Applied Materials AI Brand Visibility (December, 2025)

ChatGPT Visibility Report

AI Brand Visibility for Applied Materials (appliedmaterials.com) reflects a low but measurable level of exposure in AI results, where wafer fabrication process optimization is the strongest entity with a Visibility Index of 62, typical rank around 1.0, and appearing in roughly 75% of AI replies. Across all 5 entities linked to Applied Materials, the average Visibility Index is about 45, with solid LLM confidence at roughly 76% and moderate brand discovery around 50%. For the top entity wafer fabrication process optimization, AI responses show very strong confidence at about 100% and very strong brand match near 100%, indicating below target visibility quality for the strongest touchpoint. Another key entity, thin film deposition techniques, holds a below target Visibility Index of 62 with solid discovery (about 75% of responses) and very strong confidence near 100%. In addition, semiconductor manufacturing equipment technology shows below target visibility, combining a Visibility Index of 60 with solid discovery near 75% and very strong confidence near 94%. Taken together, these results show that Applied Materials is still early in its AI visibility journey and will benefit from focused initiatives to increase recognition in model responses.

RankLens is one of the most accurate ways to measure AI Brand Visibility in large language models (LLMs). Backed by academic studies and patent-pending mathematical foundations, run a FREE report for your business and start improving your AI Visibility.

Create a Free AI Visibility Report

Company Name: Applied Materials

Website: appliedmaterials.com

Stock Symbol: AMAT

---

About:

Relevant Entities

Semiconductor manufacturing equipment technology Advanced material engineering solutions Wafer fabrication process optimization Thin film deposition techniques Precision metrology and inspection See More Entities

Edit & Schedule Reports

RankLens measures how visible a brand is inside large language models (LLMs). It runs controlled sampling of AI responses, tracks where and how often your brand is mentioned, and normalizes the results into a Visibility Index so you can benchmark and track AI brand presence over time. RankLens is based on Entity-Conditioned Probing + Resampling principles.

Rank (Avg)

Average ranking position of the entity across all sampling iterations (lower is better).

LLM Confidence

The normalized confidence score the LLM reports for its answers including your brand.

Brand Appearance (SoV)

How many times the brand or website appears in the sampled responses out of total iterations. Share of Voice (SoV): % of all responses the AI assigned to a brand compared to all other brands.

Brand Discovery

The probability (as a percentage) that the brand appears in an LLM response for the tested entities.

Brand Target

A normalized measure based on confidence interval width showing how tightly focused the LLM responses are on the brand.

Brand Match

Accuracy of matching the results to the intended brand name or website.

Visibility Index

An overall score out of 100 combining probability, confidence, and targeting to summarize AI brand visibility.

Explore Other AI Brand Visibility Reports

---

---

---

---

Contact Us if you own this business or if you would like to report a data issue.