Leveraging Artificial Intelligence (Ai) for the Enhancement of Business Processes Performance

Thesis title: Leveraging Artificial Intelligence (Ai) for the Enhancement of Business Processes Performance
Author: Kánovics, Jakub
Thesis type: Diploma thesis
Supervisor: Špaček, Miroslav
Opponents: Rejthar, Stanislav
Thesis language: English
Abstract:
The master thesis develops and defines a fundamentally improved business process of face-to-face communication analytics with the utilization of AI, ML, and NLP as means of improving the business process performance. To achieve so, from the theoretical point of view, the paper delves into various aspects of artificial intelligence through an extensive literature review. On the other hand, from the practical point of view, the paper analyzes numerous business processes utilizing AI-driven text and call analytics using business process modelling. Additionally, the paper provides practical insights into AI-driven analytics for driving sales and customer experience through a qualitative study consisting of semi-structured interviews and case studies. By the end of the master thesis, readers will have a comprehensive understanding of the AI, ML and NLP technology, and text and call analytics, with the ultimate goal of proposing author’s solution of a fundamentally improved business process of face-to-face communication analytics utilizing AI technology.
Keywords: sales; analytics; artifical intelligence; business process performance; customer experience
Thesis title: Leveraging Artificial Intelligence (AI) for the Enhancement of Business Processes Performance
Author: Kánovics, Jakub
Thesis type: Diplomová práce
Supervisor: Špaček, Miroslav
Opponents: Rejthar, Stanislav
Thesis language: English
Abstract:
The master thesis develops and defines a fundamentally improved business process of face-to-face communication analytics with the utilization of AI, ML, and NLP as means of improving the business process performance. To achieve so, from the theoretical point of view, the paper delves into various aspects of artificial intelligence through an extensive literature review. On the other hand, from the practical point of view, the paper analyzes numerous business processes utilizing AI-driven text and call analytics using business process modelling. Additionally, the paper provides practical insights into AI-driven analytics for driving sales and customer experience through a qualitative study consisting of semi-structured interviews and case studies. By the end of the master thesis, readers will have a comprehensive understanding of the AI, ML and NLP technology, and text and call analytics, with the ultimate goal of proposing author’s solution of a fundamentally improved business process of face-to-face communication analytics utilizing AI technology.
Keywords: business process performance; customer experience; artifical intelligence; analytics; sales

Information about study

Study programme: Management
Type of study programme: Magisterský studijní program
Assigned degree: Ing.
Institutions assigning academic degree: Vysoká škola ekonomická v Praze
Faculty: Faculty of Business Administration
Department: Department of Entrepreneurship

Information on submission and defense

Date of assignment: 28. 11. 2023
Date of submission: 15. 5. 2024
Date of defense: 10. 6. 2024
Identifier in the InSIS system: https://insis.vse.cz/zp/86711/podrobnosti

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