AI-Enabled Nudges in Executive Innovation Decision-Making: A Systematic Review and Research Agenda

Behavioural interventions as well as Artificial Intelligence (AI)-enabled decision-support systems are increasingly shaping executive decision-making within innovation contexts. A growing number of studies on Nudge Theory, behavioural economics, and digital decision architecture have been produced; however, many remain unsystematic and disproportionately focus on operational/individual-level applications. Therefore, there is relatively little empirical evidence to support how AI-enabled nudges affect the executive-level strategic decision-making process regarding innovation investment decisions. Furthermore, the existing body of literature fails to demonstrate any theoretical linkages between Nudge Theory, Construal Theory, and Upper Echelons Theory. The results of this study highlight three specific areas where there is a lack of empirical research within the literature: 1) there are very few empirical studies investigating the use of AI-enabled nudges by Chief Executive Officers (CEOs) and at the C-level; 2) there is a lack of theoretical relationships between Nudge Theory, Construal Theory, and Upper Echelons Theory; and 3) core mechanisms for executive strategic decision-making (i.e., uncertainty reduction, psychological distancing and bias mitigation) are not adequately conceptualised or operationalised when investigating innovation decision-making.