As large language models (LLMs) become increasingly capable of generating persuasive content, understanding their effectiveness across different advertising strategies becomes critical. This paper presents a two-part investigation examining LLM-generated advertising through complementary lenses: (1) personality-based and (2) psychological persuasion principles. In our first study (n=400), we tested whether LLMs could generate personalized advertisements tailored to specific personality traits (openness and neuroticism) and how their performance compared to human experts. Results showed that LLM-generated ads achieved statistical parity with human-written ads (51.1% vs. 48.9%, p > 0.05), with no significant performance differences for matched personalities. Building on these insights, our second study (n=800) shifted focus from individual personalization to universal persuasion, testing LLM performance across four foundational psychological principles: authority, consensus, cognition, and scarcity. AI-generated ads significantly outperformed human-created content, achieving a 59.1% preference rate (vs. 40.9%, p < 0.001), with the strongest performance in authority (63.0%) and consensus (62.5%) appeals. Qualitative analysis revealed AI's advantage stems from crafting more sophisticated, aspirational messages and achieving superior visual-narrative coherence. Critically, this quality advantage proved robust: even after applying a 21.2 percentage point detection penalty when participants correctly identified AI-origin, AI ads still outperformed human ads, and 29.4% of participants chose AI content despite knowing its origin. These findings demonstrate LLMs' evolution from parity in personalization to superiority in persuasive storytelling, with significant implications for advertising practice given LLMs' near-zero marginal cost and time requirements compared to human experts.

翻译：随着大语言模型（LLMs）生成说服性内容的能力日益增强，理解其在不同广告策略中的有效性变得至关重要。本文通过互补视角对LLM生成广告进行两部分研究：（1）基于人格特质；（2）基于心理说服原则。在第一项研究（n=400）中，我们测试了LLMs能否针对特定人格特质（开放性与神经质）生成个性化广告，并将其表现与人类专家进行比较。结果显示，LLM生成广告与人类撰写广告达到统计学对等（51.1% vs. 48.9%，p > 0.05），在匹配人格特质时未表现显著差异。基于这些发现，第二项研究（n=800）将焦点从个体个性化转向普适说服力，测试LLMs在四大基础心理原则中的表现：权威性、共识性、认知性与稀缺性。AI生成广告显著优于人类创作内容，获得59.1%偏好率（vs. 40.9%，p < 0.001），其中权威诉求（63.0%）与共识诉求（62.5%）表现最强。定性分析揭示AI优势源于构建更精妙、更具抱负的讯息，并实现更优的视觉-叙事一致性。关键的是，这种质量优势具有稳健性：即使当参与者正确识别AI来源时施加21.2个百分点的检测惩罚，AI广告仍优于人类广告，且29.4%的参与者在知晓来源后仍选择AI内容。这些发现表明LLMs实现了从个性化对等到说服性叙事优势的演进，考虑到LLMs相较于人类专家近乎零的边际成本与时间需求，这对广告实践具有重要启示。