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@article{199604,
        author = {Aaditi Sarode and Ragini Marathe and Pallavi kandalkar and Sakshi badgujar},
        title = {Evaluating the Trust-Efficiency Trade-off Between AI Chatbots and Human Service Agents: A Systematic Review and the CADE Deployment Framework},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {14696-14702},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199604},
        abstract = {Artificial intelligence-powered conversational agents have gained significant adoption across service sectors including healthcare, retail, and education. These systems deliver measurable operational improvements resolution speeds three to five times greater than human personnel and cost reductions of 60 to 80 percent per transaction yet they raise ongoing concerns regarding perceived reliability, emotional inadequacy, and erosion of user trust. This paper presents a structured review of peer-reviewed literature to characterize the fundamental tension between service efficiency and trustworthiness when comparing automated and human agents. An accompanying pilot survey of 9 participants across diverse service scenarios empirically quantifies trust and efficiency preferences. The synthesis informs the proposed Context-Aware Deployment Model (CADE), which classifies incoming service interactions along task complexity and sensitivity dimensions. CADE advances the field by replacing binary deployment approaches with a context-sensitive hybrid allocation framework. Larger-scale validation is recommended as future work.},
        keywords = {AI chatbots, context-aware deployment, human-AI interaction, service efficiency, user trust, hybrid systems, pilot study},
        month = {April},
        }