AI is supposed to help people discover what matters. If it keeps reinforcing yesterday’s sports hierarchy, marketers investing in women’s sports could find themselves fighting the algorithm instead of reaching the audience.
Women’s sports have reached an inflection point that marketers have been waiting years to see. Stadiums are selling out. Television audiences continue setting records. Sponsorship values are climbing. The WNBA has become one of the hottest properties in professional sports, women’s soccer continues to expand globally, and next year’s FIFA Women’s World Cup promises to attract another generation of fans and commercial partners. According to research from McKinsey & Company, revenues across women’s sports grew 4.5 times faster than men’s sports between 2022 and 2024, creating what the consultancy describes as a $2.5 billion market opportunity that remains significantly under-monetized.
For marketers, the direction of travel seems obvious. Consumer demand is growing, audiences are becoming younger and more diverse, and brands increasingly see women’s sports as an opportunity to build long-term cultural relevance rather than simply buying media inventory.
The problem is that discovery is no longer driven entirely by consumers, but increasingly by algorithms.
That should concern every marketer investing in women’s sports because Google is no longer simply organizing the internet. Through Search, AI Overviews, recommendation systems and the broader ecosystem of machine learning that powers content discovery, Google has become one of the world’s largest gatekeepers of attention. If those systems consistently inherit decades of historical imbalance in sports coverage, then marketers are no longer competing solely against rival brands. They are competing against the assumptions embedded within the data itself.
Statistical Bias
For decades, men’s sports dominated newspaper front pages, television broadcasts, search traffic, backlinks, Wikipedia entries, video libraries and digital publishing. Every one of those signals has become part of the data environment that modern search engines and AI systems use to determine authority, relevance and confidence. When someone searches for a sport without specifying gender, the default answer frequently leans toward the men’s competition because history has produced more content, more links and more engagement around it.
2026 Reality vs 2016 Reality
Academic researchers have already begun documenting this phenomenon inside AI systems. One recent study examining large language models found that when users asked about Olympic events without specifying gender, models routinely defaulted to men’s competitions, effectively treating men’s sport as the implicit standard while women’s sport required additional clarification. The researchers concluded that historical training data continues to produce systematic representational bias whenever gender is ambiguous.
Search has become one of marketing’s most important discovery mechanisms, while AI-generated answers are rapidly replacing the traditional list of blue links that once allowed consumers to compare multiple sources. If the underlying systems continue favoring historical authority, then the visibility gap between men’s and women’s sports risks becoming self-reinforcing. More visibility generates more engagement. More engagement generates more links, citations and coverage. Those signals then reinforce future visibility.
That is why marketers should be paying much closer attention as they prepare for next year’s Women’s World Cup. The commercial opportunity surrounding the tournament will be enormous, yet the competition will not begin at kickoff. It will begin months earlier as brands compete to become part of AI-generated recommendations, search results, editorial coverage and fan conversations.
If Google’s systems continue leaning toward historical authority rather than emerging cultural momentum, marketers investing in women’s football could find themselves receiving less discoverability than audience demand actually warrants. The result would not necessarily be lower-quality campaigns. It would be lower algorithmic visibility.
The irony is that consumer behavior is moving in exactly the opposite direction. McKinsey’s research found that roughly four out of five American sports fans now follow women’s sports in some capacity, while most of that audience has emerged within the past five years. Even more significantly, the vast majority of women’s sports fans are also fans of men’s sports, suggesting brands are not choosing between two separate audiences but participating in one increasingly interconnected sports ecosystem.
The WNBA illustrates this shift perfectly. A league that was once treated as a niche sponsorship property has rapidly become a cultural conversation, producing record television audiences, dramatic sponsorship growth and athlete-driven communities that increasingly shape fashion, entertainment and social media. Brands have recognised that these athletes represent far more than media impressions because they carry cultural credibility with younger audiences who expect companies to invest where culture is actually moving rather than where it has historically been.
Algorithms, however, often struggle with cultural momentum because they are trained on accumulated evidence rather than emerging relevance.
A Dangerous Disconnect
Marketers increasingly make investment decisions based on where audiences are going, while search engines often determine visibility based on where audiences have been.
The distinction may sound subtle, but it has profound implications for brand strategy. If AI becomes the primary interface through which consumers discover sporting events, athletes and sponsorships, then algorithmic representation becomes a marketing variable rather than merely a technical one. Visibility will no longer depend solely on media budgets or creative excellence. It will also depend on whether AI systems recognise the commercial significance of women’s sports as quickly as consumers already have.
Google is hardly alone in facing this challenge. Every AI platform trained on historical internet data inherits similar structural tendencies, and researchers across multiple disciplines have shown that algorithmic systems often reproduce existing patterns of representation unless they are intentionally designed to counterbalance them.
That means the real conversation should not be about blaming Google. It should be about recognizing that search has become infrastructure for marketing, and infrastructure shapes markets whether it intends to or not.
The brands preparing for the Women’s World Cup already understand that women’s sports are no longer an emerging category. They are a growth category. The question is whether the platforms responsible for helping consumers discover those events understand it as well.
For marketers, that distinction could determine whether the next decade of women’s sports marketing reaches its full commercial potential or continues to compete against an algorithm that still believes the biggest stories in sport belong almost exclusively to men.