Abstract This paper explores the prospects for expert systems in the field of accounting. Computer performance of tasks requiring human intelligence is called artificial intelligence (AI). One subfield of applied AI is knowledge engineering, the process of acquiring knowledge from human experts and embedding the knowledge in a computer program. The product of knowledge engineering is knowledge-based systems, called expert systems. One example of what to do rather than how to do it is the operation of spreadsheet programs. Programs with English-like command structures, implemented with natural language processing, are other examples of context-sensitive systems. The appeal of expert systems stems from the opportunity they present for capturing and disseminating scarce and costly expertise in organizations. Expert systems to manage checklists could tailor the list to the current situation and maintain the responses for later processing and evaluation. An expert system whose knowledge base included relevant tax provisions could help individuals and companies minimize their tax liability. Expert systems in accounting can reduce costs and improve decision making depending on the choice of applications and the effectiveness of their implementations. Like other computer systems, however, expert systems only manipulate symbols. Users must be able to decide when to ignore a system's conclusions if they are based on faulty reasoning or inadequate information.
Borthick et al. (Sun,) studied this question.
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