AI implementation within organizations. A systematic literature review

Artificial intelligence (AI) is currently viewed as the most important and disruptive technology for organizations. Rapid progress and advancements in AI have captured the attention of both researchers and practitioners, unlocking many opportunities for its integration into organizations. The advantages of AI applications are extensive and span various domains with far-reaching possibilities. AI has been demonstrated to be effective in unmanned vehicles, medical diagnosis, transport and air traffic management, and environmental sustainability. However, as AI continues to be integrated into various aspects of society, its potential to reshape the way organizations operate cannot be underestimated. Thus, understanding the potential effects of AI is crucial for informed decision making and responsible deployment in organizations worldwide. The aim of this work is to detail the current challenges and implications that might arise from AI applications and to highlight ways to overcome such challenges to realize the potential of this emerging technology. First, this paper provides a brief history of AI and an overview of AI typologies. To map the state of the art, consolidate the heterogeneous corpus of knowledge, investigate the current impacts on organizations of AI technology, and provide insight into the possible challenges and risks associated with this technology, applying a methodological approach based on a systematic review of the literature conducted with the PRISMA method and a third type of content analysis. The research findings highlight various AI application areas, outlining their value-creation and operational mechanisms, thereby offering an overview of the most popular artificial intelligence techniques used within organizations. Moreover, the results shed light on different topics attributable to three themes: enablers, challenges, and AI systems. This study highlights the potential implications of AI within organizations, emphasizing the need for multidisciplinary research, collaboration, and ongoing assessment to ensure that AI applications align with organizational values and goals. The analysis provides researchers and practitioners with a meaningful overview of the body of knowledge to exploit AI as an effective enabler of value creation within organizations. Finally, a research agenda is proposed to guide the directions of future AI research in private sector addressing the identified trends and challenges.