The business management in any contemporary organization requires the making of decisions, the coordinating of activities, the handling of people, and the evaluation of performance directed toward group objectives. Thus, this problem cannot be solved without system approach, such as synergetic, system modeling and complexity theory. The role of system sciences is more and more determined in the viewpoint of behavioral modeling of the most complex system. This article discusses the management of information systems in support of businesses. In general business intelligence systems address the needs of different types of complex organizations, including agencies of public administration and associations. Business intelligence represents the complex iterative and interactive, pyramid-like hierarchical multi-stage process. By moving up one level in the pyramid we find optimization models that allow us to determine the best solution out of a set of alternative actions, which is usually fairly extensive and sometimes even infinite. The top of the pyramid corresponds to the choice and the actual adoption of a specific decision, and in some way represents the natural conclusion of the decision-making process. In this paper, we present a new approach for a decision making process with respect to the viewpoint of system dynamics, agent-based modeling and simulation-based optimization, that is conditioned by the existence of nonlinear economic or organizational behavioral factors in human society. Originality of this work is in the system model adaptability by structure reconfiguration or self-assembly when multi-agent organization is evolving its way to a better structure. Every simulation-based solution can be considered as new knowledge. From the point of view of the Artificial Intelligence, technological problems of data mining and knowledge discovery has been discussed.