An agile SDLC for AI systems should embed a decision architecture, derived from decision science, to capture decision requirements before choosing AI technology.
The Role of Generative AI in Software Development Productivity: A Pilot Case Study
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abstract
With software development increasingly reliant on innovative technologies, there is a growing interest in exploring the potential of generative AI tools to streamline processes and enhance productivity. In this scenario, this paper investigates the integration of generative AI tools within software development, focusing on understanding their uses, benefits, and challenges to software professionals, in particular, looking at aspects of productivity. Through a pilot case study involving software practitioners working in different roles, we gathered valuable experiences on the integration of generative AI tools into their daily work routines. Our findings reveal a generally positive perception of these tools in individual productivity while also highlighting the need to address identified limitations. Overall, our research sets the stage for further exploration into the evolving landscape of software development practices with the integration of generative AI tools.
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cs.SE 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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Agile System Development Lifecycle for AI Systems: Decision Architecture
An agile SDLC for AI systems should embed a decision architecture, derived from decision science, to capture decision requirements before choosing AI technology.