The Rise of AI in Product Recommendations: Are We Witnessing SEO 2.0?

Artificial intelligence is rapidly becoming a go-to source for online searches, often reminiscent of how we once relied on Google. However, there’s a burgeoning trend in the realm of AI product recommendations that is gaining traction without much discussion: the optimization of large language models (LLMs).

Recently, while exploring product suggestions through ChatGPT, I noticed an intriguing pattern: the recommendations have become surprisingly consistent. This consistency struck me as odd, especially considering how diverse Google’s search results used to be before SEO practices started to dominate the landscape. It appears we might be heading down a similar path with AI, yet this transformation is largely flying under the radar.

A friend of mine, who works in the marketing department of a well-established corporation, disclosed that their team has engaged an LLM optimization service. This service is designed to ensure that their products are prominently mentioned when users inquire about recommendations in their specific category. It seems there’s an emerging industry dedicated to influencing AI’s output, and that raises some significant questions.

The noticeable uptick in recommendations for established brands recently aligns with this trend. In the past, results appeared more organic and varied, but now, they seem more tailored towards larger companies. This rapid shift in the recommendation landscape is particularly striking; unlike Google, which took years to evolve in its search results, the optimization of AI is unfolding at a much faster pace—often before many users even recognize the change.

Are others experiencing this phenomenon? Is there a method to discern the authenticity of these AI recommendations? As the potential for engineered visibility within AI recommendations grows, it’s crucial that we engage in this conversation. We may be on the cusp of a transformation that mirrors the challenges of traditional search engine optimization, where the outcomes can be manipulated.

Update – April 22nd: This discussion has gained momentum beyond my expectations, and I’ve received numerous inquiries seeking further clarification. While I wish I could respond to each of you individually, I want to address common questions here. Unfortunately, I can’t disclose the name of my friend’s corporation, but he did provide me with the name of the LLM optimization service they utilize. Their website outlines various strategies designed to achieve optimized visibility. I must clarify, though, that I am not an expert in this domain, and I cannot fully validate the methods employed for LLM optimization at this time. However, the impact