Artificial intelligence in business: challenges and prospects for development

NEW TRENDS IN CONTEMPORARY ECONOMICS, BUSINESS AND MANAGEMENT

ARTIFICIAL INTELLIGENCE ADOPTION IN ENTERPRISES: A LAYERED CAPABILITY FRAMEWORK FOR EMERGING ECONOMIES

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.

Artificial intelligence as a driver of human resource management transformation: opportunities, risks and strategic directions

The rapid development of Artificial Intelligence (AI) is fundamentally reshaping organizational processes and redefining the role of Human Resource Management (HRM). This paper aims to analyze how HRM is being redesigned in the context of AI-driven transformation, focusing on key opportunities, associated risks, and strategic directions for sustainable organizational development. The study is based on a qualitative, conceptual methodology, using secondary data derived from international reports and indices, including the World Economic Forum's Future of Jobs Report, OECD well-being frameworks, International Labour Organization analyses, and European policy documents. In addition, insights from the banking sector are considered as an illustrative context due to its advanced level of AI adoption. The findings indicate that AI enhances the efficiency of HR functions such as recruitment, performance management, and workforce analytics, while also enabling more personalized employee experiences. At the same time, the integration of AI introduces significant challenges, including algorithmic bias, ethical concerns, data privacy risks, and the potential depersonalization of workplace relationships. The paper argues that HRM must evolve towards a strategic and integrative role, ensuring a balance between technological innovation and employee well-being. A conceptual perspective is proposed to support organizations in adapting HR practices to AI-driven environments while maintaining a human-centered approach and long-term performance.

Artificial Intelligence Integration and Its Effects on Business Efficiency: Evidence from a Systematic and Empirical Investigation (2020-2025)

Artificial intelligence in human resources management: Summary of academic research and emerging trends (2016-2025)

Artificial intelligence (AI) and human resource management (HRM) are two closely intertwined areas that have gained increasing attention in management research. While AI technologies aim to enhance decision-making, efficiency, and innovation within organizations, HRM reflects a company’s ability to manage, engage, and develop its workforce effectively. However, despite the growing body of literature, existing reviews remain fragmented and often lack a comprehensive synthesis of how AI impacts HR functions and employee-related outcomes. Importantly, AI is not merely a technological tool; when strategically integrated into HR practices, it can significantly improve employee engagement, organizational effectiveness, and ethical governance. The objective of this study is to examine the integration of AI in HRM and its impact on employee involvement and organizational outcomes, with a specific focus on identifying the research gap related to the lack of integrated thematic and analytical perspectives in prior reviews, and identifying the key dimensions that influence successful implementation. To achieve this, a systematic review of the literature published between 2016 and 2025 was conducted using the Scopus database to ensure access to the most relevant studies. Predefined inclusion and exclusion criteria were applied, resulting in an initial selection of 2,385 articles. After removing duplicates and conducting a detailed analysis of abstracts and full texts, a final sample of 23 studies was retained. Unlike prior studies that adopt a predominantly descriptive approach, this review combines descriptive and qualitative content analysis to provide a structured thematic synthesis of the literature. The analysis highlights three main areas: AI adoption strategies, HR functions most affected by AI, and ethical and regulatory challenges associated with its use. Key factors influencing successful AI integration include employee involvement, management commitment, and the implementation of ethical governance frameworks. Organizations that implement AI in a structured and transparent manner tend to achieve higher engagement, improved decision-making, and enhanced organizational effectiveness. The findings suggest that future research should focus on increasing employee participation in AI-driven HR initiatives, developing robust ethical guidelines, and establishing appropriate regulatory frameworks to maximize the positive impact of AI on human resource management.

EU Artificial Intelligence Act: risks and opportunities for the European system

This paper examines the European Union Artificial Intelligence Act (AI Act) as a strategic regulatory response to the rapid and pervasive diffusion of artificial intelligence technologies. Starting from a conceptual framing of AI as an instrument of augmented intelligence rooted in bounded rationality, the contribution highlights how contemporary AI systems adopt satisficing logics through heuristics and large-scale data processing rather than pursuing optimal solutions. The analysis situates the AI Act within the broader EU digital strategy and discusses its risk-based regulatory architecture, which classifies AI systems according to the severity and likelihood of potential harm to fundamental rights, safety, and democratic values. Particular attention is devoted to high-risk AI systems, whose stringent compliance obligations raise significant legal, technical, and economic challenges, especially for SMEs and start-ups. While acknowledging the risks of regulatory rigidity, innovation slowdown, and market entry barriers, the paper also emphasizes the strategic opportunities generated by the AI Act. These include the consolidation of a trustworthy, human-centric AI ecosystem, the strengthening of the Digital Single Market, and the potential emergence of a global regulatory benchmark through the so-called “Brussels effect.” Ultimately, the AI Act is interpreted not merely as a compliance burden, but as a long-term investment capable of transforming regulation into a competitive advantage for the European system.