This chapter analyses the growing role of artificial intelligence (AI) in the transformation of contemporary enterprises and analyses the transition from fragmented AI-supported processes towards integrated AI-first organisational models. The chapter combines theoretical discussion with an empirical market analysis conducted among 192 enterprises representing various sectors of the economy, including manufacturing, logistics, finance, trade, technology, and service industries. The purpose of the market analysis was to identify the principal areas of AI implementation, evaluate the organisational and strategic impact of intelligent technologies, and assess the preparedness of enterprises for operating under conditions of dynamic digital transformation. The findings indicate that artificial intelligence increasingly functions as a strategic component of enterprise development rather than merely a technological support tool. Organisations most frequently utilised AI in areas related to data analytics, digital marketing, customer service, logistics, and operational optimisation. The implementation of intelligent systems contributed to improving operational efficiency, accelerating strategic decision-making, strengthening organisational adaptability, and supporting innovation processes. Enterprises additionally emphasised the growing significance of predictive analytics, automation, recommendation systems, and AI-supported communication infrastructures in shaping organisational competitiveness and long-term resilience. The market analysis further demonstrates that the level of AI implementation remains strongly dependent on organisational resources, technological infrastructure, and digital competencies. Large enterprises were more likely to adopt advanced AI systems, whereas small and medium-sized organisations more frequently faced barriers related to financial limitations, shortages of qualified specialists, and insufficient technological preparedness. Respondents also identified important challenges associated with AI implementation, including cybersecurity risks, data protection, algorithmic transparency, and ethical governance. The findings presented in this chapter additionally reveal that artificial intelligence increasingly affects organisational culture, managerial practices, and human–technology interaction within enterprises. AI-driven transformation contributes to the emergence of more integrated, data-oriented, and adaptive organisational structures while simultaneously generating new governance-related challenges connected with accountability, explainability, and human oversight. The chapter therefore provides both an empirical and market-oriented perspective complementing the broader theoretical discussions presented throughout the book concerning AI-driven enterprise transformation, integrated AI systems, and the growing role of governance and leadership within AI-first organisational environments.
Ida Skubis, Judyta Kabus, Jolanta Wodarska et al.· 0 citations
Artificial intelligence (AI) is becoming an increasingly visible element of business management, influencing not only operational processes but also strategic planning, financial management, leadership, and organisational governance. This book examines these changes from an interdisciplinary perspective, combining management studies, innovation research, AI ethics, and enterprise decision-making. Rather than presenting artificial intelligence solely as a technological tool, the volume explores its growing role in shaping organisational structures, managerial practices, and new models of leadership. The chapters discuss integrated AI systems, intelligent process automation, predictive analytics, and AI-supported decision-making across strategic, operational, and financial dimensions. Particular attention is devoted to the appearance of humanoid and virtual leaders, including the cases of Mika, the humanoid CEO, and Tang Yu, the virtual CEO. These examples are used to analyse how AI is increasingly embedded within executive and managerial functions, raising important questions about accountability, transparency, human oversight, explainability, and the future role of managers in organisations. The volume additionally includes an empirical market analysis conducted among 192 enterprises representing sectors such as manufacturing, logistics, finance, trade, technology, and services. The findings illustrate how organisations implement AI technologies, what barriers they encounter, and how intelligent systems influence organisational efficiency, strategic adaptability, customer relations, and innovation processes. At the same time, the book addresses broader organisational and societal implications connected with AI adoption, including workforce transformation, algorithmic bias, governance challenges, and changing forms of human–machine collaboration. Combining theoretical discussion with case studies and practical examples, the volume offers a critical and accessible examination of how artificial intelligence is influencing entrepreneurship, enterprise management, and leadership in the digital economy.
Ida Skubis, Judyta Kabus, Jolanta Wodarska et al.· 0 citations
This chapter examines humanoid and virtual AI leaders as a new model of enterprise decision-making, with particular focus on the cases of Mika, the humanoid CEO of Dictador, and Tang Yu, the virtual CEO of NetDragon Websoft. The analysis investigates how artificial intelligence is increasingly integrated into strategic, operational, and managerial processes, moving beyond a traditional decision-support function towards a more active role in organisational governance. The study applies a qualitative case study methodology based on corporate reports, public statements, interviews, and secondary academic literature. The findings indicate that AI-based leaders may enhance operational efficiency, support continuous data analysis, improve forecasting capabilities, and optimise resource allocation. At the same time, the analysis identifies significant organisational and ethical challenges related to transparency, explainability, accountability, bias, and human oversight. The chapter further discusses the implications of AI-driven leadership for managerial roles, team dynamics, and enterprise governance structures. It is argued that the effective implementation of humanoid and virtual leaders requires human-centric governance frameworks that combine the analytical capabilities of AI systems with human responsibility, ethical judgment, and organisational control mechanisms.
Ida Skubis, Judyta Kabus, Jolanta Wodarska et al.· 0 citations