Keywords
Abstract
With a mixed-method design and based on data from 171 organizations from a range of industries, the question of the impact of AI technology on organizational decision-making is addressed. This study formulates and tests an integrated model of AI's impact on time, accuracy, and resource utilization efficiency in decision-making. Evidence proves that companies enabled by AI achieve more than 55.5% multi-dimensional efficiency improvement with 370% faster decision-making, 34.8% increase in forecast accuracy, and positive ROI after one and a half years of having implemented AI enabling tools. These key findings are captured by a model that represents data infrastructure maturity, organization level readiness, enterprise purpose vis-a-vis business goals level alignment including basic functions and potential AI functions. In the theory of strategic management, these findings reinterpret responsive algorithmically-augmented systems—AI-enabled systems—not just as automation systems but rather cognition adaptive systems that reconstruct agile decision-making out of complex systems thinking providing implementable approaches for achieving competitive agility through AI for the handling of complex business dynamics.
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