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Exploring the Potential of Generative AI: Use Cases in Software Startups
Conference proceeding   Open access   Peer reviewed

Exploring the Potential of Generative AI: Use Cases in Software Startups

M Simaremare, Triando XXX and S Rico
Agile Processes in Software Engineering and Extreme Programming Workshops: XP 2024 Workshops, Bozen-Bolzano, Italy, June 4–7, 2024, Revised Selected Papers, Vol.524, pp.3-11
Lecture Notes in Business Information Processing, 524
25th International Conference on Agile Software Development (XP 2024) (Bolzano, 03/06/2024–07/06/2024)
2025
Handle:
https://hdl.handle.net/10863/51545

Abstract

Generative AI potential applications Product development Software startups
Background and Related Work: Software startups face unique challenges in product development, including limited resources, the need for rapid innovation, and the constant pressure to adapt to market changes. Generative Artificial Intelligence (GenAI) has recently gained significant attention, offering capabilities to assist creative processes, generate content, and enhance decision-making through data analysis. However, how GenAI can be integrated into agile product development processes in software startups remains an open question. Objective: This study aims to identify potential use cases for GenAI in software startups and explore how GenAI can support innovation, overcome development challenges, and integrate with agile practices to improve product quality and development speed. Method: We identified a list of GenAI use cases from existing systematic literature reviews and mapped them to engineering process areas in software startups. Following that, we conducted workshops with experts to validate our results. Results: The results provide a descriptive overview of GenAI’s potential applications in software startup environments. Given the current state of the art, we identified areas that could benefit faster from integrating GenAI. Conclusions: The study delineates the prospective impact of GenAI on agile product development in software startups, showcasing areas of immediate applicability.
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https://doi.org/10.1007/978-3-031-72781-8_1View

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