D DAM LLM Independent research · AI × DAM

Statistic · AI Tagging · From the corpus

5+tags / asset (mean)

Average AI-generated tags per creative asset in 2026.

Across the 1M+ creative assets in the DAM LLM research corpus (data partner: Uplifted), the mean number of AI-generated tags per asset is 5 or more. Tags span objects, scene/mood, brand recognition, and — for video — clip-level tags including motion, transcription cues, and shot composition.

Mean
5+ tags / asset
Corpus size
1M+ assets
Distinct customers
200+ teams
Tag instances
5M+ total
Data partner
Uplifted (disclosed)
Methodology
Read →

AI tag categories represented in the corpus

Indicative breakdown · sample n=1M+ assets · DAM LLM Research, May 2026

Object detection
~95%
Scene / mood
~80%
Brand elements
~60%
Clip-level (video)
~55%
Transcription cues
~40%
Motion / camera
~30%

Percentages show share of assets that have at least one tag in each category. Categories overlap; an asset typically has tags in 4-6 categories. Source: Uplifted corpus, anonymized aggregate. Methodology →

Why this matters

The volume and structure of AI-generated tags is what makes natural-language asset retrieval possible. With 5+ tags per asset across millions of assets, an LLM can answer queries like "show me top-performing hooks from last quarter with a human face in frame and a bright outdoor background" grounded in real metadata — no manual tagging required.

The corpus also lets us benchmark AI tagging accuracy (see Report 03, in preparation) by comparing AI tags to human-verified subsets.

Cite this statistic

DAM LLM Research. "Average AI tags per creative asset, 2026." damllm.ai, 2026. https://damllm.ai/statistics/ai-tags-per-asset/

See also