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.

翻译：信任在AI代理中已在文献中得到广泛研究，并推动了对该领域的深入理解。然而，大语言模型（LLM）的快速进步及基于LLM的AI代理框架的出现，为后续研究带来了新的挑战与机遇。在流程自动化领域，新一代基于AI的代理已崭露头角，能够执行复杂任务。同时，通过用户友好的无代码工具和训练机制，构建自动化的流程对业务用户而言变得更加便捷。本文探讨了这些新挑战与机遇，分析了现有文献中讨论的AI代理信任的主要方面，并识别出与新一代自动化代理相关的具体考量和挑战。我们还评估了该领域新兴产品如何应对这些考量。最后，我们指出了研究社群应在这一不断演变的背景下解决的若干挑战。