  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.
