How to Get AI to Recommend Your Business
Published on September 10, 2026
To capture traffic and build trust in the age of generative AI, businesses must shift their content strategy from purely human-centric storytelling to formats that AI systems can crawl, index, and cite. This involves restructuring websites and newsletters to serve as data sources for AI models like ChatGPT, Claude, and Perplexity, ensuring your brand appears as a trusted advisor in automated recommendations.
Key Takeaways
- AI as the New Gatekeeper: Approximately 68% of Google search queries no longer result in a click to a website, as consumers increasingly rely on private AI conversations for research and recommendations.
- Newsletter Repurposing Strategy: Send newsletters to subscribers, then publish the exact same content on your website for indexing, followed by creating a second version with AI-optimized headings and formatting.
- The Value of Originality: AI filters out generic content it could generate itself; businesses must provide proprietary data, personal stories, or specific results to be cited.
- Structural Chunking: Content sections must be self-contained so AI can extract "chunks" of information that directly answer user questions without needing broader context.
- Rapid Results Potential: A consulting firm achieved 72% dominance in its category’s AI recommendations within three weeks by optimizing existing content rather than increasing ad spend.
The Shift from Human-Centric to AI-Centric Content
Most business owners and creators still produce content exclusively for human consumption. This approach relies on story arcs, hooks, and dramatic tension designed to keep readers engaged. YouTube videos are structured with beginnings, middles, and ends, while Instagram posts are crafted to stop the scroll. However, this traditional methodology overlooks a critical shift: machines are now reading content, but they do not consume it like humans do.
AI does not start at the top of an article and read down to the bottom. It does not get excited about a setup or look for a payoff. Instead, AI uses what experts call "fan-out queries." When a user asks a question, the AI automatically generates and executes dozens of related searches beyond the original prompt. For example, someone researching a competitor might receive market analysis, pricing data, and analytics they never explicitly requested because the AI inferred a broader intent.
This behavior mirrors the transition from the Yellow Pages to Google. Businesses that once named themselves “AAA Locksmith” to land first in the phone book had to adapt when consumers moved online. Some adapted and thrived; others disappeared. Today, a similar split is occurring with AI. Roughly 68% of Google search queries no longer result in a click to a website. Consumers are having private conversations with AI tools instead of opening dozens of browser tabs to research vacations, compare prices, or evaluate service providers.
AI has become the "trusted friend" and "trusted advisor." When planning a three-day road trip, the AI already knows the user’s food preferences, children's ages, and budget. The recommendations it returns are often the starting point and sometimes the endpoint of the decision-making process. Businesses that do not appear in these recommendations face a real problem.
Building the Foundation for AI Visibility
Getting your business surfaced by AI starts with how you manage your newsletter and website content. Most newsletters die after hitting the inbox, but this asset can be turned into an AI-friendly resource through a specific two-step process.
First, once the initial newsletter issue has been sent and performance proven, publish the exact same newsletter on your business website. This allows AI to find, crawl, and index the content. Second, create a second version of that newsletter specifically structured for AI consumption. This version should feature different headings, keywords, and formatting to optimize it for machine reading. These two versions address two different audiences simultaneously while living within the same domain.
Case Study: The Consulting Firm’s Rapid Rise
A consulting company was losing to established competitors because they could not outspend them on ads. As noted by industry expert Liron Segev, ads are essentially renting attention; the moment spending stops, the attention disappears. Instead of continuing to rent attention, the firm analyzed its newsletter archive and identified the highest-performing content based on subscriber engagement.
The team repurposed this content for the website using AI-optimized formatting. They also created fresh content from the same source material, structured specifically for AI consumption. Within three weeks, the consulting firm owned 72% of its category in AI recommendations. It outstripped competitors who had been publishing content for years and had much larger online followings. The difference was not volume or history, but an understanding of who the new audience (AI) was and how to reach them.
Developing Content That AI Cites and Recommends
AI prioritizes content that offers something it cannot generate itself. When searching for an answer, AI has billions of pages to choose from and uses a filtering process to decide which content to surface. The first filter is originality. AI recognizes its own output; if a business publishes content that AI could have generated itself, there is no additional value to cite.
Writing to Share Unique Value
A simple test for your content is this: if someone can swap your company name in an article for a competitor's name and the content still makes sense, AI has no reason to favor it. That content is generic and adds nothing that the AI doesn't already have. What AI wants is content it cannot produce on its own, such as personal stories, proprietary data, specific results, and firsthand experience.
For example, a financial advisor writing “10 Tips for Retirement Planning” competes with millions of identical articles. However, a financial advisor writing about what happened when a specific client restructured their portfolio during a market downturn provides something unique. AI can help create content, but the output needs personal enrichment. A generic prompt asking AI to write “seven things to do in Anaheim” produces generic content that AI will never cite. Content built using AI as a drafting tool but enriched with personal stories, specific data points, and firsthand experience gives AI something it cannot generate on its own.
Similarly, a conference organizer writing about what attendees should do before an event can create unique value by referencing specific experiences from past events, mentioning how many people attended a particular dinner, or describing a specific restaurant discovery from the previous year. AI’s predictive algorithms recognize these personal details as a source of added value.
Structuring Content for AI Chunking
AI does not read an article from top to bottom. It uses a process called "chunking," which is the extraction of a specific, self-contained piece of content from a larger article that directly answers a user's question. That chunk is pulled out and returned to the user, often with a citation linking to the source.
This changes how content should be structured. Each section of your content needs to stand on its own, making sense without the paragraphs that come before or after it. If AI can extract a two- or three-sentence answer from a section, that section is effectively optimized for AI citation. By ensuring your content is modular and self-contained, you increase the likelihood that AI will select your business as a trusted source for recommendations.