Technology is a pervasive and growing component of accounting tasks and has been shown to change work processes. The meta-theory model for AIS research contained in this paper explicitly recognizes this factor. Currently, multiple research methods are being employed to investigate dual AIS/accounting problems. This is especially evident in managerial accounting, where experimental, ®eld, and analytical work has addressed the interrelationships between managerial tasks and AIS design and use. Less evident is an explicit combined strategy to employ multi-methods in a manner that most eectively uses the strengths of each approach (Peters, 1993). The meta-theory model develops a comprehensiveframeworkthatcan be used to help organize and interpret future research. The meta-theory model may also provide a vehicle to encourage the integration of AIS research with the other sub-disciplines of accounting research. Explicitly considering task commonalities and dierences between sub-disciplines may avoid unnecessary duplication of research as well as accelerate the advance of AIS research. This paper develops a meta-theory model for AIS research that begins with a task focus and suggests a matching process between requirements of the task and system design alternatives at four dierent levels of analysis. Further, the model suggests that technological, organizational, and cognitive contingency factors impact the outcome, task performance. The three contingency factors are developed from a review of the extant literature and are complimentary, each focusing on an important aspect of AIS design and use in addressing accounting issues. The model provides a nomological structure that can be used in future research to identify variable combinations and critical interactions for speci®c task settings. Four propositions for future research are also identi®ed using the proposed model. These propositions illustrate questions that have been under-researched regarding the temporal ordering of contingency factors, the relative importance of contingency factors for dierent tasks, the consequences of system design choices and the complementarities in AIS.