Smart Financial Decisions and Business Sustainability: The Mediating Role of AI-Driven Financial Analytics
DOI:
https://doi.org/10.35870/ijmsit.v6i2.6918Keywords:
Financial Decisions, Business Sustainability, AI-Driven Financial Analytics, MSMEs, Digital TransformationAbstract
Artificial intelligence (AI) is increasingly embedded in corporate financial decision-making, reshaping how organisations pursue sustainability goals; nevertheless, many companies still find it difficult to convert their financial strategies into durable, sustainable results. Existing research offers mixed conclusions: some studies argue that financial choices strengthen sustainability performance, whereas others point to a disconnect caused by a focus on short-term gains, exposing a gap in the understanding of the mechanism connecting the two. This research addresses that gap by investigating whether AI-driven financial analytics mediates the link between financial decision-making and business sustainability. A quantitative design was used, drawing on survey responses from 200 MSME decision-makers in Indonesia. Partial Least Squares Structural Equation Modelling (PLS-SEM) was applied to examine both the direct and indirect pathways among the constructs. Results show that financial decisions have a markedly positive influence on sustainability and also meaningfully shape the extent to which firms adopt AI-driven financial analytics. AI-driven analytics, in turn, positively affects sustainability and partially mediates the main relationship, demonstrating that technological capability amplifies the value of sound financial decisions. Theoretically, the study broadens the Resource-Based View and Dynamic Capabilities perspective by framing AI-driven financial analytics as a strategic capability embedded in the finance function. From a practical standpoint, the findings point to the need for firms to weave AI into their financial workflows to secure sustainable outcomes, and for policymakers to encourage the development of digital capability among MSMEs. Subsequent research is encouraged to adopt longitudinal designs and cross-national comparisons to better capture how these dynamics evolve across contexts.
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