The State of Generative AI Adoption from Software Practitioners' Perspective: An Empirical Study

Abstract

Context: Generative AI (GenAI) brings new op-portunities to the software industry and the digital economy in a broader context. Objective: This study aimed to explore and capture the practitioners' perception of GenAI adoption in the fast-paced software industry in the context of developing countries. Method: We conducted online focus group discussions with 18 practitioners from various roles to collect qualitative data. The practitioners have an average of 7.8 years of working experience and have used GenAI for over a year. We employed thematic analysis and the Human-AI Collaboration and Adaptation Framework (HACAF) to identify the influencing factors of GenAI adoption, such as awareness, use cases, and challenges. Results: The adoption of GenAI technology is evident from practitioners. We identified 22 practical use cases, three of which were novel, i.e., contextualizing solutions, assisting the internal audit process, and benchmarking the internal software development process. We also discovered seven key challenges associated with the GenAI adoption, two of which were novel, namely, no matching use cases and unforeseen benefits. These challenges slow GenAI adoption and potentially hinder developing countries from entering a high-skill industry. Conclusion: While the adoption of GenAI technology is promising, industry-academia collaboration is needed to find solutions and strategies to address the challenges and maximize its potential benefits.

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