# AI Brand Visibility Snapshot — GCC | Foreground Digital > Weekly AIVS measurements for 50 GCC brands across 5 industries on 4 LLMs. Free, CC-BY-4.0 licensed primary dataset on AI brand visibility in the Gulf region. Source: https://foreground.agency/data/ai-brand-visibility/ --- [Home](https://foreground.agency/) / Data — AI Brand Visibility # AI Brand Visibility Snapshot — GCC. Weekly measurements of how often LLMs mention 50 GCC brands across 5 industries. Open data, CC-BY-4.0. The first public dataset of AI brand visibility for the Gulf region. [Download dataset ↓](#download) [Methodology](#methodology) [How to cite](#cite) Brands tracked 50 Industries 5 LLMs measured 4 Claude · GPT · Gemini · DeepSeek Update cadence Weekly Mondays, Dubai time Industries covered ## Where we look. 10 brands per industry. Selected from public business directories, ad spend signals, and brand-name searches in each market. - Real estate brokers — Dubai 10 brands CSV → - Digital marketing agencies — Dubai 10 brands CSV → - Real estate portals — UAE 10 brands CSV → - WhatsApp / CRM platforms — global 10 brands CSV → - Document verification SaaS — UAE 10 brands CSV → Methodology ## How AIVS is calculated. For each brand we fire 8 prompts across 4 LLMs — 32 calls per brand per snapshot week. Prompts are grouped: - 3 industry-level open-ended — "Best [industry] in [city]?" Did the LLM volunteer the brand? - 3 niche-level open-ended — "Best [specific subcategory] in [city]?" Tighter — separates broad presence from real authority. - 2 brand-named echoes — "Tell me about [brand]" Does the LLM know who the brand is when asked directly? AIVS = 0.5 · (industry_mentions / 12) + 0.3 · (niche_mentions / 12) + 0.2 · (echo_mentions / 8) Grades: A ≥ 0.70 B 0.50–0.69 C 0.30–0.49 D 0.10–0.29 F < 0.10 Methodology v1.5 — locked 2026-05-08. Earlier weeks (v1.0, 5-prompt) are flagged in the dataset and not directly comparable to v1.5+ scores. Download ## Open data, CC-BY-4.0. Use it, cite it, build on it. Attribution required. [Latest snapshot — CSV All brands, all engines, current week ↓ CSV](https://foreground.agency/data/ai-brand-visibility/latest.csv) [Latest snapshot — JSON Same data, JSON structure with co-citations ↓ JSON](https://foreground.agency/data/ai-brand-visibility/latest.json) [Full history — CSV Every weekly snapshot since launch ↓ CSV](https://foreground.agency/data/ai-brand-visibility/history.csv) All endpoints stream from /data/ai-brand-visibility-export.php. Fresh on every request — no stale cache. How to cite ## Citation formats. APA Foreground Digital. (2026). AI Brand Visibility Snapshot — GCC [Dataset]. https://foreground.agency/data/ai-brand-visibility BibTeX @dataset{foreground_aivs_gcc_2026, title = {AI Brand Visibility Snapshot --- GCC}, author = {{Foreground Digital}}, year = {2026}, url = {https://foreground.agency/data/ai-brand-visibility}, note = {Weekly snapshot, methodology v1.5}, license = {CC-BY-4.0} } Plain text "AI Brand Visibility Snapshot — GCC", Foreground Digital, weekly snapshot, https://foreground.agency/data/ai-brand-visibility, CC-BY-4.0. ## Want your brand checked individually? The dataset covers 50 brands. The free AI Brand Mention Checker runs the same methodology on any brand you give it — emailed PDF report. [Check your brand →](https://foreground.agency/tools/ai-brand-check)