AI Adoption in Business Decision-Making: Challenges, Enablers, and Organizational Readiness Assessment

Bangjie Lin; Qiyue Yang; Xu Wang

doi:10.6918/IJOSSER.202511_8(11).0030

Authors

Bangjie Lin
Qiyue Yang
Xu Wang

DOI:

https://doi.org/10.6918/IJOSSER.202511_8(11).0030

Keywords:

Artificial Intelligence, Decision-Making, TOE Framework, Organizational Readiness, Governance

Abstract

Artificial intelligence (AI) is migrating from pilots to the core of managerial decision-making. Organizations increasingly embed learning algorithms into planning, forecasting, risk control, and operations. Yet adoption remains uneven. Many firms struggle with data quality, opaque models, fragmented processes, skill shortages, and governance gaps. Anchored in the Technology–Organization–Environment (TOE) perspective, this paper investigates how “organizational AI readiness”—strategic alignment, talent readiness, process adaptation, and ethical governance—relates to the depth and effectiveness of AI use in decisions. Drawing on a multi-industry survey of 200 multinational firms and complementary case evidence, we estimate a structural model linking readiness, enabling conditions, and outcomes. The analysis suggests that readiness exerts a strong direct effect on adoption depth and an indirect effect on decision effectiveness through implementation enablers. We conclude with implications for managers and policymakers seeking to translate AI potential into reliable, repeatable value.

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