An examination of the literature on managerial decision making provides insights for improving the design of Declslon Support Systems. Frequently, these systems are designed using one dominant decision making model; some ignore them altogether. This paper incorporates conflicting decision making constructs into an overall framework for designing Decision Support System and discusses the evolution of Decision Support Systems within this framework. This framework is then used to examine advances in decision support research. Perceived useful ness and appl icabillty of decision support tool s demonstrate the trend toward domai n- independent General Decision Support Systems. Domain-independent systems are those which can be adapted to many different problem areas, usually by the addition or del etion of pertinent data and models. We conclude with an evaluation of the advances that artificial intelligence techniques can bring to decision support system research. The major purpose of this paper is to identify aspects of managerial decision support where techniques of artificial intelligence may provide useful contributions. In addition, a framework is devel oped for positioning and eval uating current research efforts on AI-based Decision Support Systems (DSS) vis-a-vis other approaches identified in the literature. The paper is organized as follows: The first section presents a brief review of the organizational and individual decision making literature relevant to the design and evaluation of DSS. The next section outlines the evolution of DSS design phil osophy over the last two decades with a view toward identifying major contributions made to managerial decision making. Finally, the third section examines recent advances made in AI-based DSS.