Implementation of artificial intelligence in companies: Benefits,challenges and strategies

This thesis analyzes the level of maturity and approaches to the implementation of artificial intelligence (AI) in selected Czech companies with an emphasis on generative models. The theoretical part of the thesis defines key terms, places the issue in the context of international AI maturity models (Gartner, McKinsey, LXT), and describes aspects of strategic management, governance, and the EU AI Act legislative framework. The practical part deals with a comparative analysis of eight companies of different sizes and industry focus, ranging from technology startups to multinational corporations, with the identities of three entities anonymized for the protection of sensitive data. In the introduction, the author defines two hypotheses, the validity of which is verified in the practical part. For this purpose, qualitative research is carried out in the form of comparative case studies based on semi-structured interviews with key stakeholders, analysis of internal documents, and comparison with expert opinions. The partial result of the thesis is: a) Confirmation of hypothesis number 1, that organizations with a formal strategy and centralized management show a higher level of security, but achieve longer deployment times than companies with a decentralized approach. The results show a direct correlation between the degree of formalization of governance and the length of the innovation cycle. b) Confirmation of hypothesis number 2, that technology companies build AI competencies organically in-house, while traditional non-technology companies prefer strategic partnerships with external suppliers. The research identified a fundamental difference in the approach to building competencies depending on the technological focus of the company. A key finding of the study is that there is no universal recipe for success, but effective adoption requires alignment of strategy with company culture. Based on identified barriers, such as data quality or the absence of project lifecycle management, the author has developed a set of practical recommendations for managers in the areas of strategy, governance, and processes. Similarly, the conclusion of the work provides detailed answers to the research questions and discusses the limits of qualitative research.