Sep 2026· International Journal of Creative and Open Research in Engineering and Management· 0 citations
AI in Service Interactions
Abstract
Customer experience has become a key differentiator for organisations operating in increasingly digital markets, and Artificial Intelligence (AI) is now widely used to make digital marketing faster, more personalised and more responsive. This study examines the role of AI in enhancing customer experience in digital marketing, with special reference to SSR Compressor Service, an industrial air-compressor sales and service organisation based in Chennai. The study adopts a quantitative, descriptive and analytical cross-sectional research design. Primary data were collected from 31 respondents through a structured questionnaire covering four composite constructs — AI accessibility and use (QTotal), AI-enabled personalisation and interaction (ATotal), responsiveness and convenience (CTotal), and overall customer experience (ETotal) — and analysed using descriptive statistics, Pearson correlation, multiple linear regression, and Cronbach’s alpha reliability testing. All four composite measures were positively and significantly correlated with one another (r = .615 to .892, p < .001). A multiple regression of the three predictor composites on overall customer experience was statistically significant, F(3,27) = 28.626, p < .001, explaining 76.1 percent of the variance (R² = .761, Adjusted R² = .734). CTotal (Beta = .640, p < .001) and ATotal (Beta = .565, p = .022) emerged as significant unique predictors of customer experience, while QTotal did not retain a significant unique effect once the overlapping variance among the predictors was accounted for. Reliability testing confirmed good internal consistency across all scales (alpha = .730 to .869). The findings suggest that AI can meaningfully enhance digital customer experience when it is implemented as a supporting technology built around personalisation, convenience and responsiveness rather than as a replacement for human interaction, and the study offers practical recommendations for SSR Compressor Service and similar industrial businesses.
Keywords: Artificial Intelligence; Digital Marketing; Customer Experience; Personalization; Chatbots; Customer Engagement; Trust.
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