Communications firm 5W AI Communications recently released its Sports Nutrition & Protein AI Visibility Index 2026, examining which sports nutrition brands are recommended by ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews when consumers use AI to research products.
The analysis covered more than 60 unique consumer-style prompts across six categories: whey/isolate, plant-based protein, ready-to-drink protein, pre-workout, creatine and recovery/clean-label performance. Prompts ranged from broad questions such as “best protein powder” to more specific searches focused on attributes like “clean,” “transparent” or “no artificial ingredients.” Each prompt was run five times on each AI platform to account for variability in responses.
“The biggest takeaway is that the protein aisle is no longer decided by one answer, it’s decided by the qualifier attached to the question,” said Ronn Torossian, founder of 5W AI Communications.
AI visibility isn’t the same as market share
In this context, a qualifier is a word or phrase that narrows what a consumer is looking for. The analysis found that adding criteria such as “clean,” “transparent” or “no artificial ingredients” can change which brands AI recommends.
5W estimated that Optimum Nutrition accounted for roughly 14% of citation share across the tracked queries, making it the most-cited brand overall. It also emerged as the default recommendation for the broad “best protein powder” query. However, recommendations shifted toward brands including Transparent Labs and Legion when consumers added more specifics to their queries, illustrating how smaller brands can outperform larger brands when consumers add specific qualifiers.
“That happened consistently enough across our 60+ tracked prompts to be a structural pattern, not a one-off,” Torossian said. “For brands, that means market share and AI visibility are no longer the same metric, and treating them as interchangeable is the mistake we see most often.”
“The moment someone adds a qualifier like ‘clean,’ ‘grass-fed’ or ‘no artificial ingredients,’ the conversation changes,” said HALO Comms co-founder Derek De Vette. “AI isn’t defaulting to the biggest household names anymore—it’s looking for evidence that a brand actually fits what the person asked for.”
De Vette said this creates an opportunity for brands that have invested in transparency.
“If you’ve published your formula, explained your ingredient choices, shared third-party testing and earned credible coverage, you’ve given the model something it can point to. In many cases, that’s enough for a smaller brand to appear alongside—or even ahead of—a much larger competitor,” he said.
Format matters too
Reflecting on the findings, Torossian told NutraIngredients that the biggest surprise was how product format appeared to create a separate category, largely disconnected from a brand’s reputation in other formats.
“What surprised us was that ‘best protein shake’ doesn’t route to protein powder brands at all, it routes almost entirely to ready-to-drink players like Premier Protein and Fairlife Core Power,” he said.
Dymatize and Ascent, for example, can perform strongly in whey and isolate comparisons but be largely absent from “best protein shake” recommendations, Torossian said. In other words, the AI response can change not only based on what attributes a consumer wants but also on the format they are seeking.
How reliable is AI visibility measurement?
While the findings suggest AI recommendations can create new winners and losers in sports nutrition, experts caution that measuring this emerging visibility remains an imperfect science.
“Most methodologies advertised as tracking AI citation share are highly unreliable and inconsistent in measured outcomes, both internally…and externally,” said Jordan Brannon, COO & President, Coalition Technologies. “Our testing has found that most amount to being slightly better than a coin flip.”
Rather than relying on a single AI rank-tracking tool, Brannon said Coalition has begun using multiple approaches alongside manual testing.
5W likewise describes its citation-share figures as estimates based on the frequency of brand mentions across tracked prompts, noting that the percentages should be viewed as directional measures of relative visibility rather than precise market measurements.
Is AI a major discovery channel yet?
Brannon also cautioned against assuming AI has already become a dominant channel for product discovery.
“‘Traditional channels,’ now infused with AI, seem to be winning product discovery still,” he said, pointing to Google and Meta as continuing to dominate product and brand discovery for supplement companies.
For those exploring generative search, Brannon recommends that brands consider Google’s broader AI ecosystem, which include traditional organic and paid search, Gemini, Google AI Overviews and AI Mode. He also suggested brands determine which AI models and chatbots are most relevant to their particular category.
What makes a brand visible?
As AI becomes another layer in the discovery process of sports nutrition products, the signals that influence brand visibility may be changing, De Vette said.
He pointed to earned media, including news coverage, interviews, expert commentary and independent reviews, as an important form of third-party validation.
“Your website explains who you think you are. But earned coverage, expert commentary and independent reviews tell AI how the rest of the world sees you—and that’s a very different signal,” De Vette said.
AI systems are increasingly drawing from specialist publishers, expert reviews, forums and other trusted sources when generating responses, he said. In health and nutrition, that makes corroboration particularly important.
“Credibility matters so they’re naturally looking for corroboration rather than simply repeating brand messaging,” he said.
De Vette said AI may be rewarding brands that invested in transparency and scientific communication long before they recognized the potential discoverability benefits. Consistently publishing useful information, earning credible third-party coverage and making expertise easy to find can provide AI systems with stronger signals when generating recommendations.
“That’s not something you fix with a quick optimization project—it’s something you build over time,” he said.
What should brands do?
For brands looking to improve their visibility, the experts emphasized a combination of transparency, credible third-party validation and a better understanding of where consumers are actually using AI.
Torossian said brands should publish structured, verifiable information—including full formulas, dosing rationale and third-party testing—and determine which specific attributes or qualifiers they want to own.
Brannon, meanwhile, said brands shouldn’t abandon traditional search in pursuit of AI visibility and should determine which AI experiences matter most in their category.
De Vette recommended making claims easy to substantiate, prioritizing credible earned coverage and ensuring that a brand’s website provides enough information to establish trust when consumers arrive from an AI recommendation.
“Make it easy to verify what you’re saying,” De Vette said. “Publish complete formulas, ingredient sourcing, third-party testing and the rationale behind your dosing.”
He added that a credible mention in a respected trade publication or from a trusted expert can go father than a large volume of generic press coverage.
AI isn’t Google…yet
The 5W analysis suggests that AI-generated recommendations may be creating a more fragmented competitive landscape for sports nutrition brands, where visibility depends not only on brand recognition, but also on the consumer’s specific question, product format and AI platform.
At the same time, the experts caution that AI has not displaced traditional discovery channels and that the tools used to measure AI visibility are still evolving.
For brands, however, the underlying lesson may be less about chasing a particular AI ranking and more about building the information and credibility that can support visibility across channels.
As De Vette put it, “the same things that earn trust with these models tend to earn trust with people, too.”
