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The State University of New York at Buffalo rtificial intelligence (AI) applications are utilized to simulate human intelligence for either solving a problem or making a decision. AI provides the advantages of permanency, reliability, and cost-effectiveness while also addressing uncertainty and speed in either solving a problem or reaching a decision. AI has been applied in such diverse realms as engineering, economics, linguistics, law, manufacturing and medicine, and for a variety of modeling, prediction, and decision support and control applications (1). One of the most promising applications of AI has been its rigorous use in the Internet such as in search engines (2). Although the efficacies of AI are significant, as with any application they are limited in both capability and functionality. These limitations will be presented later in this article. Before describing AI’s limitations, this article will briefly survey some of AI’s advantages. In an organization in which human intelligence is tied to a particular person or a group of people, AI applications can provide permanency that prevents the knowledge from being lost when the individual or the group members retire or are no longer available to the organization. The life of the knowledge encapsulated in an AI framework could be as long as the relevance of the problems and decision scenarios remain unchanged. AI also enables the development of a learning capability which can be utilized to further prolong the life and relevance of the application. Learning from real-world success and failure is an enabling feature of AI tools known as “reinforcement learning” and is advantageous in that it increases the …