Automation of product visioning and planning using generative AI in Fintech

Abstract

The rapid expansion of financial technology (fintech) has accelerated the need for product teams to make faster, data-informed strategic decisions. Traditional product visioning and planning processes, which rely heavily on manual market analysis, expert judgment, and iterative workshops, struggle to keep pace with dynamic regulatory environments, emerging customer behaviors, and increasingly complex technology infrastructures. This paper investigates the potential of generative artificial intelligence (genAI) to automate and augment product visioning, strategic roadmapping, and early-stage planning in fintech organizations. A multi-layer evaluation framework was applied, integrating prompt-engineered generative models, regulatory-mapped language models, customer-intent prediction engines, and multi-source market intelligence feeds. Results from controlled simulations and practitioner interviews indicate that genAI assisted product planning reduces upstream analysis time by 54%, increases strategic hypothesis accuracy by 37%, and improves roadmap alignment across engineering, compliance, and business teams. The study demonstrates that genAI can autonomously generate market opportunity maps, risk-aware product strategies, regulatory impact analyses, and multi-horizon product roadmaps with human oversight. Findings highlight both the transformative potential and operational limitations of AI-driven product planning in fintech, offering a structured adoption model for organizations seeking to integrate genAI into strategic decision-making workflows.