1) Gürpinar, T.
Towards web 4.0: frameworks for autonomous AI agents and decentralized enterprise coordination
(2025) Frontiers in Blockchain, 8, art. no. 1591907, .
Abstract
The rise of Web 4.0 marks a shift toward decentralized, autonomous AI-driven ecosystems, where intelligent agents interact, transact, and self-govern across digital and physical environments. This paper presents a layered framework outlining the infrastructural, behavioral, and governance dimensions required for enabling autonomous AI agents in decentralized ecosystems. It also explores how enterprises can strategically adopt Web 4.0 applications while mitigating risks related to decentralization and AI coordination. A conceptual approach is adopted, synthesizing research on blockchain-enabled AI, decentralized governance, and autonomous agent interactions. The paper introduces a six-layer framework visualizing key dimensions for Web 4.0 adoption, alongside a framework focusing on enterprise integration guidelines. The study identifies six essential dimensions – spanning infrastructure, trust, and governance – that collectively enable Web 4.0. AI agents require decentralized coordination, transparent behavioral norms, and scalable governance structures to operate autonomously and ethically. Enterprises adopting Web 4.0 must address challenges in data privacy, AI training, multi-agent interaction, and governance. The findings highlight that successful enterprise adoption will depend on trust mechanisms, regulatory alignment, and scalable AI deployment models that balance autonomy with accountability. Copyright © 2025 Gürpinar.
2) Kovbasiuk, A., Triantoro, T., Przegalińska, A., Sowa, K., Ciechanowski, L., Gloor, P.
The personality profile of early generative AI adopters: a big five perspective
(2025) Central European Management Journal, 33 (2), pp. 252-264.
Abstract
Purpose: This pilot study aimed to evaluate the impact of the big five personality traits on user engagement with chatbots at the early stages of artificial intelligence (AI) adoption. Design/methodology/approach: The pilot study involved 62 participants segmented into two groups to measure variables including engagement duration, task performance and future AI usage intentions. Findings: The findings advocate for the incorporation of psychological principles into technology design to facilitate more tailored and efficient human–AI collaboration. Originality/value: This pilot research study highlights the relationship between the big five personality traits and chatbot usage and provides valuable insights for customizing chatbot development to align with specific user characteristics. This will serve to enhance both user satisfaction and task productivity. © 2024, Anna Kovbasiuk, Tamilla Triantoro, Aleksandra Przegalińska, Konrad Sowa, Leon Ciechanowski and Peter Gloor.
3) Laskin, A.V., D'Agostino, G.
The Delphi Panel investigation of artificial intelligence in investor relations
(2024) Public Relations Review, 50 (4), art. no. 102489, .
Abstract
In recent years, there has been a discernible upswing in the attention dedicated to artificial intelligence (AI) within the domains of public relations, advertising, and marketing. Notably, the subdomain of investor relations has maintained a significant historical engagement with AI, actively employing AI and AI-enabled tools for several decades, a practice traceable back to the 1980s. This protracted involvement presents a reservoir of invaluable insights germane to comprehending the broader integration of AI within the purview of public relations. This scholarly inquiry embarks on a Delphi panel examination to scrutinize the deployment of AI in investor relations, proffers a systematic classification of AI-enabled tools within this realm, and prognosticates the trajectory of AI's influence on investor relations and financial communications. The panel of Delphi participants comprises seasoned authorities in the field, boasting a cumulative professional experience spanning 161 years. Leveraging the depth of expertise inherent in investor relations, the study not only illuminates the current landscape but also posits conceivable trajectories for the evolution of AI across other subfields within the domain of public relations. © 2024 Elsevier Inc.
4) Laskin, A.V., Freberg, K.
PUBLIC RELATIONS AND STRATEGIC COMMUNICATION IN 2050: Trends Shaping the Future of the Profession
(2024) Public Relations and Strategic Communication in 2050: Trends Shaping the Future of the Profession, pp. 1-264.
