Burlakov Oleksandr, PhD in Economic, Assistant Professor at the Department of Accounting, Taxation and E-business Technology, Higher educational institution «Podillia State University», Kamianets-Podilskyi, Ukraine

ORCID: 0000-0003-2753-3600
e-mail: burlakovos@pdatu.edu.ua

Digital Management in the Context of Artificial Intelligence Technologies Implementation

Abstract. Introduction. The article discusses the importance of the digital transformation landscape and the integration of artificial intelligence (AI) technologies into digital management. AI is conceptualized as the driving force of a technological revolution that will fundamentally reshape economic and organizational well-being. The urgency of this research stems from the gap between AI’s potential and the lack of expertise in strategically using it to create tangible business value. This demands that digital managers shift from technical supervision to strategic architecture.

Purpose. This study aims to conduct a thorough scientific analysis of how digital management is transformed by AI. The analysis will identify the necessary theoretical frameworks, strategic shifts, and governance principles. The study aims to develop a comprehensive conceptual model for the strategic integration of AI, organizational transformation, and ethical oversight, resulting in actionable scientific recommendations.

Results. The analysis determined that successful digital management is defined by effectively aligning AI and IT across four primary sources of value creation: automation, knowledge management, strategic decision-making (SDM), and service innovation. Notably, AI significantly enhances the SDM process through cognitive augmentation, accelerating the speed, improving the quality, and expanding the scale of strategic analysis by enabling virtual simulations and providing unbiased feedback. Effective implementation requires a robust AI governance framework that embeds principles such as accountability, transparency, and fairness to mitigate ethical and regulatory risks. The paper introduces the “superagency” conceptual model as the new managerial competence required for effective co-creation with intelligent systems, shifting the focus from control to collaboration. The paper proposes a novel governance harmonization framework that illustrates how national data governance practices can align with international ethical standards, such as Singapore’s FEAT principles, to ensure digital resilience in the context of post-war recovery.

Conclusions. Digital management must focus strategically on implementing ethical AI governance and developing management practices based on cognitive augmentation. The key scientific novelty of this study includes the conceptual modeling of the influence of AI on SDM through cognitive augmentation within the Ukrainian enterprise context, the development of a governance harmonization framework, and the introduction of the “superagency” competence model. Future research should prioritize empirically quantifying AI value, formally formalizing the superagency model, and harmonizing national AI policies with international regulatory frameworks, such as the EU AI Act, with a focus on digital resilience and economic recovery.

Keywords: artificial intelligence; digital management; strategic decision-making; Governance; cognitive augmentation; transformation.

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