Abstract:
This thesis covers the transformative role of Artificial Intelligence (AI) within the e-commerce sector, highlighting how technologies such as machine learning, natural language processing, and large language models have reshaped both operational processes and consumer interactions. Building on existing literature, it illustrates how AI-driven personalisation, real-time analytics, and predictive modelling contribute to more efficient inventory management, targeted marketing, and enhanced customer service. The research also addresses the crucial balance between leveraging advanced data-processing capabilities and maintaining consumer trust, underscoring the importance of robust privacy and security measures.
By examining practical use cases, ranging from intelligent product recommendations and AI chatbots to predictive demand forecasting, the thesis demonstrates how AI applications elevate customer experiences and foster greater business efficiency. It also acknowledges challenges such as technical complexities of system integration, potential ethical concerns, and the need for strategic alignment between AI innovations and organisational goals. Empirical evidence gathered through qualitative interviews with industry experts forms the basis for deeper insights into the interplay between AI technologies, consumer expectations, and the dynamic competitive landscape of online retail.
This thesis ultimately provides a nuanced perspective on AI’s capacity to drive innovation and streamline e-commerce operations. It points to emerging trends like hyper-personalisation, advanced sentiment analysis of user reviews, and evolving chatbot dynamics, all of which signal a continuously shifting frontier for businesses seeking to stay at the cutting edge of digital commerce. The findings underscore that while AI offers substantial benefits in terms of scalability, efficiency, and customer engagement, a deliberate, ethically aware approach is vital to ensure sustainable success in the fast-evolving world of e-commerce.
