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AI is already replacing traditional search. In a survey of 12,000 consumers, the Harvard Business Review (HBR) found that 58% had used AI to search for products and services in 2025, compared with 25% in 2023. The consumers using AI search tend to be younger, wealthier, and better educated than average.
Bigger changes are coming as agentic AI begins to change how people purchase products, not just find them. To adapt, brands need to learn how to use agentic AI, how to convince customers to use in-house “brand agents,” and finally how to convince third-party AI agents (from ChatGPT and others) to choose their brand’s products and services.
In this article, we will examine strategies to maintain brand visibility in the age of AI.
In AI search, “share of model” (SOM) measures how often brands are mentioned in the results produced by different large language models (LLM), according to the Harvard Business Review. SOM tries to capture brand mention rates, average position, and brand perception. There is still no single, widely accepted method for measuring SOM, which can vary both by LLM and by the prompts used.
SOM is an evolution of “share of search” (SOS), which measures customer demand based on the number of queries for a particular brand. In the age of search engine dominance, SOS was a useful way to measure customer demand and tailor search engine optimization (SEO) efforts.
But there is a critical difference in brand visibility when comparing traditional search results and LLM (or AI) search. As the HBR authors write: “Failure to register on an LLM means a brand doesn’t appear at all before consumers. On ChatGPT, unlike Google, there is no ‘page two.’” (Emphasis added.)
The single best way to improve brand visibility in LLM results is to state a problem and solve it. According to the HBR: “LLMs are not optimizing for attention, they are optimizing for resolution. Identifying the ‘job to be done’ thus becomes the number one priority for brand leaders if they want to score big on SOM.” There are two elements driving SOM – solving problems and demonstrating authority.
Because LLMs are looking for “resolution,” rather than keywords, brands need to identify specific user needs, use cases, and pain points – and then offer specific solutions for each.
Instead of offering “the best running shoes,” for example, a brand is better served by offering “running shoes with a carbon fiber midsole for improved long distance training.” The second description offers a specific use case and “resolution.”
LLMs also look for authority – signs that your brand has the expertise to answer questions and solve problems.
In a 2026 Harvard Business Review article, “Preparing Your Brand for Agentic AI,” the authors argue that AI is changing not just how consumers find products and services, but how they buy them.
The authors write, “Every major AI company is developing agents in anticipation of mainstream adoption.” As one example, OpenAI is partnering with payment platforms like PayPal and retailers like Walmart “to facilitate purchasing within ChatGPT.”
To maintain brand visibility and avoid becoming dependent on third party agents (which the authors call “consumer agents”), brands should consider developing in-house AI agents (which the authors call “brand agents”).
Brands should begin by asking under what circumstances their customers are willing to interact with an AI agent. The answer often depends on context. People are most likely to accept an AI agent for “low stakes” decisions like restocking household supplies.
The calculation changes when the stakes are higher (such as healthcare or financial decisions), involve personal connections (such as choosing gifts or personal items), or when human interaction is part of the buying experience (such as shopping for luxury goods).
In these higher stakes situations, brands need to adjust, as we discuss below.
The first challenge is to convince customers to use in-house brand agents, rather than general purpose consumer agents like ChatGPT, which may direct purchases to competing brands and products. Consumers tend to trust consumer agents as being “on their side,” but brand agents have advantages to leverage:
Since some customers will always prefer using consumer agents, the next challenge is to improve the odds those agents select your brand.
The brand began prompting the leading LLMs regularly and compiling their responses. It then began to update websites, advertising, and other content until the LLMs started to reflect correct product information and brand messaging. (We at 10 Plus Brand have been creating and updating SOM content for our clients to ensure their brands lead AI search. Contact us for more information.)
AI has already transformed search and may soon do the same for purchasing. To maintain brand visibility, organizations must update their strategies.
👉 contact Joanne’s team at AIXD.world to begin building your brand’s AI presence before your competitors do.
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Joanne Z. Tan is the Founder & CEO of 10 Plus Brand, Inc. Joanne is a globally recognized brand strategist, thought leadership coach, content & branding expert, and speaker. She helps founders, CEOs, executives, board members, leaders, entrepreneurs, and organizations decode their Brand DNA, elevate merely successful businesses to become powerful brands in the AI age. Joanne was trained in law and business, and had a liberal arts education from Brandeis University before earning a law degree. Her coaching emphasizes comprehensive strategies, business modeling, multidisciplinary thought leadership and high authority content creation, brand building, culture, GTM, user experience design, AI native brand architecture™, and AIXD™ (AI experience design). A former journalist, award-winning photographic artist, Joanne is also a poet, writer, and an avid wilderness backpacker.
© Joanne Z. Tan, 2026. All rights reserved.