Strategic Decision-Making: Implementing Artificial Intelligence for Customer Experience in XYZ Electricity

Abstract

This case study outlines the challenges in resolving customer complaints at XYZ electricity provider, where the industry achieves only 89.16% against a 100% service level agreement, leading to poor customer experience (CX). The objective of this paper is not only to identify the root causes of poor CX and validate artificial intelligence (AI)’s potential role as a solution, but also to pioneer the identification of critical success factors (CSFs) and strategic areas for AI implementation, leveraging computational ratings to enhance decision-making processes. This research employs comprehensive data collection methods, including primary data from interviews and workshops involving 300 participants and secondary data from observation and literature studies. It utilizes an integrative strategy framework (ISF) to strategically synthesize internal and external analyses. Additionally, it ranks critical areas for AI implementation using the analytic hierarchy process (AHP) based on pairwise judgment and Likert scale surveys from ten experts. The most significant findings reveal that direct impact on customers, at 28.54%, is the strongest CSF, while customer service, 14,63%, is the most impactful implementation of AI in the XYZ to fix poor CX. A pilot project on customer service can improve CX, revenue, and cost savings. The authors suggests that another researcher implement and evaluate AI in various businesses and specific client categories.