Teams of the future will likely consist of humans and AI agents. To this purpose, we conducted experiments to explore how such teams integrate their individual decisions into a group response. We propose a set of models to explain team decision making using appraisal dynamics, Prospect Theory, Bayes rule, and eigenvector centrality. Decision-making in the experiments proceeds consists of two sequential tasks: a first task in which the teams decide to report one of the presented options to a multiple-choice question or to choose one of the agents, and if the teams decide to use an agent, the second decision-making task consists of integrating the agent's response with their previous responses and reporting an answer.