Application Characteristics and Challenges of Generative AI in Service Industry Marketing Scenarios

Generative Artificial Intelligence (AIGC) is profoundly reshaping the value creation paradigm in service marketing. Grounded in Service-Dominant Logic (S-D Logic), this study systematically analyzes AIGC’s application characteristics across three core service marketing scenarios: Intelligent Interaction: Constructing a human-AI-customer triadic collaboration system (Guo, 2025) to enable seamless service delivery. Content Creation: Achieving scalable personalized service (Bai & Guo, 2024) through dynamic content generation. Customer Insight: Empowering data-driven decision-making for precision marketing. These applications significantly enhance marketing efficiency, personalization, and experiential quality. Concurrently, the study identifies critical inherent tensions in localized AIGC implementation: Technology-Trust Tension: Data security risks and algorithmic black-box opacity undermining accountability (Zhang & Chen, 2025; Chen & Li, 2025). Efficiency-Empathy Tension: The “empathy gap” in human-AI interaction, particularly detrimental in high-touch service recovery scenarios (Li & Zheng, 2024). Globalization-Localization Tension: Cultural misfit due to inadequate adaptation of global models to local contexts (e.g., Chinese cultural nuances) (Wang & Wang, 2025). To address these challenges, we propose the innovative Lightweight-Embedded-Adaptive-Forward-feeding (LEAF) Model: Lightweight Technology (L): Prioritizing API integration (e.g., Baidu, Alibaba, Tencent, DeepSeek) for cost-effective access. Embedded Processes (E): Structuring workflows (e.g., “AI triage + human expert”, “AI draft + human refinement”) for genuine human-AI collaboration. Adaptive Culture (A): Implementing prompt engineering and localized fine-tuning to embed cultural intelligence. Forward-feeding Mechanism (F): Establishing a data-driven feedback loop (collection → structuring → model optimization) for continuous improvement. The LEAF model provides a strategic pathway for local service enterprises, especially resource-constrained SMEs, to implement AIGC responsibly, efficiently, and cost-effectively, offering significant theoretical and practical contributions.