AI Adaptability and Customer Satisfaction in Telecom Complaint Handling: The Mediating Role of Customer Psychographics and Perceived Usefulness

This paper seeks to examine the effects of AI flexibility on customer satisfaction in complaint management in telecoms, with special emphasis on the mediating role of the customer psychographics and the perceived usefulness. The use of AI technologies is becoming common in customer service systems so far as to enhance efficient operations and ensure that complaints are handled in a timely manner. Nonetheless, the differing attitude of customers, level of technological readiness and patterns of lifeways are key factors in establishing the effectiveness of AI solutions on perception. The research is quantitative and uses the technique of structured surveys and performance measurement to obtain information on telecom customers belonging to a wide demographic range. Regression and structural equation modeling (SEM) statistical models are going to be used to observe correlations between variables and support the conceptual framework. The study will also enhance the knowledge to achieve a better level on how AI adaptability factors in the perception of trust, the perceived service aptitude and the general client thermal conscience, amongst others and it will also enlighten the barriers like lack of emotional intelligence, fear of the breach of data privacy, refusal to embrace the concept. This empirical research will enable telecom enterprises to develop AI-based systems to manage complaints efficiently and proactively such that they are not merely efficient but also customer friendly to win their loyalty in the long term and adopt a sustainable business model.