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Fostering responsible AI adoption in startups through entrepreneurial orientation: A sustainable approach

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  • Alshibani, Safiya Mukhtar
  • Korayim, Diana
  • Mehrotra, Ankit
  • Agarwal, Vaishali

Abstract

In the dynamic and fluid business landscape, startups face the daunting task of maintaining their position and navigating the path of growth. Responsible AI (RAI) is technological support that promises to be a differentiator and propeller for startups. The study employed grounded theory method within a qualitative framework to analyze the themes from cross-cultural data. These themes aligned with the Entrepreneurial Orientation theory and the Responsible Innovation framework. The retrieved opinions were then divided into five sub-themes: innovativeness and reflexivity, proactiveness and anticipation, risk-taking and reflexivity, autonomy and inclusion, and competitive aggressiveness and responsiveness, which laid the foundation for understanding the drivers and adopters of RAI in startups. This research contributes to the literature on the emerging Responsible AI domain in businesses, particularly startups, by elaborating on the factors that would lead to the adoption of Responsible AI for business sustainability.

Suggested Citation

  • Alshibani, Safiya Mukhtar & Korayim, Diana & Mehrotra, Ankit & Agarwal, Vaishali, 2025. "Fostering responsible AI adoption in startups through entrepreneurial orientation: A sustainable approach," Technological Forecasting and Social Change, Elsevier, vol. 219(C).
    • Handle: RePEc:eee:tefoso:v:219:y:2025:i:c:s0040162525003038
    DOI: 10.1016/j.techfore.2025.124272
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    2. Su, Yu & Feng, Xuan, 2026. "Machine learning approaches to predicting energy price correlation: From a responsible AI perspective," Technological Forecasting and Social Change, Elsevier, vol. 225(C).

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