Abstract
Artificial intelligence (AI) is pulling the accounting function away from its traditional role as a backward-looking record keeper and toward a forward-looking part in enterprise strategy. This paper asks how that shift, AI-enabled accounting innovation, actually bears on strategic decision making in modern enterprises. Drawing on the dynamic capabilities perspective and a synthesis of recent scholarship and industry evidence, we build a conceptual framework that links AI technologies, accounting innovation, information quality, and decision outcomes, with data governance and human oversight as the conditions that determine how much of the potential is realized. The evidence indicates that machine learning, natural language processing, robotic process automation, and predictive analytics improve the timeliness, accuracy, and reach of accounting information, and through that improvement support faster and better-informed strategic choices. Reported gains are concrete: sizable reductions in manual error, faster closes, stronger anomaly detection, and more accurate forecasts. Yet the value is conditional. It depends on the quality of the underlying data, on the transparency of the algorithms, and, above all, on whether accountants are reskilled from custodians of records into strategic advisers. AI, we argue, is not a replacement for managerial judgement but the enabling layer of a hybrid decision architecture in which algorithmic output and human reasoning work together and accountability stays human.