AI Driven Chatbots
Kumar, Vishal (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025121938702
https://urn.fi/URN:NBN:fi:amk-2025121938702
Tiivistelmä
The customer service development and application of artificial intelligence-based chatbots is examined in this literature-based thesis, that only reviews the years after 2022. What a sophisticated AI-based chatbots have changed customer service processes, customer experience and the role of human agents in industries such as ecommerce, SaaS support, call centres and maintenance services. 2025. Four research questions covering technological change, operational impacts, domainspecific applications, and future developments serve as the compass of this study. It follows the IMRaD pattern.
At least 50 reports and 10 papers, more than fifteen excellent blog posts and case studies from manufacturers and analysts, and peer-reviewed journal and conference articles from ACM, IEEE, and ScienceDirect provide systematic literature reviews of the method (BCG, 2024; Chintalapudi, 2025; Gartner, 2023). The theoretical foundation includes human-AI interaction, trust, and customer satisfaction, as well as contemporary chatbot designs such as LLMS, retrieval augmented generation (RAG), and agent frameworks (Chang et al., 2024; Chen et al., 2023; Ferraro, 2024).
Five functional systems—Klarna AI Assistant, Intercom Fin, Google Contact Center AI (CCAI), Salesforce Einstein/Agent force for Service, and AI-driven generative maintenance SOLUTIONS in automotive and airline environments—were scrutinized for results (BCG, 2024; Engeman, 2025; McKinsey & Company). These systems offer features such as proactive and predictive service, real-time assisted demo support by human agents, autonomous resolution of routine problems, and deep integration with CRM and operational data (BCG, 2024; Premier Cloud, 2025). Along with additional risks such as hallucinations, transparency concerns, and worker distraction, studies show significant improvements in productivity, resolution time, and customer loyalty (Ferraro, 2024; Yang et al., 2023).
According to the discussion, AI chatbots will become central “service agents” rather than peripheral accessories. They are likely to have more proactive, multimodal and personalized interactions in the future, supported by stronger governance and continuous human design (BCG, 2024; McKinsey & Company, 2024).
At least 50 reports and 10 papers, more than fifteen excellent blog posts and case studies from manufacturers and analysts, and peer-reviewed journal and conference articles from ACM, IEEE, and ScienceDirect provide systematic literature reviews of the method (BCG, 2024; Chintalapudi, 2025; Gartner, 2023). The theoretical foundation includes human-AI interaction, trust, and customer satisfaction, as well as contemporary chatbot designs such as LLMS, retrieval augmented generation (RAG), and agent frameworks (Chang et al., 2024; Chen et al., 2023; Ferraro, 2024).
Five functional systems—Klarna AI Assistant, Intercom Fin, Google Contact Center AI (CCAI), Salesforce Einstein/Agent force for Service, and AI-driven generative maintenance SOLUTIONS in automotive and airline environments—were scrutinized for results (BCG, 2024; Engeman, 2025; McKinsey & Company). These systems offer features such as proactive and predictive service, real-time assisted demo support by human agents, autonomous resolution of routine problems, and deep integration with CRM and operational data (BCG, 2024; Premier Cloud, 2025). Along with additional risks such as hallucinations, transparency concerns, and worker distraction, studies show significant improvements in productivity, resolution time, and customer loyalty (Ferraro, 2024; Yang et al., 2023).
According to the discussion, AI chatbots will become central “service agents” rather than peripheral accessories. They are likely to have more proactive, multimodal and personalized interactions in the future, supported by stronger governance and continuous human design (BCG, 2024; McKinsey & Company, 2024).
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