Gushwork raises $9M, betting on AI search as a customer acquisition channel

The digital marketing world has revolved around one axis for decades — Google's search results. Entire industries grew up on the skill of landing in the top ten results, and budgets for SEO and contextual advertising were measured in billions. But what if this familiar order is already cracking at the seams? Startup Gushwork, which just raised $9 million in a seed round led by SIG and Lightspeed funds, claims it sees the first outlines of a new reality — and is building a business on the fact that AI search engines like ChatGPT are becoming a full-fledged customer acquisition channel.

Gushwork's idea sounds simultaneously simple and provocative. The company noticed that more and more users are turning to language models for recommendations instead of traditional search engines. Rather than typing a query into Google's search bar and scrolling through links, people ask ChatGPT, Perplexity, or Gemini — and get a ready-made answer with specific recommendations. For business, this means a fundamentally new question: how do you ensure that an AI assistant mentions your product when a user asks about solving their problem? Gushwork is fixing early, but quite tangible results — part of their client base came through exactly such AI recommendations.

To understand the scale of the shift, it's worth recalling the context. Over the past two years, AI search engines have gone from experimental toys to everyday tools for hundreds of millions of people. According to various analytical agencies, the share of search queries that begin in a language model interface rather than a classic search engine is steadily growing. OpenAI integrated web search capabilities into ChatGPT, Google responded with AI Overviews in its results, and Perplexity is built entirely as an AI-first search system. All this creates a new ecosystem in which link ranking algorithms give way to a completely different logic — the logic of answer generation.

This is where the main intrigue lies. Classic SEO relies on understandable, if constantly changing, rules: keywords, backlinks, page load speed, content structure. Optimization for AI search — territory where there are almost no rules yet. Language models form answers based on training data, dialogue context, and increasingly, current information from the internet. How exactly a model decides which product to recommend — a question to which there is no transparent answer even from the developers of these models. Gushwork apparently is trying to find patterns in this black box and turn them into a reproducible strategy for business.

The participation of Lightspeed and SIG in the round is a signal that should be taken seriously. Both funds are known for early bets on transformational trends, and their willingness to invest $9 million at seed stage suggests that investors see AI lead generation not as a niche story, but as a potentially scalable market. If AI search engines really capture a significant share of commercial queries from Google, we're talking about a redistribution of advertising budgets measured in tens of billions of dollars annually.

That said, skepticism is quite appropriate here. Early results are not yet a sustainable trend. It's still unclear how stable AI recommendations are and whether they can be systematically influenced without manipulations that sooner or later will provoke a response from the developers of these models. OpenAI and Google are unlikely to calmly watch as third parties learn to "hack" their recommendation algorithms. Moreover, serious questions arise about transparency: if an AI assistant recommends a product, the user should understand whether it's an organic recommendation or a paid one. Regulators, already concerned about native advertising in traditional search, will surely turn their attention to this sphere as well.

Nevertheless, Gushwork has hit a nerve of the times. Business always goes where customers are, and customers are increasingly starting their path to purchase with a conversation with AI. A startup that first learns to systematically work with this channel will gain a colossal advantage. Nine million dollars — a modest sum by industry standards, but enough to test the hypothesis and, if it's confirmed, attract the next round on completely different terms. We are witnessing the birth of a new market, and for now it looks like a wild west — without maps, without rules, and with enormous opportunities for those who dare to enter first.