AI maturity as a double-edged capability: planning fallacy and firm performance in technology startups
TL;DR
The study contributes to digital entrepreneurship by showing that AI maturity does not automatically neutralize planning bias; rather, its performance implications depend on alignment among AI capabilities, managerial attention, and venture planning routines.
Abstract
Artificial intelligence (AI) maturity is increasingly viewed as a source of advantage for technology startups, yet its value may depend on the planning assumptions guiding its use. Drawing on socio-technical systems theory, the attention-based view of the firm, and entrepreneurial cognition research, this study examines the relationship between planning fallacy and firm performance and tests the moderating role of AI maturity. Planning fallacy is defined as a perceived tendency to underestimate schedules, costs, and risks while overestimating expected outcomes. Survey data from 165 technology startups in Tehran, Iran, were analyzed using partial least squares structural equation modeling. Planning fallacy was negatively associated with firm performance, while the lower-order path from AI maturity to performance was positive and significant. The interaction effect was negative and significant, indicating that the adverse association between planning fallacy and performance becomes stronger at higher levels of AI maturity. The model explained 30.3% of the variance in firm performance (R² = 0.303). These findings position AI maturity as a contingent, double-edged capability whose value depends on disciplined and realistic planning. The study contributes to digital entrepreneurship by showing that AI maturity does not automatically neutralize planning bias; rather, its performance implications depend on alignment among AI capabilities, managerial attention, and venture planning routines.
