Утицај асистената вештачке интелигенције на продуктивност, когнитивно оптерећење и концентрацију програмера

Милан Ајдер

doi:10.24867/36BE45Ajder

Electrotechnical and Computer Engineering

Vol. 41 No. 10 (2026): Proceedings of the Faculty of Technical Sciences

The Impact of AI Assistants on Productivity, Cognitive Load, and Deep Concentration in Developer Work

Милан Ајдер

36BE45Ajder.pdf (Serbian)

DOI:: https://doi.org/10.24867/36BE45Ajder
Submitted: October 14, 2026
Published: 2026-10-16

Abstract

This paper examines the impact of AI assistants on developer productivity, cognitive load and deep concentration. The study was conducted through a survey of 131 respondents, 119 of whom use AI assistants. The analysis covered perceived productivity, cognitive load, technology acceptance, workflow, and possible changes in users’ ways of thinking. Results show that AI assistants contribute most to efficiency and the reduction of routine mental effort, while their impact on work quality and deep focus is more moderate.

References

[1] S. Peng, et al., "The impact of AI on developer productivity: Evidence from GitHub Copilot," arXiv preprint arXiv:2302.06590, 2023.
[2] D. DeBellis, et al., "DORA 2025 State of AI-Assisted Software Development Report," Google/DORA, 2025.
[3] N. Forsgren, et al., "The SPACE of Developer Productivity: There’s more to it than you think," Queue, vol. 19, no. 1, pp. 20-48, 2021.
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[5] M. Csikszentmihalyi, "Flow: The psychology of optimal experience," 1990.
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[7] K. Niederhoffer, G. R. Kellerman, A. Lee, A. Liebscher, K. Rapuano, and J. T. Hancock, "AI-Generated Workslop Is Destroying Productivity," Harvard Business Review, 2025.
[8] H. P. Lee, et al., "The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers," Microsoft Research, 2025.
[9] J. T. Liang, C. Yang, and B. A. Myers, "A large-scale survey on the usability of AI programming assistants: Successes and challenges," Software Engineering, 2024.

[1] [1] S. Peng, et al., "The impact of AI on developer productivity: Evidence from GitHub Copilot," arXiv preprint arXiv:2302.06590, 2023.

[2] [2] D. DeBellis, et al., "DORA 2025 State of AI-Assisted Software Development Report," Google/DORA, 2025.

[3] [3] N. Forsgren, et al., "The SPACE of Developer Productivity: There’s more to it than you think," Queue, vol. 19, no. 1, pp. 20-48, 2021.

[4] [4] C. Clark and R. Kimmons, "Cognitive Load Theory," 2023.

[5] [5] M. Csikszentmihalyi, "Flow: The psychology of optimal experience," 1990.

[6] [6] D. Marikyan and S. Papagiannidis, "Technology acceptance model: A review," TheoryHub Book, 2024.

[7] [7] K. Niederhoffer, G. R. Kellerman, A. Lee, A. Liebscher, K. Rapuano, and J. T. Hancock, "AI-Generated Workslop Is Destroying Productivity," Harvard Business Review, 2025.

[8] [8] H. P. Lee, et al., "The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers," Microsoft Research, 2025.

[9] [9] J. T. Liang, C. Yang, and B. A. Myers, "A large-scale survey on the usability of AI programming assistants: Successes and challenges," Software Engineering, 2024.