Abstract: Project risks encompass both internal and external factors, characterized by unplanned problems and events. These factors are interrelated, infl uencing others in a causal way. In fact, most information technology companies evaluate project risk by roughly measuring the related factors, ignoring the important fact that there are complicated causal relationships among them. More effective mechanisms must be developed to systematically judge all factors related to project risk. In order to accomplish this, our study adopts a cognitive map (CM)–based mechanism. The CM represents the causal relationships in a given object and/or problem and describes tacit knowledge hidden in the problem domain. CMs have proven especially useful in solving unstructured problems with many variables and causal relationships. However, simply applying CMs to project risk management is not enough because most causal relationships are hard to identify and measure exactly. To overcome this problem, we have borrowed a mutiagent metaphor in which CM is represented by a use of mutiagents, and project risk is explained through the interaction of the mutiagents. Such an approach presents a new computational capability for resolving complicated decision problems. Our own proposed system is called MACOM (multiagent cognitive map) where CM is represented by a set of mutiagents, each embedded with basic intelligence in order to determine its causal relationships with other agents in decision-making situations. Using the MACOM framework, we demonstrate that the task of resolving the information systems (IS) project risk management can be systematically solved, and in this way IS project managers can be given robust decision support.