Investing in Artificial Intelligence (AI) for Business Leaders to Enhance Decision-Making

Introduction

Mouzas and Bauer (2022) stated that businesses, including small and medium-sized enterprises (SMEs), face the potential risk of closure because of the exposure to severe market competition every year. Also, Kharlamova et al. (2019) pinpointed that business closure negatively affects countries' Gross Domestic Product (GDP) and the employment rates of global communities. The disappointment of the labor showcase to assimilate the existing work constraint leads to an increase in the unemployment rates with an impact on hardship and influences the individual's physical and mental well-being. Unemployment leads to weak aggregate demand, and the global economy is more likely to experience a negative gap, with the actual GDPs becoming less than the potential ones. Therefore, analyzing the reasons behind businesses closure gained significant importance to aid economies and communities to continue growing.

Many reasons could lead to business closure. Through exploring a case, Mayr et al. (2020) expressed that researchers analyzed the reasons behind the closure of many businesses and found that the most significant reasons are (a) financial-related reasons, such as struggling cash flow and wrong investment and (b) management-related reasons, such as lack of planning and weak leadership skills. However, the leadership effect might drive the success and failure of the provided reasons. Leaders could not make decisions that help their firms survive the challenging business environments. Decision-making is one of the essential reasons and a critical process that impacts the existence of firms and the continuity of their operations. Lack of persistent efforts, prioritization, and shortage of skilled resources represent critical challenges to firms. Sedky (2021) confirmed that small and medium-sized enterprises (SMEs) are extremely important for economic growth and employment. The European Commission (2019) endorsed the importance of SMEs, demonstrating through its report that SMEs comprise 99.8% of businesses and employ 66.6% of the workforce in Europe. Therefore, decision-making is critical to driving every organization's direction and development.

Leaders should possess the confidence to make decisions that determine organizations' paths. The process of making decisions is not an easy task for business leaders. Leaders need the tools and sufficient data to eliminate risks and assure success, especially when making complex decisions (Newman & Ford, 2020). Artificial Intelligence (AI) could be the tool business leaders need to access firms' data, allowing for a superior view of situations before making decisions. AI has become the technology of choice to spot and solve complex business problems in various industrial sectors where organizations are present (Allal-Cherif et al., 2021; Vrontis et al., 2021). Leaders use AI to collect data, analyze data, and make beneficial decisions that lead their organizations to success through building assumptions and developing business scenarios. However, the lack of knowledge about AI could represent a milestone for leaders to decide to invest in AI. At the same time, the increased risks in critical situations could be the enabler for such an investment. From this perspective, investing in AI could allow organizational leaders to become more capable of making better decisions that enable their firms to succeed and continue operating. Therefore, investing in AI is extremely important to solve organizational problems by enhancing decision-making to ensure firms' success.

In this chapter, the researcher explored the importance of investing in AI for business leaders to enhance their decision-making. The researcher explored previous literature and conducted a qualitative multiple case study that involved the participation of real estate property industry leaders from the United States and the United Arab Emirates (U.A.E.). The researcher relied on Herbert Simon’s decision-making conceptual framework to bridge research gaps (Saunders et al., 2020). The purpose of this chapter is to explore why investing in AI may enhance business leaders' decisions and enable sustaining their firms.