Affiliation:
1. Driehaus College of Business, DePaul University, Chicago, IL, USA
2. College of International Studies, Kyung Hee University, Yongin, South Korea
Abstract
This research seeks to determine whether IT leaders are willing to leverage Artificial Intelligence (AI) recommendations to augment their decision-making when considering which IT projects to select based on the projects’ contribution towards organizational goals and objectives and the IT leaders’ level of knowledge and trust in AI. The research design utilized a quantitative survey of 113 IT leaders to understand their willingness to accept AI recommendations that augment their own decision-making while considering organizational criteria for selecting the best IT projects to invest in. AI recommendations were measured based on factors contained within a conceptual AI-driven online recommendation system, while decision-making was measured based on factors such as uncertainty, consequences of decisions, information & goals, motivation, and self-regulation that were designed and validated to examine certain aspects that influence decision-making. IT project contributions were measured based on relevance, risk, reasonableness, basis research return, and business return associated with the project. The research results showed the relationship between IT Project Contributions and IT leader decision was significant in that the leader's perception of IT project contributions towards organizational goals and objectives has a positive influence on the IT project selection decision. Unfortunately, the remaining hypothesized relationships showed no significant outcomes. The research results did not show that IT Leader Decisions may be influenced by AI recommendations, nor the greater knowledge of AI an IT Leader has, the stronger the relationship will be in support of or against AI recommendations, nor that the greater trust in AI an IT Leader has, the stronger the relationship will be in support of or against AI recommendations. This research will provide important insights to understand IT project selection and human-AI collaboration by IT leaders in organizations.