Aug 2026· Tạp chí Khoa học Đại học Công Thương· 0 citations
TL;DR
The findings suggest that AI creates enterprise value through cognitive automation, decision intelligence, and business model innovation, but their effectiveness depends on data governance, digital leadership, human capital, financial readiness, and regulatory support.
Abstract
Artificial Intelligence (AI) is increasingly recognized as a foundational technology for enterprise competitiveness in the digital economy. However, limited research explains how AI capabilities create enterprise value in emerging economies with uneven digital readiness. This study synthesizes the mechanisms of AI-driven value creation and examines structural barriers to enterprise AI adoption in Vietnam. Using a qualitative conceptual research design based on secondary data, the study integrates the Resource-Based View (RBV) with a four-layer AI framework covering data, algorithms, infrastructure, and applications. The findings suggest that AI creates enterprise value through cognitive automation, decision intelligence, and business model innovation, but their effectiveness depends on data governance, digital leadership, human capital, financial readiness, and regulatory support. In Vietnam, adoption is constrained by fragmented data systems, shortages of skilled AI professionals, limited SME investment capacity, and evolving governance frameworks. This study contributes a conceptual synthesis linking AI capability layers to enterprise value creation and provides implications for managers and policymakers seeking to accelerate responsible AI adoption.
This study aims to identify the key challenges and development prospects of AI implementation to enhance business efficiency and ensure sustainable development, providing strategic guidance for organizations to balance technological innovation with responsibility and risk management.
Giedrius Čyras, Vita Marytė Janušauskienė· International Scientific Con...· 1 citation
An extended theoretical framework that integrates AI-specific trustworthiness and organizational digital maturity as contingency mechanisms is proposed 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
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
It is concluded that no single framework adequately explains GenAI's enterprise decision-making effects across all analytical levels, and that individual-, organizational-, and task-level frameworks must be combined rather than treated as competing explanations, identifying multi-level theoretical integration as the central future research prospect.
Pallavi Rahul Gedamkar, Alpesh A. Nasit, P. Tiwari et al.· International journal of com...· 0 citations
The rapid advancement of Artificial Intelligence (AI) has transformed how organizations build and sustain competitive advantage. However, investments in AI alone are insufficient to achieve sustainable competitiveness without the support of strong organizational capabilities. This study aims to develop a conceptual framework that explains the strategic role of AI-enabled Human Capital in enhancing Organizational Resilience and Sustainable Competitiveness. Using a Conceptual Literature Review (CLR) approach, the study synthesizes complementary theoretical perspectives, including Human Capital Theory, the Resource-Based View, Dynamic Capabilities Theory, and Risk Governance Theory, supported by contemporary literature on artificial intelligence, strategic management, financial policy, risk governance, and organizational resilience. The study proposes an Integrated Strategic Capability Framework that explains how organizations transform AI investments into sustainable competitive advantage through the interaction of four strategic capabilities: Financial Policy, Risk Governance, AI-enabled Human Capital, and Organizational Resilience. Within this framework, AI-enabled Human Capital is positioned as the central strategic capability that integrates human expertise, AI technologies, organizational learning, and strategic decision-making. The proposed framework contributes to the theoretical development of AI-driven strategic management while offering practical guidance for organizations in designing AI-based transformation strategies. Nevertheless, further empirical studies are required to validate the proposed framework across diverse organizational contexts.
Rida Justin Jacobalis, Iman Sjamsu Rahardjo, Sri Rahayu et al.· Jurnal Minfo Polgan· 0 citations
Purpose: Artificial intelligence (AI) is helping organization to acquire knowledge, take informed decisions, innovate, allocate resources and interact with stakeholders effectively and hence, bring a transformative up-scaling which is resulting in gaining successful competitive edge. However, mere adoption and usage of AI will not result in gaining quick and automatic sustainable competitive advantage. Therefore, there are various other factors required for an organization to obtain competitive edge and the factors like the ability of organizations to convert technological investments into durable competitive outcomes, complementary organizational resources, dynamic capabilities, innovation, human capital, leadership, sustainability practices and responsible governance. With a focus on the developing role of artificial intelligence, this conceptual paper examines and incorporates recent research on the causes and effects of sustainable competitive advantage.
Design/Methodology/Approach: The adoption of blockchain, corporate digital responsibility, AI adoption, green innovation, knowledge management capability, human resource capability, fintech adoption, strategic leadership, women's strategic leadership, and lean and green manufacturing practices are studies that are cited in this paper. The Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT) provide additional support for conceptualizing the sustainable competitive advantage.
Findings: The paper proposes an integrated conceptual framework in which AI-enabled capabilities act as an important contemporary antecedent, while organizational agility, innovation capability, business model innovation and sustainability-oriented capabilities function as mechanisms through which AI and other strategic resources generate SCA. The proposed framework identifies technological, organizational, strategic, sustainability and institutional factors as major antecedent categories and identifies sustainable performance, organizational resilience, business value creation, innovation performance and long-term organizational competitiveness as major outcomes.
Future Research: By changing the focus from "AI adoption: competitive advantage" to "AI-enabled capability: sustainable competitive advantage," the paper adds to the body of literature and offers suggestions for further empirical study.
Unknown authors· International Journal of Man...· 0 citations
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