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Machine Learning Analysis of Chatbot Adoption: Efficiency, Accessibility, and Environmental Benefits in Tourism

Students & Supervisors

Student Authors
Sumit Paul
Bachelor of Science in Computer Science & Engineering, FST
Tohomina Rahman Tisha
Bachelor of Science in Computer Science & Engineering, FST
Fariha Farhad
Bachelor of Science in Computer Science & Engineering, FST
Mahdi Hassan Noor Asif
Bachelor of Science in Computer Science & Engineering, FST
Tamim Hasan Apurbo
Bachelor of Science in Computer Science & Engineering, FST
Supervisors
Md. Mortuza Ahmmed
Associate Professor, Faculty, FST

Abstract

This paper uses machine learning-based time-series and forecasting analysis to study the adoption of AI-powered chatbots in the tourism sector of Bangladesh during the period of 2015 to 2024 as it relates to productivity, accessibility, and environmental sustainability using secondary adoption and usage data. The results suggest a transformative virtuous circle with Bengali Natural Language Processing (NLP) integration becoming an essential variable that is related to faster rates of chatbot adoption, which are expected to reach about 95 percent in 2024 with a stabilizing effect in the following years (r ≈ 0.99). In addition to improving operational efficiency, this localization-first strategy shows strong correlations with cost savings (r = 0.92) and user satisfaction (r = 0.98). Importantly, the study identifies an empirical association between chatbot deployment and measurable environmental benefits, revealing a strong correlation with estimated carbon emission reductions, amounting to over 6,000 tCO₂e by 2024 (r = 0.89). The COVID-19 pandemic is observed as a contextual catalyst that accelerated the simultaneous adoption of contactless services and environmentally sustainable operational practices. By demonstrating that targeted and localized AI deployment can simultaneously support economic, social, and environmental objectives, this study contributes empirical insights relevant to sustainable tourism innovation in developing countries. The findings further propose a reproducible analytical framework for evaluating AI-driven sustainability outcomes in comparable tourism contexts.

Keywords

AI Chatbots Sustainable Tourism Natural Language Processing (NLP) Tourism Digitalization Bangladesh Tourism.

Publication Details

  • Type of Publication:
  • Conference Name: International Conference on Business Innovation and Sustainable Development (ICBISD 2026)
  • Date of Conference: 29/01/2026 - 29/01/2026
  • Venue: Varendra University, Rajshahi, Bangladesh
  • Organizer: Department of Business Administration, Varendra University, Bangladesh.
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