Abstract
Taking stock of the technological, political, economic, and social trends that exist today, this book extends the discussion to analyze and predict how these trends will affect the public relations and strategic communication industry of the future. This book is divided into two sections, the first addressing such key topics as artificial intelligence (AI), big data, political polarization, and misinformation, the second looking at key facets of the profession, such as media relations, crisis communication, and measurement and evaluation. Leading researchers in the discipline share their analysis of these topics while also providing theoretically based and practically relevant insights on how the industry must evolve to keep up with, and perhaps anticipate, changes in culture, society, and technology. This book will be of interest to scholars, industry professionals, and advanced undergraduate and graduate students in public relations and strategic communication. © 2025 selection and editorial matter, Alexander V. Laskin and Karen Freberg; individual chapters, the contributors.
5) Przegalinska, A., Triantoro, T., Kovbasiuk, A., Ciechanowski, L., Freeman, R.B., Sowa, K.
Collaborative AI in the workplace: Enhancing organizational performance through resource-based and task-technology fit perspectives
(2025) International Journal of Information Management, 81, art. no. 102853, .
Abstract
This research examines how artificial intelligence, human capabilities, and task types influence organizational outcomes. By leveraging the frameworks of the Resource-Based View and Task Technology Fit theories, we executed two distinct studies to assess the effectiveness of a generative AI tool in aiding task performance across a spectrum of task complexities and creative demands. The initial study tested the utility of generative AI across diverse tasks and the significance of AI-related skills enhancement. The subsequent study explored interactions between humans and AI, analyzing emotional tone, sentence structure, and word choice. Our results indicate that incorporating AI can significantly improve organizational task performance in areas such as automation, support, creative endeavors, and innovation processes. We also observed that generative AI generally presents more positive sentiment, utilizes simpler language, and has a narrower vocabulary than human counterparts. These insights contribute to a broader understanding of AI's strengths and weaknesses in organizational settings and guide the strategic implementation of AI systems.
6) Yawson, R.M., Goryunova, E.
Nested Complexity: A Conceptual Framework for Leveraging AI for Sustainable Organizations and Human Resource Development
(2025) Advances in Developing Human Resources, 27 (2-3), pp. 91-123.
Abstract
Problem: Organizations face increasing complexity in implementing artificial intelligence (AI) while maintaining a focus on human resource development. Human Resource Development (HRD) professionals struggle to balance technological advancement with human capital development amidst volatile, uncertain, complex, and ambiguous (VUCA) environments. Solution: We propose a “nested complexity” framework that conceptualizes AI implementation challenges as multi-layered complexities spanning technological, ethical, and regulatory dimensions, nested within broader environmental complexity. Through a narrative literature review and conceptual integration, we develop practical guidelines for assessing organizational readiness, developing learning strategies, and managing change during AI implementation. Stakeholders: This framework provides HRD professionals with structured approaches for leading AI initiatives while prioritizing human development. It enables organizations to develop implementation strategies that balance technological advancement with human capabilities, offering practical tools for building organizational capacity that supports successful AI integration while maintaining focus on human capital development. © The Author(s) 2025.
7) Yawson, R.M.
Perspectives on the promise and perils of generative AI in academia
(2025) Human Resource Development International, 28 (3), pp. 476-487.
Abstract
Recent advances in generative artificial intelligence (AI), spearheaded by models such as GPT-3, DALL-E 2, and ChatGPT, have demonstrated capabilities to produce remarkably human-like text, images, and speech. This has fuelled growing interest in applying these technologies in academic contexts to augment teaching, research, and knowledge creation. However, the integration of emerging technologies into education requires a thoughtful evaluation to ensure responsible and ethical adoption. This essay provides a balanced perspective on both the potential promise and the possible perils of deploying generative AI in academia. It examines key technical factors that require evaluation, discusses risks and limitations, and proposes an informed framework for assessing when and how these technologies could appropriately enhance academic pursuits. © 2024 Informa UK Limited, trading as Taylor & Francis Group.
