近年來，內容行銷領域的行銷專業人員以專業生成內容（PGC）與使用者生成內容（UGC）為主，進行消費者參與度提升的多元化策略。然而，隨著數位資訊的快速增長，透過傳統內容策略來引發消費者興趣的難度逐漸增加。本研究旨在探討品牌透過PGC及UGC策略提升消費者參與時所面臨的挑戰，並進一步探討運用人工智慧生成內容（AIGC）作為解決方案之可行性。

本研究首先採用根本原因分析（RCA），確認降低內容行銷時消費者參與之四項核心障礙，包括強烈的商業懷疑、不明或不可靠資訊來源、高昂的審核成本，以及品牌聲譽管理困難。這些障礙共同構成了名為「品牌認知障礙」的理論架構。

接著，本研究透過六個具代表性的品牌進行多重個案研究，探索生成式人工智慧工具在內容行銷中的應用方式。分析結果歸納出三種不同的AI與人類共創模式，分別為協作式AI增強視覺內容創作、個人化AI驅動參與，以及AI促進創意協作。本研究提出AI與人類共創模式可作為中介機制，降低品牌認知障礙的負面影響，進而提高消費者的參與程度之假設，並透過結構方程模型（SEM）針對166份有效問卷資料進行實證驗證，證實了此一假設成立。

最後，本研究透過半結構式的專家訪談，進一步針對量化分析結果進行質性補充與深入探討。研究結果顯示，AI與人類共創模式對於降低品牌認知障礙對消費者參與的負面影響具有顯著的中介效果。此外，透過皮爾森相關分析，亦指出各種AI與人類共創模式對於消費者參與之情感、認知與行為面向的影響程度存在差異。

本研究在理論上闡明並實證驗證了AI與人類共創模式在品牌認知障礙與消費者參與之間的中介角色；在實務上則提出具體策略與建議，協助品牌管理者有效運用AIGC，促進數位內容生態系統中消費者的互動與參與。

In recent years, content marketing professionals have increasingly employed diverse strategies, primarily focusing on Professionally Generated Content (PGC) and User-Generated Content (UGC). However, amid the current surge of digital information, capturing consumer interest through traditional content strategies has become more challenging. This research addresses the difficulties brands encounter in enhancing consumer engagement via digital content marketing strategies that utilize PGC and UGC. It also explores the potential of employing Artificial Intelligence-Generated Content (AIGC) as a strategic solution.

The study begins with a Root Cause Analysis (RCA) to identify four main barriers to effective consumer engagement strategies: aggressive commercial skepticism, unreliable and unknown sources, high moderation costs, and challenges in reputation management. Collectively, these barriers form a theoretical construct known as "Brand Perception Barriers."

A multiple-case study involving six representative brands’ marketing campaigns was conducted to explore the use of generative AI tools in content marketing. This analysis identified three distinct modes of AI-Human Co-Creation: Collaborative AI-Enhanced Visual Content Creation, Personalized AI-Driven Engagement, and AI-Facilitated Creative Collaboration. The study hypothesized that these modes of AI-Human Co-Creation could mediate the adverse effects of Brand Perception Barriers, thereby enhancing consumer engagement. These hypotheses were empirically validated using Structural Equation Modeling (SEM) with data from 166 valid questionnaire responses, confirming the proposed mediating relationships.

Ultimately, semi-structured expert interviews provided qualitative insights that further contextualize the quantitative findings. The results demonstrate that AI-Human Co-Creation modes significantly mediate the adverse effects of Brand Perception Barriers on consumer engagement. Additionally, Pearson correlation analysis revealed that each AI-Human Co-Creation mode influences consumer engagement's emotional, cognitive, and behavioral dimensions in distinct ways.

This study contributes theoretically by clarifying and empirically supporting the mediating role of AI-Human Co-Creation modes in the relationship between Brand Perception Barriers and consumer engagement. From a practical perspective, it provides strategic guidance and actionable recommendations for brand managers to effectively leverage AIGC, thereby enhancing consumer engagement within digital content ecosystems.

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