本研究以臺灣媒體從業人員為研究對象，探討新聞專業信念、AI 自我效能、 AI 知覺威脅與AI 使用意圖之間的關係，採混合研究設計（mixed-methods design），結合量化問卷調查（n = 96）與深度訪談（n = 5）進行分析。
量化部分以偏最小平方結構方程模型（PLS-SEM, Mode A）進行路徑分析，並以 1,000 次偏差校正與加速自助抽樣法（ Bias-Corrected and Accelerated Bootstrap）估計中介效果；質化部分採立意抽樣，以面對面深度訪談蒐集從業人員之實務經驗，並以半結構訪談為分析框架。
研究結果顯示，新聞專業信念對 AI 使用意圖之影響呈現「競爭式中介」結構（competitive mediation）。新聞專業信念一方面透過強化 AI 知覺威脅產生負向間接效果（β = −.153），體現從業人員對 AI 侵蝕查證責任與新聞倫理邊界的審慎防禦；另一方面亦對 AI 使用意圖具有正向直接效果（β = +.194, p = .038），反映專業判斷能力愈強的記者愈能主動評估AI 工具之使用價值。兩條路徑近乎抵銷，總效果趨近於零（βtotal = +.041, ns）。AI 知覺威脅對 AI 使用意圖具最強負向預測力（β = −.387, p < .001, f² = .144），此現象為 AI 與新聞專業邊界的核心呈現。AI自我效能雖未達調節效果，敏感度分析仍顯示其對 AI 使用意圖具強烈正向直接效果（β = +.436, p < .001, f² = .239），提示操作能力的提升有助於從業人員重新界定人機協作中的責任邊界。
質化訪談進一步揭示，從業人員普遍將人工查證視為不可讓渡之專業核心，並發展出多層查核機制以維護新聞可信度；組織政策的強制性介入則顯示，邊界重構並非純然出於個人意願，而是在制度壓力下被動形塑的結果。本研究據此提出「雙路徑採用模型」（dual-pathway adoption model），整合邊界工作之規範性審慎路徑與科技接受模型之工具性自信路徑。

This study investigates the relationships among journalistic professional beliefs, AI self-efficacy, perceived AI threat, and intention to use AI among media professionals in Taiwan. A mixed-methods design was employed, integrating a quantitative questionnaire survey (n = 96) with qualitative in-depth interviews (n = 5).
For the quantitative component, Partial Least Squares Structural Equation Modeling (PLS-SEM, Mode A) was used for path analysis, while 1,000 bias-corrected and accelerated (BCa) bootstrap resamples were conducted to estimate mediation effects. For the qualitative component, purposive sampling was employed to recruit media professionals for face-to-face in-depth interviews, with a semi-structured interview framework used to guide data collection and analysis.
The results indicate that journalistic professional beliefs exert a competitive mediation effect on intention to use AI. On the one hand, stronger journalistic professional beliefs increase perceived AI threat, generating a negative indirect effect (β = −.153). This reflects media professionals’ cautious and defensive stance toward AI’s potential erosion of fact-checking responsibilities and the ethical boundaries of journalism. On the other hand, journalistic professional beliefs also exert a positive direct effect on intention to use AI (β = +.194, p = .038), suggesting that journalists with stronger professional judgment are more capable of proactively evaluating the practical value of AI tools. These two pathways nearly offset each other, resulting in a total effect approaching zero (β_total = +.041, ns).
Perceived AI threat demonstrates the strongest negative predictive effect on intention to use AI (β = −.387, p < .001, f² = .144), highlighting the central role of the boundary between AI and journalistic professionalism. Although AI self-efficacy does not demonstrate a significant moderating effect, sensitivity analysis reveals a strong positive direct effect on intention to use AI (β = +.436, p < .001, f² = .239). This finding suggests that improving operational competence may help media professionals redefine the boundaries of responsibility in human–AI collaboration.
The qualitative interviews further reveal that media professionals generally regard human-led fact-checking as a non-negotiable core of journalistic professionalism and have developed multilayered verification mechanisms to safeguard news credibility. The mandatory intervention of organizational policies further indicates that the reconstruction of professional boundaries is not solely driven by individual willingness but is instead shaped, in part, by institutional pressures.
Based on these findings, this study proposes a “Dual-Pathway Adoption Model”, integrating the normative and cautious pathway of boundary work with the instrumental confidence pathway of the Technology Acceptance Model (TAM).

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