基于智能体的在地化农产品品牌视觉设计策略研究

AI Agent-Driven Strategies for Localized Agricultural Product Brand Visual Design

摘要: 在乡村振兴战略背景下，农产品品牌建设面临视觉同质化、设计成本高和在地性不足等问题。本文提出“智能体驱动的在地化品牌视觉设计”框架，旨在通过人工智能与人机协同，兼顾效率与文化表达。研究方法上，构建由五个环节组成的系统模型：文化信息采集、文化符号提炼、智能体多方案生成、在地性校准和视觉系统构建。研究结果表明，该框架能够降低小规模农户的品牌设计门槛，提升文化真实性，避免AI导致的审美平均化风险。结论认为，智能体应被视为协作主体，其价值在于构建兼顾普惠性与在地性的设计生态，为农产品品牌提供理论与实践支持。

Abstract: Under the rural revitalization strategy, agricultural branding faces challenges of visual homogenization, high design costs, and insufficient cultural localization. This study proposes an “AI agent-driven framework for localized brand visual design”, aiming to integrate efficiency with cultural expression through artificial intelligence and human-AI collaboration. Methodologically, the research constructs a five-stage model: cultural information collection, symbol refinement, multi-scheme generation, localization calibration, and visual system construction. The findings indicate that this framework lowers design barriers for smallholder farmers, enhances cultural authenticity, and mitigates risks of aesthetic averaging caused by AI. The conclusion emphasizes that AI agents should be regarded as collaborative partners rather than mere tools. Their true value lies in building a design ecology that balances inclusivity and localization, thereby providing both theoretical and practical support for agricultural brand development.