Improvement and automation of business processes with natural language processing and artificial intelligence

This thesis examined the impacts of natural language processing and artifical intelligence Technologies on the automation and improvement of business processes. It explored the integration of AI and NLP tecnologies into business processes, focusing on areas such as process automation, the development of decision support systems, and the execution of repetitive tasks without human intervention. In this context, the potential of AI models to structure process flows, support data driven decision making, and optimize processes are evaluated. Additionally, the role of NLP in process improvement through the analysis of language based data is highlighted. The thesis supported these discussions with case studies demonstrating the benefits of these techbologies across various sectors and companies, analyzing how AI is utilized in data intensive and knowledge driven processes to enhance decision makinh. In this scope, the current applications, opportunities, and potential improvement areas offered by NLP and AI technolohies in business processes are investigated. Furthermore, a practical application example focused on call center process management is included. This case study showed how AI and NLP based solutions can be leveraged to classify, respond to and direcy customer requests, enhancing call center processes and optimizing workflow. The study detailed how process autiomation contributes to overall efficiency in call center operations