Author
Listed:
- Frantisek Pollak
(Bratislava University of Economics and Business, Faculty of Business Management
Faculty of Corporate Strategy, Institute of Technology and Business in České Budějovice)
- Petra Partlova
(Faculty of Corporate Strategy, Institute of Technology and Business in České Budějovice
Czech University of Life Sciences Prague, Faculty of Economics and Management)
- Zuzana Dzilska
(Bratislava University of Economics and Business, Faculty of Business Management)
Abstract
Innovations are created at a high pace, and the time for their adaptation is getting shorter and shorter. The expectations for artificial intelligence (AI) are enormous, particularly in the context of business process digitization and e-commerce, which has accelerated due to the global pandemic. Despite the projected rapid growth in both AI and e-commerce, AI remains more of a promise than an objective reality, contributing relatively little to economic gains. Analysis focuses on examining the authenticity of AI solutions in the online environment. Based on more than a decade of continuous research in the field of online reputation management, the authors have developed a robust knowledge base for empirical investigation of the phenomenon of accelerated digitalization. The methodology established will enable long-term monitoring of industry trends and growth in reference markets. The findings reveal that the AI market, outside of industry leaders, remains underdeveloped, with many entities having low reputation levels, creating challenges for effective reputation management. The specificity of AI product names and optimizing for unique identities are critical to avoiding reputation traps, such as polysemous names that hinder accurate online search optimization. Furthermore, neglecting media visibility for products can lead to reputation threats that deter potential users. There is still a lot of work to be done so that artificial intelligence in the online space does not look too artificial. Authenticity is one of the basic preconditions for acceptance. The study emphasizes the need for a reference framework for ongoing research and further reputation management insights in AI.
Suggested Citation
Frantisek Pollak & Petra Partlova & Zuzana Dzilska, 2026.
"Authenticity Analysis of Generative AI Tools and Platforms in an Online Environment,"
Springer Proceedings in Business and Economics, in: Singha Chaveesuk & Seungwoo Shin & Sebastian Kot & Bilal Khalid (ed.), Entrepreneurship and Human-Centric Business Strategies for Social and Economic Resilience, pages 1163-1181,
Springer.
Handle:
RePEc:spr:prbchp:978-981-95-6415-6_72
DOI: 10.1007/978-981-95-6415-6_72
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