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Exploring the Impact of Generative Artificial Intelligence on Software Development in the IT Sector: Preliminary Findings on Productivity, Efficiency and Job Security

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  • Anton Ludwig Bonin
  • Pawel Robert Smolinski
  • Jacek Winiarski

Abstract

This study investigates the impact of Generative AI on software development within the IT sector through a mixed-method approach, utilizing a survey developed based on expert interviews. The preliminary results of an ongoing survey offer early insights into how Generative AI reshapes personal productivity, organizational efficiency, adoption, business strategy and job insecurity. The findings reveal that 97% of IT workers use Generative AI tools, mainly ChatGPT. Participants report significant personal productivity gain and perceive organizational efficiency improvements that correlate positively with Generative AI adoption by their organizations (r = .470, p

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  • Anton Ludwig Bonin & Pawel Robert Smolinski & Jacek Winiarski, 2025. "Exploring the Impact of Generative Artificial Intelligence on Software Development in the IT Sector: Preliminary Findings on Productivity, Efficiency and Job Security," Papers 2508.16811, arXiv.org.
    • Handle: RePEc:arx:papers:2508.16811
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    References listed on IDEAS

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    1. Marian STOICA & Marinela MIRCEA & Bogdan GHILIC-MICU, 2013. "Software Development: Agile vs. Traditional," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 17(4), pages 64-76.
    2. C. Piton, 2023. "The economic consequences of artificial intelligence: an overview," Economic Review, National Bank of Belgium, pages 1-29, June.
    3. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    4. Alekseeva, Liudmila & Azar, José & Giné, Mireia & Samila, Sampsa & Taska, Bledi, 2021. "The demand for AI skills in the labor market," Labour Economics, Elsevier, vol. 71(C).
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