DECISION MAKING BY PRIORITIZING IMPLEMENTATION OF GEN AI (GENERATIVE ARTIFICIAL INTELLIGENCE) FOR ENHANCING CUSTOMER EXPERIENCE IN PT PLN (PERSERO)

• Main Author: IFM Pasaribu, Puspa
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/83996
• Institution: Institut Teknologi Bandung

Artificial intelligence (AI), specifically GEN AI, has turbocharged business development processes and services, which drives companies to improve and develop improvements and new business models. A developed business model positively impacts users and researchers, speeds up business processes, generates benefits for management, and creates value for customer satisfaction. In 2022, the worldwide AI market had a value of USD 454.12 billion. It is projected to reach around USD 2,575.16 billion by 2032, with a compound annual growth rate (CAGR) of 19 % from 2023 to 2032. In 2022, North America accounted for around 36.84 % of the market share. From 2023 to 2032, the Asia-Pacific market is projected to have the highest Compound Annual Growth Rate (CAGR) of 20.3 %. AI has been applicable to improve several industries such as healthcare for musculoskeletal imaging, automotives, banking, finance, manufacturing, agrifood, aerospace, retail, and many more. The bulk of sectors have traditionally relied on technological breakthroughs. The adoption of AI in energy firms is clearly extending to many areas of the energy sector, including energy transformation, digital transformation, integration, and the reciprocal impact across diverse sectors of energy and transportation. PT PLN (Persero) can enhance customer experience (CX) by improving operational performance, productivity, customer satisfaction, and support function transformation with the rapid growth of AI technologies, particularly Gen AI. CX drives growth, profitability, and success. The company plans to utilize the advancements in AI technology to enhance the CX across value chain such network, customer, and support function. Despite the clear strategic plan, the transition to a more AI-integrated CX has encountered practical challenges, particularly in scaling up the technology to meet the high volume and diverse nature of customer interactions. Currently, the company is struggling to handle an increasing number of customer complaints. Recent bad performance yielded a score of 89.16% out of a possible 100% and left the customer with a negative experience. ii To fix bad performance, the author conducted an exploratory research method and managed to identify eight areas of improvement to implement AI from the Focus Group Discussion (FGD). The author focuses on decision making among those areas after synthesizing the most impactful critical success factors (CSFs) for successful implementation. Thus, CSFs must be elaborated to ensure implementation success since there is insufficient understanding and a lack of research on improving CX for electricity companies from the previous studies, and this company’s bad performance must be fixed. Therefore, the author called for research and conducted qualitative research to assess whether AI is the solution to overcome bad performance and quantitative research to assess CSFs and narrow down areas of improvement to implement AI. This paper addresses the request and confirms the effectiveness of AI as a solution, critical success factors for power companies, and areas that may be improved. Additionally, it enhances these findings by using a more rigorous approach, utilizing the Analytic Hierarchy Process, also known as AHP, to statistically evaluate decision makers' priority. This evaluation is conducted with the assistance of ten expertise. The results of the analytic hierarchy method may provide guidance and support to decision leaders in determining the order of activities, maximizing the use of resources, and ensuring that they are in line with the strategic goals of the eight areas of improvement. The AHP involves categorizing, assessing, and ranking certain areas based on the examination of outcomes related to Critical Success Factors (CSFs) that are impacted by CX. The author identifies critical challenges and strategic opportunities using Fishbone/Ishikawa diagrams, Pareto charts, value chain analysis, PESTEL analysis, and SWOT analysis. An Integrative Strategy Framework (ISF) synthesizes internal and external strategic analyses. Finally, using the AHP and Likert scale, the study ranks AI implementation improvement areas. The research's most significant finding is direct impact on customers (Direct Impact to Customer) is the top criterion, at 28.54%, for AI implementation to improve CX. Customer service support is the top alternatives at 14,63% as the highest-impact to customer among other areas of improvement can boost CX, electricity company revenue, and operational efficiency.