INTRODUCTION

Abstract

Al-powered analytics could effectively assess and enhance public sector efficiency by increasing productivity through e-government systems and demonstrate how public sector digitization increases productivity and economic growth by streamlining processes, reducing corruption and encouraging private sector investment. [...]by using natural language processing (NLP) and sentiment analysis to examine customer reviews and feature descriptions, companies can uncover important themes and insights about user satisfaction to develop Al-driven marketing strategies and increase productivity. Research shows that the traditional role may be transformed due to the emergence of self-organized teams and agile practices, and suggests implications for leadership development, curricula and strategic planning in project management.

Artificial intelligence is no longer just a distant concept for the future but a present reality influencing industries and economies worldwide. As Al continues to advance, its role in increasing productivity and transforming the world of work is becoming ever more important. This conference proceedings summarizes the wealth of shared knowledge and the key findings of the 7" International Scientific Conference on the Economics of Digital Transformation (EDT Conference 2024). Our distinguished speakers and contributors have provided invaluable perspectives on the benefits and risks of Al adoption. From improving production efficiency and personalizing customer experiences to the economic impact and ethical considerations, these contributions reflect a comprehensive examination of the impact of Al. Our aim is to provide a deeper understanding of how Al can increase productivity by exploring related challenges such as job displacement, inequality and ethical concerns. By fostering an interdisciplinary dialog and collaboration, we aim to contribute to the development of sustainable and inclusive strategies for the use of Al in the digital economy. All published research papers have undergone a rigorous double-blind peer review process to ensure their scientific quality and relevance. These contributions advance the field by providing innovative solutions and novel perspectives on critical challenges and opportunities in artificial intelligence and productivity.

The first series of articles deals with digital transformation and the use of Al in public administration and regulation. The recent CJEU ruling in the SCHUFA (scoring) case highlights the challenges and opportunities of using Al-supported automated decision making to increase productivity but, at the same time, also raises critical questions about data protection and employee rights under EU labour law. The use of Al in eHealth and personalised medicine increases productivity by enabling tailored therapies based on genetic profiles but its use carries significant technical, legal and ethical challenges that need to be addressed to ensure the protection and appropriate regulation of genetic data and biobanks. Al-powered analytics could effectively assess and enhance public sector efficiency by increasing productivity through e-government systems and demonstrate how public sector digitization increases productivity and economic growth by streamlining processes, reducing corruption and encouraging private sector investment. Al-enabled digitalization in public administration, particularly under the EU's Next Generation initiative, highlights the potential for productivity gains through algorithmic processes while addressing the need for adequate training and coordination of civil servants to uphold constitutional principles and ensure efficient service delivery.

The second series of articles refers to the impact of digitalization and innovation on economic development. In this sense, our authors emphasize the crucial role of external knowledge from sources such as customers, universities, suppliers and consultants in increasing productivity and innovation in companies. The phenomenon of virtual influencers in digital marketing highlights the opportunities and challenges for companies using Al-driven influencers to increase productivity and reach younger generations who value authenticity, ethics and product quality in their interactions and purchasing decisions. In addition, by using natural language processing (NLP) and sentiment analysis to examine customer reviews and feature descriptions, companies can uncover important themes and insights about user satisfaction to develop Al-driven marketing strategies and increase productivity.

The third series of articles refers to topics related to artificial intelligence and Industry 4.0. Advances in Al, such as machine learning and predictive analytics, are revolutionizing financial sector tasks including risk management, fraud detection and investment strategies, thus highlighting the transformative potential, challenges and opportunities of Al for the financial industry. By systematically analyzing high-quality sources from large databases, our authors identify key research topics and gaps that focus on Challenges related to the integration of Al, the current attitudes towards Al and its trustworthiness in the public sector. This should guide future research towards a more nuanced understanding of the impact of Al on public administration and governance practices. Furthermore, our authors discuss the financing of cleantech innovation by assessing the role of crowdfunding as a viable alternative to traditional financing mechanisms. By examining EU equity crowdfunding platforms for cleantech projects, critical success factors such as the number of investors, the promised internal rate of return (IRR) and the investment horizon are identified.

The final set of contributions explores topics related to modern management, organization and marketing, focusing on how digitalization and emerging project management approaches are set to reshape the role of the project manager in the future. Research shows that the traditional role may be transformed due to the emergence of self-organized teams and agile practices, and suggests implications for leadership development, curricula and strategic planning in project management. Another contribution in this area advances the understanding of lean implementation within the context of Industry 4.0 by presenting a novel model that connects key success factors and challenges identified in the literature. This model not only expands the theoretical framework for lean practices, but also provides practical guidance for applications in education and business improvement. By using computational techniques such as the Newton's method to solve nonlinear equations in a duopoly scenario, one of the articles provides a detailed understanding of the interplay between offensive and defensive marketing efforts. This approach not only bridges the gap between theoretical knowledge and practical applications, but also emphasizes the importance of using advanced computational tools for strategic decision making to increase productivity and gain competitive advantages in dynamic markets.

We are confident that these scientific contributions will offer our readers valuable insights and fresh perspectives. We trust you will find the authors' work both provoking and engaging. As we conclude, we warmly invite you to join us at our next conference, where we will continue to expore and share groundbreaking ideas.

Editors