The unique contribution of this book is to draw attention to the possibilities resulting from conducting transdisciplinary research and drawing on the rich achievements in the field of research development on knowledge-based systems that can be used to holistically support the processes of planning, evaluation and project management.
Although some people had considerable doubts about the usefulness of such solutions in the past, AI plays a growing role in modern business. It can be expected that the interest in it will also lead to an increase in supporting the planning, evaluation and implementation of projects. In particular, the proper functioning of multifaceted evaluation methods has a crucial impact on the appropriate planning and execution of various types of projects, as well as the effective achievement of the organization's goals. This book offers a presentation of complex problems and challenges related to the development of AI in project management, proposing an integrated approach to knowledge-based evaluation and indicating the possibilities of improving professional practical knowledge in this field.
The unique contribution of this book is to draw attention to the possibilities resulting from conducting transdisciplinary research and drawing on the rich achievements in the field of research development on knowledge-based systems that can be used to holistically support the processes of planning, evaluation and project management. The concept of the integrated approach to knowledge-based evaluation is presented, developed as a result of drawing inspiration from the systems approach, praxeology and selected AI mathematical models.
Presented in a highly accessible manner, the book discusses mathematical tools in a simple way, which enables understanding of the content by readers across broad subject areas who may be not only participants of specialist training and university students but also practitioners, consultants, or evaluators. Supported by pedagogical features, this book will be a valuable resource for academics and upper-level students in particular across project management related fields and of great interest to all those looking to understand the challenges and effectiveness of AI in business.
1 Introduction
2 AI in Business
2.1 The Essence and Potential of Artificial Intelligence
2.2 Machine Learning and Neural Networks
2.3 Generative AI in Organizations
2.4 Rough Set Models
2.5 Knowledge-Based Systems
3 Selected AI Applications in Project Management
3.1 Data-Driven Project Management
3.2 Generative AI in Modern Project Management
3.3 Learning Models for Project Evaluation
3.4 Applications of Rule-Based Systems
3.5 Methodological Approaches for Multicriteria Knowledge-Based Project Analysis
4 AI-Driven Knowledge-Based Evaluation
4.1 Preliminary Comments about Evaluation System Modeling
4.2 Integrated Approach
4.3 Knowledge Discovery Through Learning
4.4 Combining Rule-Based Systems and Generative AI
4.5 Building and Assessing AI-Powered Knowledge Base
4.6 Using Knowledge-Based Evaluation Systems
5 Conclusions
Tadeusz A. Grzeszczyk is Associate Professor in the Faculty of Management at Warsaw University of Technology, Poland. He engages in scientific and didactic activities focused on scientific research methodologies, encompassing qualitative, quantitative, and mixed methods approaches in the realms of management, social and economic sciences, and evaluation research. His scientific interests span methodological assistance for project and program evaluations, AI decision-support methods, and knowledge-based systems. He has written over a hundred papers and contributed to several books. Additionally, he is a reviewer for numerous journals indexed in the Web of Science or Scopus databases, and evaluates a number of national and international project proposals. His involvement extends to being a member of various national and international scientific societies, editorial boards, and advisory committees.
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