Product discovery is being reshaped in real time, and AI is taking control. Platforms like ChatGPT, Gemini, and Perplexity are now quietly curating which brands enter the conversation and which don’t.
Here’s the risk: small changes in phrasing can erase your brand from AI results entirely. Swap “best CRM for sales” with “top sales tool” and you disappear.
With over 70% of B2B searches now answered by AI, brands are losing visibility without warning, metrics, or recourse.
This is prompt bias—driven by how AI interprets language and ranks relevance—an invisible filter deciding who’s seen and who’s forgotten. If you’re not adapting, you’re already behind. Visibility isn’t earned. It’s engineered.
What Is Prompt Bias, and Why Should Marketers Care?
Prompt bias is the phenomenon where slight changes in phrasing dramatically affect which brands AI platforms mention, recommend, or ignore.
Unlike search engines that retrieve indexed pages, AI models generate answers on the fly—based on training data, linguistic probabilities, and how the prompt is worded.
That means two users with the same intent may get entirely different brand results just because they asked the question differently.
A recent BrandRadar study found that up to 48% of brand mentions fluctuate based solely on prompt variation (Prompt Bias Index Report, Q1 2025).
Takeaway: If your brand isn’t discoverable across a range of phrasing styles, you’re invisible to entire segments. AI isn’t ignoring you; it just doesn’t recognize your brand in the language your buyers use.
Inside the Data: A Real-World Skincare Case Study
To explore the impact of prompt bias in the wild, BrandRadar analyzed 90+ AI-generated responses across ChatGPT, Gemini, and Perplexity.
We used 10 different prompts that all asked about skincare products, including:
- “Best skincare for oily skin”
- “Affordable skincare that works”
- “Dermatologist-recommended face wash”
We scanned each model's answers for brand mentions, frequency, position, and consistency.
Key Findings:
1. Prompt-Robust Brands
Brands like CeraVe and La Roche-Posay showed up in nearly every query variant across all models, regardless of tone or emphasis.
- PSI Score: 0.12 (low)
2. Prompt-Sensitive Brands
Brands such as Kiehl’s and Paula’s Choice appeared in premium-focused prompts but dropped over 60% in price- or expert-led variants.
- PSI Score: 0.62 (high)
3. Middle Performers
The Ordinary maintained visibility in value-focused queries but struggled when the tone was clinical or vague.
- PSI Score: 0.38 (moderate)
Result: On average, only 2 (CeraVe and La Roche-Posay) out of 10 brands remained consistently visible across all prompt styles.
What Is the Prompt Sensitivity Index (PSI)?
To measure volatility, BrandRadar developed the Prompt Sensitivity Index (PSI). It quantifies how often a brand appears across semantically similar prompts.
- Low PSI (e.g., CeraVe): Consistent brand recognition across styles
- High PSI (e.g., Kiehl’s): Heavy fluctuation depending on how the prompt is worded
Takeaway: Tracking your PSI over time helps reveal which kinds of prompt phrasing your brand is underperforming in and how to fix it.
Why One Word Can Make or Break Visibility
Let’s compare two nearly identical user prompts:
- “Best face wash for acne”
- “Affordable cleansers recommended by dermatologists for acne-prone skin”
Both suggest the same intent. But the AI-generated outputs? Entirely different:
- Query 1: CeraVe and La Roche-Posay were dominant.
- Query 2: Lower-cost clinical brands surfaced. CeraVe dropped below the fold.
In fact, brand rankings shifted by as much as 80% just from tweaking a few adjectives like "affordable" or "recommended."
Why Brands Must Act Now
By 2026, AI-generated answers are expected to influence over 40% of all e-commerce discovery decisions. This isn’t a quirk. It’s a feature of how large language models work.
They generate answers based on language patterns, not structured indices. If your brand isn’t associated with the right phrasing, you simply won’t be part of the conversation.
And yet, despite the rising importance of AI visibility, only 27% of enterprise marketers have a strategy for monitoring brand mentions across LLMs (source: HubSpot AI Trends Report, 2025).
The brands that get ahead of this now will own disproportionate mindshare in the AI-first world.
How to Build Prompt-Robust Visibility
1. Audit Your Brand's AI Presence
Use a tool like BrandRadar to analyze where and how often your brand shows up in AI-generated responses.
Pro Tip: Try 10 natural variations of your core category prompts (e.g., “best [product] for [need]”) across different platforms. Log which models surface your brand—and which don’t.
BrandRadar is the one-stop AI tracker platform with a built-in multimodal system that allows you to do that seamlessly.
2. Map Out Natural Language Prompts
Study how users actually phrase their questions. Reddit threads, product reviews, and voice search data are gold mines.
3. Diversify and Structure Your Content
Create brand copy that works across tones: clinical, casual, value-focused, and expert-driven. Use structured data and consistent messaging.
4. Track and Improve Your PSI
Use the Prompt Sensitivity Index to identify weak spots and growth opportunities. Brands with low PSI scores will dominate multi-context discovery over time.
Final Thought: In the Age of AI, Visibility Is Prompt-Dependent
Prompt bias is not merely an incident; it is the primary challenge that marketers confront in the AI era.
That means if you’re not managing how AI interprets your brand across prompt variations, you’re not just missing clicks—you’re missing relevance. But you can change the narratives today with BrandRadar’s PSI.
BrandRadar’s Prompt Sensitivity Index doesn’t just show you where you stand—it shows you where you’re slipping. Which prompts bury you? Which ones boost you?
Find out fast, fix it faster, and take control before AI writes you out of the conversation. Request a BrandRadar demo or onboard now to get started.
