ArticlePloS one2025
Digital product success under the microscope: When artificial intelligence in projects helps - and when it hurts.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
2 authors.
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Abstract
As organizations navigate an increasingly dynamic digital landscape, the challenge of achieving consistent product success has intensified. This study investigates how key management factors-customer-driven product development, open innovation networks, organizational digital agility, and AI-integrated project management-influence digital product outcomes. Special attention is given to the dual role of artificial intelligence: as a potential enabler of innovation and a possible constraint when applied in rigid or misaligned ways. A quantitative survey was conducted among 239 professionals engaged in product-related roles across diverse industries and regions. Data were analyzed using linear regression, moderation analysis, and non-parametric testing to assess both direct and interaction effects among the variables. The results reveal that customer-driven product development, open innovation networks, and organizational digital agility each have a statistically significant positive impact on product success, with customer-driven development emerging as the strongest predictor. In contrast, AI-integrated project management does not demonstrate a significant direct effect. Notably, AI negatively moderates the relationship between open innovation networks and product success, suggesting that while AI may enhance structured knowledge-sharing, it can also diminish the creative and collaborative elements essential for innovation if not carefully managed. These findings highlight the strategic complexity of integrating AI into digital product development. While AI can enhance operational efficiency and knowledge flows, its impact on innovation outcomes is context-dependent and may disrupt the balance between human creativity and automated decision-making. The study underscores the need for hybrid models in which AI complements-not replaces-human expertise. Insights from this research offer valuable guidance for organizations aiming to design resilient, customer-centric, and innovation-driven digital product strategies in an AI-enhanced environment.
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