

• Elevate PR as a core investment - it’s no longer a soft line item you can simply cut during a bad quarter. It is now a critical long-term investment in both mental and algorithmic availability.
• Fund original research and data analysis - whether you commission some new research or allocate resources to look at your own data, creating unique data points will be crucial to improving information gain.
• Balance new content creation with maintenance - content budgets need to be rebalanced. We can’t just invest in new content, we need to balance it with maintaining the old. 
• Promote executive profiles - LLMs still promote people over brands. Budget must be allocated to executive profiling, particularly LinkedIn, which is the second most-cited source across LLMs (might even be number 1 after ChatGPTs algorithm changes deprioritising Reddit )

The AI search era is not just another channel to optimise - it represents a fundamental shift in how buyers consume information and make purchasing decisions. This is the start of a journey, not the end.

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