Automation, augmentation, or dual AI strategies for superior product line performance: the functional subsidiarity challenge

Abstract

This study evaluates the effectiveness of AI strategy implementation within the solution delivery process of products by analyzing the associations between such strategies (i.e., automation, augmentation, and dual) and the market performance of product lines. The analysis uses a unique sample of 667 distinct product lines from 2023 and applies Kernel-based propensity score matching to ensure that AI-enhanced smart products are comparable to their non-AI-enhanced counterparts. The core findings reveal that, irrespective of their AI capacity, a product's smart capabilities must align with the specific functional needs of the task at hand to optimize outcomes, a principle termed functional subsidiarity. The results show that neither automation nor augmentation alone has a significant impact on market performance; instead, only a dual AI strategy demonstrates a positive effect. By analyzing the effectiveness of smart product lines within strategic processes rather than isolated tasks, the findings highlight the importance of adopting a flexible dual AI strategy to navigate the complexities of solution delivery processes, specifically across its problem identification, solution development, and solution implementation stages. Theoretical and practical implications are discussed.