Aug 2026· Journal of Intelligent Decision Making and Information Science· 0 citations· 23 references
Abstract
AI capability is a new strategic capability in the organization that goes beyond operational efficiency and can support the quality strategic decision-making, sustainable performance of an organization, and high decision quality. Though AI capability is evolving, current research remains disparate in how to transform an AI capability to a organizational value with the role of governance, leadership, and organizations capability. To solve this, in this study, a integrated conceptual framework grounded in the theory of resource-based view(RBV), dynamic capabilities theory(DCT) and the AI Governance literature is developed and empirically tested. In the model, the sequential relation between AI capability, AI governance, strategic decision quality, organizational agility, and organizational performance was proposed and the moderating role of digital leadership was examined. An explanatory sequential mixed-methods research design was used. The empirical analysis includes two phases. In the first phase, a cross-sectional survey of 446 senior executives and strategic decision makers of public and private organizations was conducted to empirically test the proposed integrated model using Partial Least Squares Structural Equation Modeling (PLS-SEM). In the second phase, qualitative data from 30 semi-structured interviews with senior executives was collected to gain a deep understanding of AI governance, digital leadership and organizational agility practices. Multi-group analysis further revealed differences in the proposed relationships for public and private organizations. Findings revealed that AI capability not only significantly strengthens the AI governance, and consequently the strategic decision quality, but it also improve the organizational agility, resulting in improved performance. Furthermore, digital leadership has a positive effect on reinforcing the association between AI governance and the strategic decision quality. Overall, this study integrates the technology capability, the organizational capability and the leadership capability to establish an AI-enabled strategic decision-making and performance management framework, and provides strategic insights for organizations that aim to realize greater value from their AI investments.
The study concludes that AI adoption serves as a strategic organizational capability that significantly enhances strategic planning effectiveness and suggests that organizations leveraging AI technologies are more likely to develop effective strategies, improve decision quality, enhance forecasting accuracy, and strengthen organizational adaptability.
Mark Ian C. Abrias, Nerissa M. Revilla· World Journal of Advanced Re...· 0 citations
Artificial Intelligence (AI) has revolutionized corporate governance practices, improving transparency, accountability, compliance monitoring, and strategic decision-making. This study analyzes the influence of AI-Driven Corporate Governance (AICG) on the performance of the companies, examining also the mediation effect of Decision Intelligence and the moderation effect of Digital Literacy. The study integrates the views of the Resource Based View (RBV) and Dynamic Capability theory to explore the link between AI's governance mechanisms and organizational performance. The research adopts an integrated moderated mediation approach, grounded in the Resource Based View (RBV) and Dynamic Capability Theory, to explain the role AI’s governance mechanisms play in enhancing organizational performance. The data which have been collected were analyzed on correlation, reliability, regression on 235 employees that work in organizations that in the process of digital transformation. The results clearly indicate that there is a positive effect of AI Corporate Governance on firm performance. Additionally, AI governance is a key lever for employing Decision Intelligence to boost organizational performance by maximizing the efficiency, agility and quality of managerial decision-making. The findings also illustrate that the influence of AI governance on firm performance is significantly moderated by Digital Literacy, underscoring the influence of employees' digital skills in unlocking the value of AI-enabled governance system. By bringing together technological capabilities and human competencies under one umbrella, the study adds to the increasing amount of literature on AI governance. It builds on existing work, by bringing the experiences of a developing economy context, where AI adoption and digital transformation is not yet mature. The results are of practical relevance for managers, policymakers, and organizations aiming to enhance governance efficiency, decision-making and the performance of their organizations by means of responsible use of AI and digital competences. The study builds that there is a need to not only invest in technology but also nurture intelligent decision making and a digitally empowered workforce to enable AI governance in the right path.
