The New Role of Brand Positioning in the Age of AI

According to research by Cornell University, traditional positioning strategy provides the foundation for a company’s marketing and commercial decisions. It helps define the Ideal Customer Profile (ICP), identify meaningful differentiation, establish a category or value proposition and develop a distinctive idea that the company wants to own in the customer’s mind.

Consider a cybersecurity company that specializes in helping mid-sized manufacturers protect operational technology and industrial systems. Its strategy might influence everything from its website and sales messaging to the content it produces and the customers it targets.

Ultimately, traditional positioning answers a straightforward question: Why should this customer choose us instead of the alternatives? That question remains important. What has changed is the way customers find the answer. When AI increasingly participates in discovery and evaluation, companies must ensure that their positioning is not “lost in translation” but clear, consistent and interpretable by these AI platforms.

1. From Differentiation to Machine-Friendly Differentiation

Humans are quite good at interpreting context. We can read between the lines, connect ideas and understand what a company means even when its messaging is somewhat vague. AI systems have different attributes. They need information from which they can establish relationships between entities, topics, problems, audiences and solutions.

This isn’t simply a theoretical concern. Research from Princeton University shows that by synthesizing information from multiple sources to produce responses, generative engines are creating a fundamentally different visibility environment from traditional search. Their 2024 study also demonstrated that content optimization could significantly influence visibility in AI platform responses.

For example, consider the difference between saying “We help organizations transform their future” and saying “We provide cybersecurity services to Canadian mid-market manufacturers, specializing in industrial control systems, security and ransomware preparedness.”

The second statement gives both a human and a machine considerably more information. It establishes who the company serves, what it does, where it operates and what specific problems it addresses.

This is what machine-readable differentiation increasingly requires. Companies need to be explicit about: 

• • who they serve, 

• • what problems they solve, 

• • where they are strongest, 

• • what they do not address, 

• • how they compare with alternatives and 

• • what evidence supports their claims.

Importantly, these signals cannot exist only on a positioning slide hidden inside the marketing department. They need to be reflected consistently across the company’s digital footprint, including its website, content, product information, social profiles, reviews, media coverage and third-party references. This is what is known as a company’s digital ecosystem. 

The more coherent these signals are, the more dense an ecosystem is, the easier it becomes for AI systems to build an accurate understanding of what the company is and where it belongs.

This does not mean creating robotic, keyword-filled content designed to manipulate AI systems. Rather, it means becoming clearer about the company’s actual strategic identity and ensuring that identity is consistently represented throughout its digital ecosystem.

The objective is not to trick an AI into recommending a company. It is to make the company’s genuine expertise, differentiation and relevance sufficiently clear that an AI system can accurately recognize them.

2. From Owning a Message to Owning a Category of a Pain Point

Traditional brand positioning often focuses on owning a particular idea or message in the customer’s mind. A company wants to become associated with a particular benefit, category or distinctive concept. On the other hand, AI-mediated discovery introduces another opportunity: owning a problem-space.

Your prospective B2B buyer may not search for a particular company because they do not know which company to look for. Instead, they describe their problem to an AI assistant. For example: “What companies can help a professional association increase member engagement and retention?” Or: “What are the best alternatives to Salesforce for a mid-sized company looking for a simpler CRM?” AI is being asked to identify relevant solutions to a problem.

This means positioning increasingly needs to establish a strong connection between the company and the problems it wants to solve. A consultancy that describes itself simply as a “business transformation firm” may have difficulty distinguishing itself in such a scenario. A consultancy that clearly establishes its expertise in helping professional associations address declining member engagement has created a much stronger relevance between its brand and a specific problem. The goal is therefore shifting from simply owning a message to becoming naturally associated with a category of pain points and solutions.

The strategic question becomes: When a buyer describes the problem we solve, will an AI system recognize our company as belonging among the relevant solutions?

3. From Persuasion to Evidence

Marketing has always involved persuasion. Companies naturally want to emphasize their strengths and communicate compelling reasons to choose them. But AI has changed the information environment in which those claims are evaluated.

An AI system can synthesize information from numerous sources rather than relying exclusively on a company’s own marketing platforms. A company can claim to be “the leading provider” or “the most innovative solution,” but competitors can make exactly the same claims.

What makes one position more credible than another is increasingly the evidence behind it. As mentioned earlier, digital ecosystems now play a crucial role in modern positioning. Customer results, detailed case studies, client reviews, product specifications, expert validation, independent comparisons, original research, certifications and media coverage can all reinforce the brand positioning message a company wants to own.

