The paper does not explicitly identify specific technical or domain challenges (analysis #23411)

The gap

Evidence profile

Sourced from the recommendations and future-work section and stated challenges of the source papers, classified as general, drawn from work published between 2025 and 2026, spanning 3 journals. Those papers have been cited 36 times in total.

Supporting evidence — 4 representative gaps

• Persuasive Marketing Intelligence in Supermarket Kiosk Agents: Extending an Intelligent Receptionist System for Context-Aware Recommendations (2026) · International Journal of Creative and Open Research in Engineering and Management · doi

  in-store customer should be processes without interaction interruptions. The operational scalability of the system is supported with the ability to become a complementary tool assisting the staff instead of substituting them. As the implementation shows, an intelligent intent classification that is combined with structured retail information may make the processes more efficient and help in the optimization of revenues in a physical retail context [8]. The rest of this paper addresses related work, system the architecture, methodology, implementation, and performance evaluation of the suggested framework of the conversational kiosk. details the of through systems are aimed at enhancing the flexibility and interactivity with customers the use of automation technologies [3]. Service robots based on the use of large language models are also presented in the environment of the shopping mall to make a better user interaction and give a contextual assistance [6]. These applicability of systems portray conversational AI in offline retail environments. increasing the language model and NLP-based customer service systems have gone a step higher to enhance automated query processing through ranking pre-trained system [4]. The literature has also investigated AI customer service software in the localized settings including healthcare and online shopping platforms where it has shown to be more user-satisfied and efficient with intelligent automation [7], [8]. response Moreover, chat agents that cater to the needs of e- commerce settings have revealed that automated chat systems can be useful in answering questions raised by customers as well as to aid in online-shopping choices [9], [10]. Most of such implementations however are more of virtual or online providing than the physical setting supermarket. shows literature efficacy of the

  generalrecommendationsevidence 5/5
  Keywords: systems customer system retail service shopping online processes interaction implementation shows intelligent make efficient physical
• Effectiveness of AI Chatbots and Conversational Commerce on Customer Loyalty in the Indian Retail Sector: A Study on Reliance in Chhattisgarh (2026) · Iconic Research and Engineering Journals · doi

  including expanding multilingual support, implementing proactive engagement strategies, and strengthening privacy protections. The research demonstrates that AI function as bridges between operational chatbots efficiency and relationship-building, requiring strategic balance between automation and human empathy to sustain long-term customer relationships in the Indian retail context. providing optimizing chatbot retail, for enhance customer engagement and service delivery. This technological shift represents a fundamental reorganization of customer interactions, moving from traditional transactional models to conversational, relationship-based commerce enabled by messaging platforms and AI-powered conversational agents. Reliance Retail, India's largest organized retailer (groceries, operating across multiple segments through fashion, electronics, digital commerce) platforms such as JioMart, AJIO, and Reliance Digital, has emerged as an early adopter of AI chatbot technology. The company's Smartbot, accessible via WhatsApp and other messaging channels, handles substantial customer interaction for product volumes, providing 24/7 support personalized searches, recommendations, resolution. Conversational commerce, defined as the use of messaging platforms, chat interfaces, and voice assistants to facilitate customer-brand interactions during the purchasing process, has demonstrated significant customer to engagement, conversion rates, and loyalty metrics globally. In the Indian market specifically, the prevalence of WhatsApp (over 400 million users) and other messaging creates unique applications opportunities for conversational commerce, as many consumers prefer chat-based interfaces to traditional e-commerce websites. complaint tracking, potential improve order and Keywords: AI Chatbots, Conversational Commerce, Customer Loyalty, Brand Trust, Reliance Retail, Indian Retail Sector, Technology Acceptance I. INTRODUCTION The Indian retail sector is undergoing rapid digital transformation, with businesses increasingly adopting artificial intelligence and chatbot technologies to II. LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK

  generalrecommendationsevidence 5/5
  Keywords: customer retail commerce conversational indian messaging engagement chatbot platforms reliance digital support chatbots relationship providing
• Navigating the Digital Frontier: Exploring the Dynamics of Customer–Brand Relationships Through AI Chatbots (2025) · Sustainability · cited 18× · doi

  Future studies could investigate the role of AI chatbots in industries beyond customer service, such as healthcare, education, and entertainment. Studies must deeply explore how cultural norms, values, and demographic diversity influence user acceptance and satisfaction. Experimental studies could manipulate chatbot features to assess their direct impact on customer-brand relationships. Future research could employ a longitudinal study to track changes in customer perceptions as they interact with AI chatbots.

  generalfuture-work sectionevidence 5/5
  Keywords: future studies investigate role chatbots industries beyond customer
• Navigating the Digital Frontier: Exploring the Dynamics of Customer–Brand Relationships Through AI Chatbots (2025) · Sustainability · cited 18× · doi

  The paper does not explicitly identify specific technical or domain challenges, but it highlights the need to understand how AI chatbots can facilitate responsible business practices and promote digital sustainability. The study notes the importance of optimizing digital interactions and reducing resource-intensive human support. The researchers emphasize the need for businesses to design AI-driven chatbot systems that improve customer experience and align with sustainable digital transformation efforts.

  generalstated challengesevidence 5/5
  Keywords: paper does explicitly identify specific technical domain challenges

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