The study shows that AI adoption interacts with digital transformation and digital maturity in an emerging-market subsidiary, not as a universal driver of transformation, but as a contingent catalyst shaped by governance, acculturation, internal capabilities, and ecosystem coordination.
Abstract
ABSTRACT Objective: This study examines the relationship between Artificial Intelligence (AI) adoption, digital transformation, and digital maturity in a Brazilian subsidiary operating in the mobility and payment ecosystem. Methods: An interpretivist, qualitative-dominant mixed-methods design was adopted, combining a single case study with semi-structured interviews and the CRITIC and WASPAS multi-criteria decision-making techniques. Results: The findings show that AI adoption is shaped by organizational structure, culture, employee training, and technological integration. When supported by governance, acculturation, and capability development, these conditions may contribute to digital transformation. In the CRITIC-based weighting structure, implementation cost presented the lowest informational contribution, while internal development emerged as the most salient alternative, followed by partial implementation and ready-made or outsourced solutions. Managers also associate AI adoption with gains in efficiency, customer experience, and competitive positioning. Conclusions: The study shows that AI adoption interacts with digital transformation and digital maturity in an emerging-market subsidiary, not as a universal driver of transformation, but as a contingent catalyst shaped by governance, acculturation, internal capabilities, and ecosystem coordination.
This study investigates how AI adoption enhances organizational innovation capability and, in turn, improves economic, environmental, and social dimensions of business performance, and links digital transformation with sustainability outcomes.
S. P, Sriharan M, S. P et al.· International Journal for Re...· 0 citations
The results suggest that the sustainability benefits of AI emerge when contextual readiness and psychological assurance jointly enable organizations to move beyond adoption intention toward sustained AI utilization, encompassing economic, operational, and environmental dimensions.
This study investigates the impact of Artificial Intelligence (AI)-driven digital transformation on performance efficiency in Accounting Information Systems (AIS) within emerging economies, with Nigeria as the focal context. The study is anchored on the Technology Acceptance Model (TAM), Diffusion of Innovation (DOI), and Resource-Based View (RBV), which collectively explain technology adoption behavior, diffusion patterns, and performance outcomes.
A cross-sectional descriptive and explanatory survey design was adopted. Primary data were collected from 300 accounting and finance professionals drawn from banking, manufacturing, telecommunications, and public sector organizations across Lagos, Abuja, Port Harcourt, and Ibadan. Data were obtained through a structured Likert-scale questionnaire and analyzed using SPSS version 27.
The findings reveal that AI-driven digital transformation significantly enhances accounting system performance efficiency, particularly in processing speed (β = 0.47, p < .001), reporting accuracy (β = 0.43, p < .001), and real-time financial decision support (β = 0.45, p < .001). Results further indicate that AI integration improves automation of financial workflows, strengthens data consistency, and enhances system responsiveness.
However, the study identifies key barriers including high implementation costs (86.9%), inadequate technical skills (84.1%), cybersecurity risks (82.3%), and infrastructural limitations (75.6%), which collectively slow full-scale AIS transformation.
The study concludes that AI-driven digital transformation is a significant predictor of accounting information system performance efficiency in emerging economies. Theoretically, the study extends TAM and DOI by demonstrating their relevance in AIS transformation, while RBV explains how AI enhances organizational capability. Practically, the study provides actionable insights for policymakers, system developers, and organizational leaders on optimizing AI integration in accounting systems.
David Sunday Araoti· Journal of Artificial Intell...· 0 citations
Artificial Intelligence (AI) technology has transitioned from an advanced corporate application into an accessible operational utility for contemporary business management. For Small and Medium Enterprises (SMEs), integrating AI capabilities offers substantial potential to optimize internal workflows, enhance decision-making precision, and strengthen market positioning. However, actual AI adoption among smaller enterprises in developing economies remains fragmented due to resource limitations and technical risks. Moving beyond a conventional application of the Technology-Organization-Environment (TOE) framework, this paper proposes an extended theoretical framework that integrates AI-specific trustworthiness and organizational digital maturity as contingency mechanisms. The conceptual model evaluates primary drivers across technological (relative advantage, complexity), organizational (top management support, financial readiness), and environmental contexts (competitive pressure, regulatory support), while incorporating Perceived AI Trustworthiness as a mediating mechanism and Organizational Digital Maturity as a moderating condition. The paper formulates eight testable propositions and details a quantitative methodology based on Partial Least Squares Structural Equation Modeling (PLS-SEM) for a target sample of N=300 SMEs. This framework advances theoretical understandings of technology adoption in emerging economies and offers actionable directives for policymakers and business managers seeking to accelerate digital maturity.
Nor Fazalina Salleh, N. H. Asnawi, Norfazlina Ghazali et al.· International journal of res...· 0 citations
Managers should prioritise technologies with clear operational utility, secure visible senior management commitment and align adoption governance with firm size and regulatory exposure and align adoption governance with firm size and regulatory exposure during the COVID-19 pandemic.
Muhammad Ihsan Fawzi, A. P. Subriadi, Mochammed Fahlevi· Journal of Science and Techn...· 0 citations
Artificial intelligence is rapidly transforming marketing by improving customer engagement and operational efficiency. Small and medium-sized enterprises (SMEs), especially in Qatar, are not able to adopt AI due to high adoption costs, poor technological skills and employee resistance. A thorough and methodological literature review was conducted to get a grasp on the factors influencing AI adoption and the subsequent effect on marketing performance. In accordance with the PRISMA guidelines, 32 peer-reviewed publications from 2020 to 2025 were analysed by applying a CASP/AMSTAR checklist, thematic coding and narrative analysis. The literature review has identified that technological readiness, managerial support, digital literacy and environmental factors are the major facilitators of AI adoption. However, context and organisational challenges are the main inhibitors of AI adoption. Nevertheless, the literature affirms that AI adoption increases the marketing performance of SMEs, and the TOE and DOI models are supported, while recommending a merger with the dynamic capabilities theory. Finally, the literature review asserts that policymakers and SME managers need to prioritise training, infrastructure and digital readiness to ease the path for AI adoption.
Salma El-Gohary, Mohamed Slim Ben Mimoun, Hatem El-Gohary· Journal of Cultural Analysis...· 0 citations