According to Edelman’s 2025 Trust Barometer, 62% of Canadians said it was becoming harder to distinguish respected news sources from dubious ones. In an environment characterized by declining confidence in information sources, evidence and external validation become increasingly important components of brand credibility.

Imagine two software companies that both claim to provide the best solution for improving sales productivity. One makes the claim repeatedly throughout its website. The other supports its position with hundreds of customer reviews, independently validated research, and detailed case studies showing measurable improvements. Obviously, the second company will gain higher credibility for its brand messaging.

In summary, it is no longer simply, “What do we say we are?” It is increasingly, “What evidence exists that makes this positioning believable?”

4. From Static to Adaptive Brand Positioning

Positioning has traditionally been treated as a relatively stable strategic asset. Companies might revisit their strategy every few years when entering a new market, launching a new product or undertaking a major rebranding exercise. However, AI is contributing to a much faster-moving competitive environment.

Competitors can produce content, analyze customer feedback, develop features and launch campaigns at unprecedented speed. At the same time, customer expectations and the problems they need to solve can evolve quickly. As a result, a positioning message that differentiated a company two years ago may no longer be distinctive today.

This means brand positioning needs to become more adaptive. Rather than developing a strategy and treating it as a finished product, companies need an ongoing process that connects market signals, customer problems, competitive positioning changes,  product and content decisions, and feedback from customers and AI-driven discovery.

For example, an analytics company might originally position itself around automated reporting. As competitors introduce similar capabilities and AI makes basic reporting easier, that positioning may become less valuable. The company may need to move toward a more differentiated positioning around predictive analytics, decision intelligence or a particular industry application. Positioning therefore becomes less of a static statement and more of a continuous strategic discipline.

5. The New Brand Positioning: From Awareness to Recommendation Eligibility

For years, marketers have focused heavily on brand awareness. The assumption was that if buyers knew about a company, it had a better chance of making the consideration shortlist.

In an AI-mediated buying journey, however, there are a few additional hurdles that come first: 

Will AI put us on the list at all?

Imagine a buyer asking an AI assistant to recommend B2B marketing firms that specialize in helping Canadian technology companies expand internationally. A company may have excellent capabilities in this area, but if its online presence primarily describes it as a general marketing agency, the AI may have little reason to associate it with that specific need/pain point.

And even if the company is included, another question follows: 

What attributes will the AI associate with the company?

Will it describe the company as a generalist agency, a B2B specialist, a lead-generation provider, a branding consultancy or an expert in international market expansion?

That makes positioning increasingly connected to search visibility, content, product information, reputation, reviews, structured information and third-party validation. A company’s positioning is no longer communicated exclusively through what it says about itself. It is also shaped by the broader external body of information that exists about it.

AI is increasingly taking a dominant role in discovery, research and recommendation. So much so that traditional SEO loses its power by the new phenomenon of zero-click searches. For this reason, companies need to think beyond brand awareness and messaging. They need to think about discoverability, categorization visibility, evidence and recommendation eligibility.

As a matter of fact, the shift is already making headways. A 2026 study published in Marketing Science analyzed ChatGPT referrals across 973 e-commerce websites and found that traffic from AI search engine platforms is emerging as a distinct digital channel, particularly for more complex products. The researchers note that it remains relatively small compared with established channels, suggesting that at this point, AI-mediated discovery is still emerging rather than fully replacing traditional search.

The positioning strategist of the future will therefore be more than a brand storyteller. They will increasingly help companies define the problem-spaces they want to own, establish the categories they want to be associated with, create coherent information across their digital ecosystem and orchestrate the evidence that supports their position.

The fundamental question is evolving from “How do we want customers to perceive us?” to “How do we want customers, and the AI systems influencing their decisions, to understand us?” That is the new role of brand positioning in the age of AI.

• • Differentiation in brand positioning needs to become machine-friendly. Companies need to communicate clearly who they serve, what problems they solve, where they specialize and how they differ from alternative solutions.
  • Companies need to own a problem-space, not just a message. In AI-mediated discovery, the goal is to become linked with the specific pain points and challenges that B2B buyers ask AI search engine platforms to help them solve.
  • Evidence is becoming part of positioning. Customer results, case studies, reviews, original research, expert validation and third-party coverage can make a company’s positioning more credible and easier to substantiate.
  • Positioning needs to become adaptive. As competitors, technologies and customer needs evolve more quickly, positioning should be continuously reviewed rather than treated as a static brand document.
  • Brand awareness is increasingly giving way to recommendation eligibility. Companies need to be understood by AI systems as relevant solutions before they can appear in an AI-generated shortlist.

Ultimately, the future of brand positioning is about making a company’s strategic identity clear and credible enough to be discovered, understood and recommended by both people and AI machines.