2023/08/10 by Sivan Schwartz, Schwartz, Sivan, Avi Yaeli +3 · 5 citations
Business, Management and Accounting · Engineering · #68T01 #Artificial Intelligence (cs.AI) #Business Process Modeling and Analysis #Digital Transformation in Industry #FOS: Computer and information sciences #Robotic Process Automation Applications
paper · pdf · doi:10.48550/arxiv.2308.05391
openalex publication_date 2023/08/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Trust in AI agents has been extensively studied in the literature, resulting in significant advancements in our understanding of this field. However, the rapid advancements in Large Language Models (LLMs) and the emergence of LLM-based AI agent frameworks pose new challenges and opportunities for further research. In the field of process automation, a new generation of AI-based agents has emerged, enabling the execution of complex tasks. At the same time, the process of building automation has become more accessible to business users via user-friendly no-code tools and training mechanisms. This paper explores these new challenges and opportunities, analyzes the main aspects of trust in AI agents discussed in existing literature, and identifies specific considerations and challenges relevant to this new generation of automation agents. We also evaluate how nascent products in this category address these considerations. Finally, we highlight several challenges that the research community should address in this evolving landscape.