This study contributes a unified research model for stakeholder-specific AI adoption, demonstrates a mixed quantitative-qualitative approach, and establishes a scalable foundation beginning with engineers and extending to other stakeholders through future empirical validation.
Assessing the effects of technology reliability (RL), credibility (CR) and technical competence (TEC) on HR professionals’ trust and, subsequently, their intent to deploy AI tools reveals that technology RL, CR and TEC each enhance trust in AI.
R. Arora, Neha Kumari Siradhana· South Asian Journal of Human...· 0 citations
By integrating five theoretical perspectives, the review develops a model of the AI strategic lifecycle, offering both a consolidated foundation for future research and a forwardlooking agenda for managers seeking to leverage AI as a strategic asset.
J. Lambert, O. Garanina· Review of business and econo...· 0 citations
This study aims to address the growing concerns surrounding the use of artificial intelligence (AI) in property valuation, particularly issues of transparency, trust and accuracy. This study focuses on aligning AI models with expectations to foster responsible adoption in real estate decision-making.
A systematic literature review (SLR) of 44 peer-reviewed studies published between 2018 and 2025 was conducted. NVivo software was used for qualitative coding, and the political, economic, social, technological, legal and environmental framework guided the analysis of external factors influencing AI adoption. The study examined both technical model performance and stakeholder concerns.
Random forest and support vector machines were most frequently applied in structured valuation tasks, while artificial neural networks were reported in contexts involving non-linear modelling and complex data patterns. Despite demonstrated predictive capabilities, policymakers and professional stakeholders placed greater emphasis on transparency, explainability and legal accountability. Identified trust-related challenges included algorithmic bias, limited model interpretability, regulatory ambiguity and insufficient integration of contextual factors. These findings informed the development of a hybrid AI valuation framework that integrates technological performance with governance mechanisms, contextual calibration and professional judgement to strengthen property valuation quality.
This study is limited by the absence of primary data from stakeholder interviews. The findings are based solely on published literature, which may not fully capture real-time industry perspectives or emerging on-the-ground challenges.
The proposed framework offers a transparent, data-driven solution for valuers, investors and regulators, supporting better-informed decisions and encouraging ethical AI adoption in real estate.
This study synthesises technical and stakeholder dimensions of AI in property valuation using a structured qualitative approach via SLR. It proposes a novel hybrid framework that integrates stakeholder trust factors with model precision to enhance both reliability and acceptance of AI tools.
Wajhat Ali, D. Samarasinghe, Zhenan Feng et al.· Urbanization, Sustainability...· 0 citations
It is demonstrated that AI adoption outcomes are contingent upon complementary organizational capabilities, knowledge management infrastructure, human capital quality, and institutional context rather than technology deployment alone.
Ridha Rayan Furqan, W. Adawiyah, Ali Şahin et al.· The International Conference...· 0 citations
Artificial intelligence (AI) is increasingly integrated into corporate strategies and operations, attracting considerable scholarly and practical attention, as well as raising important questions about its implications for firms’ sustainable development. The emerging body of literature has largely focused on the association between AI adoption and firm profitability, overlooking its implications for sustainable corporate governance. To address this gap in the literature, this study develops a novel AI adoption index to examine whether the adoption of AI is associated with stronger environmental, social, and governance (ESG) engagement among Japanese firms. Based on Stakeholder Theory and the Resource-Based View, we find for our sample of 145 Japanese firms that a higher AI adoption rate positively correlates with a higher overall ESG engagement. Specifically, our findings indicate that, after robustness checks, AI adoption is associated with social engagement scores, but not with environmental or governance engagement scores.
Ralf Bebenroth, Kevin Massmann, Yingying Zhang-Zhang· Sustainability· 0 citations
Empirical evidence is provided for the high relevance of procurement for public sector AI services via supplier-related governance perspectives and for the need to refine existing AI readiness and adoption models, particularly for regulated or defense-related procurement environments.
Max Ernst Hamscher, A. Glas, Michael Essig· International Journal of Pub...· 0 citations