Reconsidering Requirements Engineering: Human-AI Collaboration in AI-Native Software Development

• URL: http://arxiv.org/abs/2510.04380v1
• Date: Sun, 05 Oct 2025 21:58:44 GMT
• Title: Reconsidering Requirements Engineering: Human-AI Collaboration in AI-Native Software Development
• Authors: Mateen Ahmed Abbasi, Petri Ihantola, Tommi Mikkonen, Niko Mäkitalo,
• Abstract summary: Requirement Engineering (RE) is the foundation of successful software development.<n>Despite its critical role, RE continues to face persistent challenges, such as ambiguity, conflicting stakeholder needs, and the complexity of managing evolving requirements.<n>This paper explores how AI can enhance traditional RE practices by automating labor-intensive tasks, supporting requirement prioritization, and facilitating collaboration between stakeholders and AI systems.
• Score: 2.195918681143262
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Requirement Engineering (RE) is the foundation of successful software development. In RE, the goal is to ensure that implemented systems satisfy stakeholder needs through rigorous requirements elicitation, validation, and evaluation processes. Despite its critical role, RE continues to face persistent challenges, such as ambiguity, conflicting stakeholder needs, and the complexity of managing evolving requirements. A common view is that Artificial Intelligence (AI) has the potential to streamline the RE process, resulting in improved efficiency, accuracy, and management actions. However, using AI also introduces new concerns, such as ethical issues, biases, and lack of transparency. This paper explores how AI can enhance traditional RE practices by automating labor-intensive tasks, supporting requirement prioritization, and facilitating collaboration between stakeholders and AI systems. The paper also describes the opportunities and challenges that AI brings to RE. In particular, the vision calls for ethical practices in AI, along with a much-enhanced collaboration between academia and industry professionals. The focus should be on creating not only powerful but also trustworthy and practical AI solutions ready to adapt to the fast-paced world of software development.

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