Adyghe Int. Sci. J. Vol. 26, No. 1. Pp. 16–28. 

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DOI: https://doi.org/10.47928/1726-9946-2026-26-1-16-28
EDN: KCFMLE

PHYSICS

UDC 004.8; 004.94

Original Article

Next-generation engineering systems: how AI improves design and optimization efficiency

Bavizhev Mikhail Danilevich
doctor of physical and mathematical sciences, professor, vice president, director of the Research center of the joint-stock company scientific and production enterprise “Radiy” (Moscow, Russia), Laureate of the State Prize of the Russian Federation in Science and Technology, full member of IAAS, ORCID: https://orcid.org/ 0000-0003-3074-5591, SPIN-код: 9409-0418, Mbavizhev@mail.ru
Rakhmanov Alexander Alekseevich
Professor, Doctor of Technical Sciences, Advisor to the General Director of the Moscow Scientific Research Television Institute (MNITI), Honored Scientist of the Russian Federation, al.al.rakhmanov@gmail.com
Bavizhev Zaur Ramazanovich
Senior Researcher, Joint Stock Company Scientific and Production Enterprise “Radiy” (Moscow, Russia), zu588@mail.ru

Abstract. This article examines modern approaches to the application of artificial intelligence (AI) in engineering research and the development of complex technical systems. Key skepticism is analyzed, including the probabilistic nature of AI, the “black box”problem, the phenomenon of indistinguishable deepfakes, and the lack of legal liability for models. It is shown that most of these concerns stem not from the technological limitations of AI, but from misguided expectations and a lack of application regulations. It is demonstrated that modern AI models already outperform humans in routine, repeated, and systematic engineering operations, improving the quality, speed, and predictability of development. A conclusion is drawn regarding the strategic necessity of integrating AI to ensure the competitiveness of engineering teams.

Keywords: artificial intelligence, engineering research, systems engineering, MDAO, deepfakes,
requirements analysis.

Funding. The work was not carried out within the framework of funds.
Competing interests. There are no conflicts of interest regarding authorship and publication.
Contribution and Responsibility. All authors contributed to this article. Authors are solely responsible for providing the final version of the article in print.

For citation. Bavizhev M. D., Rakhmanov A. A., Bavizhev Z. R. Next-generation engineering systems: how AI improves design and optimization efficiency. Adyghe Int. Sci. J. 2026. Vol. 26, No. 1. Pp. 16–28. DOI: https://doi.org/10.47928/1726-9946-2026-26-1-16-28; EDN: KCFMLE

Submitted 05.01.2026; approved after reviewing 05.02.2026; accepted for publication 12.02.2026.

© Bavizhev M. D., Rakhmanov A. A., Bavizhev Z. R., 2026

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