Muhammad Danial Arshad, Shazia Akhtar, Kausar Shaheen· Journal of Political Stabili...· 0 citations
The aim of this study is to identify the key factors of effective artificial intelligence-supported managerial decision support systems. Although the body of literature examining the role of artificial intelligence in decision-making is rapidly expanding, existing studies predominantly adopt a technological perspective, while integrated analyses of managerial and organizational implementation dimensions remain limited. The central research question of this study is which factors contribute, at the organizational level, to the successful implementation and sustainable use of AI-based decision supper systems. The research is based on a qualitative literature review methodology, which presents the key theoretical aspects of the relationship between artificial intelligence and managerial decision support systems and analyzes the relevant literature in the field. The main contribution of the study lies in systematically synthesizing the findings of the relevant literature and identifying the key organizational, managerial, and regulatory factors that influence the effectiveness of AI-based decision support. A limitation of the study is that it relies exclusively on qualitative literature analysis and does not include empirical investigation. Nevertheless, the findings provide a foundation for further empirical research, particularly regarding leader – AI interactions and the examination of long-term performance effects.
Ákos Moro, Katalin Szabó, Zsigmond Gábor Szalay· Acta Carolus Robertus· 0 citations
The study examined that how Agentic artificial intelligence (AI) can transform corporate governance by improving the quality of decision-making at the board level, governance effectiveness, and readiness of stakeholders. Its main goal is to examine the impact of autonomous intelligence and adaptive learning processes within Agentic AI systems on the strategy, risk management, compliance, and governance performance. The study used quantitative research design and used a structured questionnaire that was given to 200 corporate governance stakeholders, who are board directors, executives and compliance professionals. Analysis and interpretation of data was done by use of “descriptive statistics, correlation analysis, regression analysis, and paired sample t-tests” in SPSS. The findings indicate that Agentic AI capability has a statistically significant positive correlation with the quality of board-level decision-making, and Agentic AI capability should be considered a significant contributor to the accountability of the governance results. Additional results show that the degree of Agentic AI integration has a moderate and significant relationship with the overall corporate governance effectiveness. More so, the willingness of stakeholders to adopt Agentic AI is also high even though their exposure to practical experience is rather limited. The study concludes that Agentic AI can be viewed as a governance enhancing mechanism that enhances transparency, decreases information asymmetry and promotes adaptive, evidence-based board leadership.
Mahesh Agarwal· Journal of Intelligent Decis...· 0 citations
Strategic decision-making has become one of the most important determinants of organizational performance in today's digital business environment. Organizations operate in markets characterized by rapid technological change, globalization, intense competition, and continuously evolving customer expectations. Under such conditions, effective strategic decisions enable firms to allocate resources efficiently, respond to market changes, exploit emerging opportunities, and achieve sustainable competitive advantage. Digital technologies such as artificial intelligence, business analytics, cloud computing, and big data have significantly improved managerial decision-making processes by providing timely and accurate information. This review paper examines the relationship between strategic decision-making and organizational performance by discussing strategic planning, leadership, digital transformation, business intelligence, organizational culture, innovation, and risk management. The paper also highlights the challenges affecting strategic decision-making and presents recommendations for improving organizational effectiveness. The findings indicate that organizations adopting systematic, data-driven, and flexible decision-making approaches experience improved operational efficiency, financial performance, innovation capability, and long-term sustainability.
Maria Khan, A. Qureshi, Eman Riaz· Journal of business and mana...· 0 citations
Through the introduction of Financial Decision Intelligence, the study provides an integrative theoretical perspective explaining how Artificial Intelligence transforms financial decision-making into a continuous process of strategic intelligence creation. In doing so, it offers a conceptual foundation for future empirical research and advances the understanding of how organizations can leverage AI to strengthen strategic decision capability in the digital economy. Using an Integrative Literature Review (ILR), the study synthesizes multidisciplinary literature spanning strategic management, finance, business analytics, information systems, and artificial intelligence to develop an integrated theoretical framework. This study contributes to the strategic management literature by reconceptualizing financial modelling as a dynamic organizational capability, integrating previously fragmented theoretical perspectives, and establishing a conceptual foundation for future empirical research on AI-enabled financial decision capability. Beyond its theoretical contribution, the proposed framework also offers practical guidance for organizations seeking to strengthen evidence-based financial governance, strategic adaptability, and sustainable competitive advantage in increasingly data-intensive business environments.
Iman Sjamsu Rahardjo, Rida Justin Jacobalis, Idha Adhani et al.· Jurnal Minfo Polgan· 0 citations