Integrating AI in business: benefits, challenges, key capabilities, and managerial solutions for a successful implementation

Abstract

Artificial Intelligence is one of the most advanced technologies that is completely revolutionizing the way businesses operate. This technology is characterized by important benefits, but it also implicates challenges and high complexity in its implementation, for which skills and competencies are required. The main objective of this paper is to analyse, through a structured literature review, both advantages and challenges associated with the implementation of AI. In addition, practical implications for decision-makers and the required capabilities to make the adoption less complicated will be discussed. Organizations are constantly searching for ways to enhance their overall performance, particularly through better decision-making and Artificial intelligence (AI) stands out as a crucial technology that enables these improvements. According to Statista (2024), the global market value of this branch of computer science is anticipated to increase significantly by 2030 to US$826 billion compared to its US$184 billion valuation in 2024. This trend shows that companies will keep investing in this technology with the goal of not losing market share and competitive momentum. Artificial intelligence (AI) can simulate, without guidance, human intellect and has benefits such as higher productivity, improved customer service, and cost reduction. This technology is also seen as a clever solution to comprehend better the internal and external aspects of an organization, which will increase the ability to make decisions for companies in a variety of industries, including banking, automotive, communication, healthcare, and information management. But despite the great advantages of AI, some downsides complicate its implementation and effectiveness within a company. In fact, although companies made significant investments, most of them have shown little to no return. Merely investing in technology is not enough to make a business competitive as they also need to create knowledge and a company culture around this new technology. Other drawbacks such as risks to security and privacy, and the results of prejudices, abuse, and false information have to be taken into consideration and for this reason, businesses must first develop AI capabilities that focus on the moral application of AI. Furthermore, the implementation of AI could be complicated due to the presence of barriers such as organizational resistance for which employees are reluctant to adopt it for the fear of losing their job or the case where the management is skeptical about giving over decision-making authority to AI. In this paper, practical implications that managers should adopt to implement AI successfully such as trainings are mentioned. Integrating AI, it’s in fact a complex process for which the workforce should comprehend as much as possible how AI systems work. It’s also critical to create a company culture that facilitates the adoption of AI by convincing employees that the AI systems are compatible with the systems already used in the company and that they are not a threat. The second part of this thesis will be dedicated to a case study about a branch of Artificial intelligence that is attracting always more attention, Generative AI.