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The Global Exploration Roadmap provides a pathway for humans to leave lower Earth orbit and develop a sustained presence in cislunar space as well as the lunar surface before embarking on a long journey to Mars. During these crewed Long Duration Exploration Missions (LDEM), communication delays will limit mission control availability to support the crew during critical in-flight anomalies. In order to address this challenge, future human spaceflight operations will benefit from intelligent Virtual Assistants (VAs) capable of assisting the crew in detecting, diagnosing, and resolving emergency anomalies. This intelligent technology could increase the probability of mission success and crew safety in emergency scenarios and could improve overall crew performance while operating in the hostile environment of deep space. Daphne-AT is a VA to support crewed LDEM in the context of diagnosing and resolving in-flight anomalies related to the Environmental Control and Life Support System (ECLSS) of a spacecraft. The overall research objective is to investigate the effect of Daphne-AT on human performance, cognitive workload, situational awareness, and trust in autonomous systems. Daphne-AT will be validated using controlled laboratory experiments, and further evaluation will occur during the Human Exploration Research Analog (HERA) C6 research campaign, consisting of four 45-day missions in 2020–21. In this paper, we provide an overview of our first version of Daphne-AT (i.e., baseline version), and discuss the design of anomaly scenarios using NASA's ECLSS simulator and the experimental set up for laboratory experiments. A preliminary within-subjects (i.e., with and without Daphne-AT) experiment was conducted with five human subjects, and preliminary results indicate that the use of Daphne-AT increases performance and decreases cognitive workload in the context of ECLSS anomaly scenarios. The data also show that subjects exhibited trust in using Daphne-AT, while it improved certain aspects of their situational awareness. Our work is part of the Human Capabilities Assessments for Autonomous Missions (HCAAM) Virtual NASA Science Center of Research (VNSCOR) within the NASA Human Research Program, and the ultimate goal is to generate standards and guidelines about how to design such VAs for future LDEMs.