In today's era, small and medium-sized enterprises (SMEs) encounter the unique challenge of effectively utilizing cloud computing for business expansion while also aligning their operations with the increasing focus on Environmental, Social, and Governance (ESG) considerations. To address this convergence, this thesis proposes an approach to help SMEs make informed choices when selecting cloud computing service providers by integrating ESG criteria. It introduces a Generative AI Chatbot powered by Large Language Model that aims to offer real-time decision support to SMEs. A large language model (LLM) is an advanced computer software that mimics human language in both understanding and expression. It processes huge amounts of text from many sources to learn via artificial neural networks, which function similarly to a virtual brain. Without specific human instruction, LLMs perform exceptionally well at understanding and generating a wide range of linguistic patterns. The main objective of this study is to create a chatbot powered by generative AI that helps SMEs to make better decisions. This chatbot will enable SMEs to ask questions, analyze, and use ESG data when choosing cloud service providers. This will help them make ethical and well-informed choices that promote sustainability. This technology makes use of LangChain, an open-source framework that lets software developers integrate external components with large language models, such as OpenAI's GPT-3.5, to create LLMpowered machine learning and artificial intelligence (AI) applications to give SMEs immediate access to customized insights and advice regarding the ESG relevant information of different cloud computing service providers.

The research begins with a thorough analysis of the state-of-the-art literature, examining the value of ESG criteria in the context of cloud computing, the special difficulties SMEs experience in the provider selection process, and the evolving use of AI-driven Chatbots in decision support. Then, a thorough research process is applied, following the Design Science Research Method, including stakeholder interviews with experts from SMEs, experts in Cloud Computing, and experts in sustainability, an in-depth analysis of ESG, and the creation of a cutting-edge generative AI Chatbot-driven decision support system. The system's use, accuracy, and effectiveness are extensively examined through iterative Prototype testing. This evaluation process includes further evaluation through interviews with a specialist in AI Chatbot, and potential end-user tests were conducted. By providing SMEs with a tool that helps to direct them toward cloud computing service providers who are in line with their ESG goals and so encourage ethical business practices and sustainable development, this research aims to support the SMEs' long-term growth. It bridges the gap between business, technology, and sustainability, giving SMEs the chance to improve their methods of making decisions in the age of cloud computing, when ESG considerations are crucial.

For SMEs, the conclusions and recommendations presented in this thesis are a valuable resource, giving them access to a smart AI-driven tool that can answer their queries and help create a more moral and sustainable business environment.