Generative AI accelerates the visual homogenization of green brand communication, making it harder for consumers to distinguish genuine green brands from greenwashing brands through visual cues. Prior research seldom addresses how AI-generated visuals shape perceived green brand authenticity. Building on the warmth-competence theory, this study proposes that warmth and competence visual cues function as asymmetric diagnostic dimensions in AI-generated contexts. Two studies were conducted. Study 1 employed a 2 & times; 2 between-subjects simulated scenario experiment (N = 451). Study 2 applied computer vision to decompose tone, brightness, and saturation from platform AI-generated green brand images, combined with subjective evaluation (150 participants, 900 observations) using crossed random-effects modeling. Convergent results show that competence-oriented cues consistently outperform warmth-oriented cues in differentiating genuine green from greenwashing brands, enhancing brand trust and green purchase intention. AI technology attitude moderates this process by shifting consumers' cue reliance. This research advances green brand authenticity scholarship from textual validation to first-screen visual attribution and extends the warmth-competence theory by revealing the dimensions' asymmetric diagnosticity in AI-generated green communication.
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