Integrating Artificial Intelligence (AI) and Fuzzy Multi - Criteria Decision-Making for Strategic Organisational Performance Optimization

Abstract

The application of Artificial Intelligence (AI) in decision-making processes is changing the way organizations approach and make decisions.Organizations are increasingly turning to Artificial Intelligence (AI) to analyze complex data, detect trends, predict outcomes, and consider various options in their decision-making process. Organisation performance assessment, however, encompasses numerous both qualitative and quantitative criteria, uncertainty, conflicting priorities of management and imprecise expert opinions – which cannot be fully captured by conventional decision making techniques. This study presents a new AI assisted Fuzzy Multi-Criteria Decision-Making (F-MCDM) model to assess the performance of an organization and to assist in making strategic management decisions. The proposed framework is based on the use of AI-based analytical capabilities and fuzzy decision-making techniques that can handle the vagueness of managerial assessments and prioritize strategic options in a systematic manner. The relative importance of organisational performance criteria are determined by using the fuzzy Analytic Hierarchy Process (FAHP), and the fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) is used to rank the strategic alternatives. It looks at aspects such as financial performance, operational efficiencies, innovation capability, customer orientation, human-resource effectiveness, and strategic adaptability as well as digital capability. The aim of the proposed approach is to enhance the decision consistency, transparency of decision making, strategic alignment and managerial responsiveness. The study illustrates that AI and fuzzy MCDM are able to offer an intelligent decision-support mechanism to organisations in an uncertain and competitive environment.