近年來生成式 AI 快速普及,深刻改變行銷人員的工作要求與工作內容,然而企業普遍面臨「技術投入」與「實際績效」脫節的困境。本研究整合工作要求-資源模型(JD-R Model)、任務-科技適配理論(TTF)與知覺組織支持理論(POS),探討生成式 AI 導入後,工作要求改變(降低阻礙性要求、增加認知要求與壓力)如何透過工作重塑影響行銷人員的適應性績效,並檢驗 TTF 與 POS 之直接效果與調節效果。
本研究以網路問卷蒐集任職於品牌方或代理商之行銷工作者資料,共回收 283 份有效問卷,採用階層迴歸分析與 PROCESS macro 進行中介及調節式中介效果檢驗。研究結果顯示:(1)降低阻礙性要求對工作重塑具顯著正向影響;(2)增加認知要求與壓力對工作重塑之影響為負向且不顯著,與原假設方向相反;(3)任務-科技適配與(4)知覺組織支持皆對工作重塑具顯著正向影響,其中知覺組織支持之解釋力最高;(5)工作重塑對適應性績效具顯著正向影響,並於「降低阻礙性要求→適應性績效」路徑中具部分中介效果,但於「增加認知要求與壓力→適應性績效」路徑中之中介效果不顯著;(6)TTF 與 POS 對工作要求改變至工作重塑路徑之調節效果均未達顯著,顯示二者較傾向以獨立主效果而非條件調節的方式影響員工行為。
研究結果說明,AI 導入對行銷人員工作重塑之驅動效果,主要來自資源釋放而非認知壓力之正向轉化,且組織治理與工具適配本身即是驅動員工主動適應的關鍵資源。本研究建議企業應將 AI 治理重心由工具採購轉向系統性支持,包括建立使用規範、提供培訓資源與容錯文化,以促使技術投資真正轉化為員工行為改變與組織績效提升。

The rapid adoption of generative AI has reshaped marketers' job demands, yet many organizations struggle to convert technology investment into measurable performance. Drawing on the Job Demands-Resources (JD-R) model, Task-Technology Fit (TTF) theory, and Perceived Organizational Support (POS) theory, this study examines how AI-driven changes in job demands—reduced hindrance demands and increased cognitive demands and pressure—affect marketers' adaptive performance through job crafting, and tests the direct and moderating roles of TTF and POS.
Survey data were collected from 283 valid marketing practitioners working at brands or agencies in Taiwan. Hierarchical regression and the PROCESS macro were used to test mediation and moderated mediation effects. Results show that (1) reduced hindrance demands significantly and positively predicted job crafting; (2) increased cognitive demands and pressure showed a negative, non-significant effect on job crafting, contrary to the hypothesized direction; (3) TTF and (4) POS both significantly and positively predicted job crafting, with POS showing the strongest explanatory power; (5) job crafting significantly predicted adaptive performance and partially mediated the path from reduced hindrance demands to adaptive performance, but did not significantly mediate the path from increased cognitive demands and pressure; (6) neither TTF nor POS significantly moderated the relationships between job demand changes and job crafting, suggesting both function primarily as independent drivers rather than boundary conditions.
These findings suggest that AI's effect on marketers' job crafting stems mainly from resource liberation rather than the positive reframing of cognitive demands, and that organizational governance and tool-task fit themselves serve as key resources driving proactive employee adaptation. Practical implications call for shifting AI governance from tool procurement toward systematic support—including usage policies, training, and a faulttolerant culture—to translate technology investment into behavioral change and organizational performance gains.

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