The evidence seems clear. Of all the ways generative AI is reshaping online marketing, one of the biggest growth opportunities for smaller brands is in search. With the recent explosion in AI search traffic, startups and smaller brands can challenge the long-standing SEO dominance of their larger rivals. The key is to be proactive and understand how to show up where your audience is looking. This means pivoting to AI before your competitors do.
SMBs Are Benefiting from This New Search Trend
According to data from Adobe, traffic from generative AI tools to US retail sites surged by 1,300% in the 2024 holiday period compared with the same period the year before. Other research shows that AI search tools like ChatGPT and Perplexity are sending more traffic predominantly to companies in the travel, financial, health, and e-commerce sectors.
The best news of all? A study by Search Engine Land shows referral traffic from generative AI increased by 123% specifically to small and medium-sized businesses between September 2024 and February 2025. This is important because many smaller businesses seem to believe that AI search represents a threat when the opposite is true. They can rank for key terms quickly without the same costs or time lag associated with traditional search engine optimisation strategies.
The Results Can Be Almost Instantaneous
As a marketer, I’ve seen businesses benefit from this trend. Despite being relatively small players in their markets, some have started working with AI tools like Microsoft’s CoPilot, OpenAI’s ChatGPT, and Perplexity, and showed up on the first page of results for a couple of key terms within days.
How did they do it? By adapting SEO best practices and searching for recommendations from what other marketers reported having success with. Above all, they sought to optimize their content strategy to make it more appealing to AI search tools, and did so in the following key ways.
Realizing That AI Traffic is Different
AI traffic behaves differently from traditional SEO referral traffic. The Adobe study mentioned above found that AI users stay on sites an average of 8% longer, browse 12% more pages per visit, and have a 23% lower bounce rate. AI users are more engaged.
This makes sense when you realize that people tend to ask AI for recommendations, insights, and company suggestions, not just answers to simple questions. Once we had adjusted our mindset to account for this, it was simple to adapt our approach.
Training AI Search With Company-Specific Data
This is less complicated than it sounds. Essentially, in my company, we compiled a list of all the search terms we wanted to rank for. Then we created a Custom GPT and uploaded relevant brand content—like blog posts, product pages, whitepapers, and FAQs—so the AI could understand our voice and areas of expertise. That way, it became familiar with us and our company. We then started to train it to recognize our content on the topics we wanted to rank for.
Structuring Content to Appeal to AI
AI search tools such as ChatGPT, CoPilot, Gemini, or Perplexity prefer content that provides clear and direct answers to user queries and that is easy to scan.
This means following content best practice to an even greater extent than before, for example:
- Publishing on Free Platforms: Medium, LinkedIn Articles, Substack, Reddit, Quora, and GitHub (for tech startups)
- Providing concise answers first, followed by more in-depth explanations.
- Using plenty of headings, bullet points, and lists, as well as short paragraphs.
- Using FAQ-style responses, which tend to perform particularly well in AI-generated outputs.
- Optimizing for Long-Tail Queries: AI models favor detailed, niche answers
Ensuring Content is Authoritative and Credible
Content needs to be well-referenced and research-based where possible, with quality backlinks. SMBs and start-ups, in particular, should focus on citing credible industry sources and emphasising data-rich case studies, reports, and articles to build trust and authority. All internal and outbound links should be reviewed to ensure they are logical, credible, and provide further context for the topics under discussion.
Prioritizing Original Quality Content Rather Than Recycled Content
Diving deeper into this topic, it seems clear that AI search favors originality and quality in the content it recommends. That means:
- No using gen AI to create blogs or articles without feeding it original data; otherwise, the resulting content will regurgitate existing sources and be penalized in AI search.
- Favoring real-life case studies containing key data points over theoretical use cases.
- Publishing original studies, surveys, and in-depth reports based on subject matter expertise.
It’s Time to Start Optimizing for AI Search
AI search may not yet be as dominant as Google, but it’s growing exponentially. This trend is only likely to continue as more users become comfortable with using AI in this way. The online marketing industry is waking up to the disruptive potential of AI, with SEMrush recently launching the first mainstream AI-specific optimization tool for enterprises to track and grow their brand across AI platforms.
Unlike with Google SEO, however, AI-based search remains a black box in the sense that we marketers don’t yet have a clear list of ranking factors. This is why smaller brands suddenly have the edge, because dominance in traditional SEO is no guarantee of success with AI search.
This could be the biggest online marketing shift in favor of startups for a generation, as the companies that figure out how to make AI recognise and recommend them will have a huge first-mover advantage. To the victor go the spoils, as the saying goes, and the victors of AI search are yet to be determined.