In any multi-actor environment, there is an inevitable trade-off between achieving global coordination of activities and respecting the autonomy of the actors involved. Agile and resilient behavior demands dynamic coordination capabilities, but task and resource allocation quickly becomes challenging because of individual constraints and demands. In this study, we present research on adaptive autonomy in multi-agent organizations. We have studied the relationship between autonomy and coordination, and developed an agent reasoning model not only that enables collaborative task coordination, but also guarantees individual autonomy-the capability to self-manage behavior. We define autonomy as the amount of influence other agents have on one's decision-making process. We have given the agent options to adapt its openness to external influences, so it can change its own level of autonomy. This allows agents to select the level of autonomy that best fits the circumstances, given a certain tasking, individual policies and organizational structure. We have incorporated this concept in a practical model and added heuristics for environmental events, information relevance and organizational rules. Our approach addresses fundamental collaborative challenges in dynamic environments, and may bring about new perspectives on autonomy in collaborative environments. © 2010 Springer-Verlag Berlin Heidelberg.