Unintended consequences of generative AI in product ideation: A product management perspective

Abstract

This research examines the transformative impact of Generative Artificial Intelligence (GenAI) on product ideation processes within product management contexts. Through qualitative exploration involving semi-structured interviews with experienced product managers from both the B2B and B2C sectors, the study identifies critical unintended consequences that emerge when leveraging GenAI tools, such as ChatGPT, Midjourney, and Gemini, during ideation phases. The methodology employed in this research consisted of in-depth, semi-structured interviews with product managers who have direct experience implementing GenAI within their ideation workflows. The interview protocol followed a three-step framework exploring a general understanding of GenAI, in-depth exploration of experiences with GenAI in new product ideation, and examination of unintended consequences and future perspectives. This approach enabled the collection of rich, qualitative data that captured both the immediate benefits and the subtle, long-term effects of AI adoption in creative processes. The findings reveal a complex relationship between efficiency gains and creative limitations. While GenAI significantly enhances ideation productivity and streamlines documentation processes, it simultaneously introduces challenges, including creativity fixation, homogenization of innovation, decision-making biases, and ethical concerns related to intellectual property and data security. Product managers reported varying experiences based on their seniority, with experienced managers finding AI to be less creative but more practical for process refinement, while junior managers valued AI for suggesting concepts they might not have otherwise considered. The research highlights how over-reliance on AI can gradually reshape cognitive patterns, potentially diminishing independent creative thinking. Additionally, the standardization of AI-generated outputs presents a risk of industry-wide homogenization of product ideas, thereby undermining competitive differentiation. The study also identifies verification challenges and trust issues that complicate the integration of AI-driven insights into strategic decision-making. This thesis concludes by advocating for thoughtfully designed hybrid human-AI approaches that maintain human leadership in domains requiring creativity and judgment while leveraging AI for its efficiency and information synthesis strengths. It provides practical recommendations for product managers and organizations to establish effective governance frameworks and integration strategies that maximize the benefits of GenAI while mitigating its unintended consequences in product innovation.