Explainable AI-Driven Strategic Decision-Making in SMEs: Simulation-Based Evaluation of Ethical Governance - Noah Benjamin; Sri Yulianingsih; Isabella Marie (Journal of Management and Informatics, 2026)
Given resource constraints and competitive pressures, we would have expected most SMEs to focus on the performance of AI over ethics. Our findings, however, ran squarely against those expectations and forced us to revise our assumptions about technological adoption in the smaller enterprise. Digital transformation in SMEs is not just about technology adoption; it is about trust building and organizational learning. While AI affords significant advantages in terms of competitiveness, the "black-box" nature of AI generates accountability gaps in ways that hit small businesses harder because they have limited capacity to absorb risk. Our study illustrates precisely how the integration of Explainable AI with digital ethics shifts decision quality in unexpected ways, to the benefit of both ethical compliance and business performance. Drawing on advanced simulation modeling and realistic synthetic data that represents SME scenarios, we compared three competing approaches: pure black-box AI, XAI without ethical safeguards, and XAI with full ethical integration. We were surprised by how the integrated approach improved not only ethical metrics but also improved strategic outcomes along many dimensions, such as in fairness, transparency, and decision quality. We provide a practical, evidence-based framework that guides SMEs through AI adoption via safe simulation environments, thereby avoiding expensive mistakes in the real world while systematically fostering stakeholder trust and organizational capability.