AN ALGORITHM FOR IMPLEMENTING GENERATIVE AI TOOLS IN TECHNOLOGICAL PRODUCT MANAGEMENT PROCESSES

Authors

  • А.Y. Moskovchenko Chief Product Officer, Product Trends LLC, USA

DOI:

https://doi.org/10.25806/uu-6065

Статья поступила в редакцию: 23.02.2026

Статья принята к публикации: 03.04.2026

Статья опубликована: 14.04.2026

Keywords:

generative artificial intelligence, technological product management, implementation algorithm, product processes, evaluation of the implementation effect

Abstract

The article discusses the problems and practical tasks of introducing generative artificial intelligence into technological product management processes due to the increasing complexity of product solutions, accelerated development cycles and the need to improve the consistency of management actions. The research methods include generalization of management practice of implementing digital tools, structuring typical problems of applying generative models and logical modeling of the sequence of managerial decisions. The result of the research is the development of an author's model of an algorithm for the introduction of generative artificial intelligence into technological product management processes, combining criteria for selecting tools, pilot application procedures, and a system for evaluating the effect of the introduction of generative artificial intelligence. Conclusions: a) the competent implementation of generative artificial intelligence requires a preliminary definition of acceptable areas of its application and criteria for selecting the most appropriate tools; b) the greatest effect of generative artificial intelligence is achieved through its phased implementation, taking into account the mandatory verification of results in pilot processes of technological product management; c) institutionalization of the practice of using generative artificial intelligence ensures increased consistency of management decisions and predictability of product results.

Информация о публикации

Финансирование: Исследование выполнено без привлечения внешнего финансирования, если иное не указано авторами.

Вклад авторов: Все авторы внесли существенный вклад в подготовку статьи, ознакомились с окончательной версией рукописи и одобрили ее к публикации.

Конфликт интересов: Авторы заявляют об отсутствии конфликта интересов, если иное не указано в публикации.

Правообладатель: Издательский дом «Академический».

Лицензия: Статья распространяется на условиях лицензии Creative Commons Attribution 4.0 International (CC BY 4.0).

Машиночитаемый файл метаданных: JATS XML

References

The state of AI in early 2024: Gen AI adoption spikes and starts to generate value // McKinsey. [Электронный ресурс]. URL: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-2024 (дата обращения: 24.01.2026).

Stay ahead, lead the future of AI in project management // PMI. [Электронный ресурс]. URL: https://www.pmi.org/learning/ai-in-project-management (дата обращения: 24.01.2026).

Worldwide Spending on Artificial Intelligence Forecast to Reach $632 Billion in 2028, According to a New IDC Spending Guide // IDC. [Электронный ресурс]. URL: https://my.idc.com/getdoc.jsp?containerId=prUS52530724 (дата обращения: 24.01.2026).

Zhang C., Zhang H. The impact of generative AI on management innovation // Journal of Industrial Information Integration. 2025. Vol. 44. P. 1-8. DOI: 10.1016/j.jii.2024.100767 EDN: LLLPBQ.

Krishnan S. The Evolution of Product Management Methods in the Era of Generative Artificial Intelligence // Emerging Frontiers Library for The American Journal of Interdisciplinary Innovations and Research. 2026. Vol. 8. No. 01. P. 56-62.

Ghazi F., Mariam S. Conceptual Framework for Integrating Generative AI into the Product Management Lifecycle // International Journal of Business and Technology Management. 2025. Vol. 7. No. 9. P. 167-176.

Valencia-Arias A. et al. Industrial applications of generative artificial intelligence: transformations in processes, design, and production // Discover Artificial Intelligence. 2025. Vol. 5. No. 1. P. 327. DOI: 10.1007/s44163-025-00557-6 EDN: WFBMPY.

Pradhan D. et al. The impact of generative AI on product management in SMEs // International Scientific Congress Society Of Ambient Intelligence. Cham: Springer Nature Switzerland, 2023. P. 167-176.

Ramalingam B. et al. Utilizing Generative AI for Design Automation in Product Development // International Journal of Current Science (IJCSPUB). 2023. Vol. 13. Vol. 4. P. 558-571.

Mohammed M. Y., Skibniewski M. J. The role of generative AI in managing industry projects: transforming industry 4.0 into industry 5.0 driven economy // Law and Business. 2023. Vol. 3. No. 1. P. 27-41. DOI: 10.2478/law-2023-0006 EDN: OYATAW.

Witkowski A., Wodecki A. Where does AI play a major role in the new product development and product management process? // Management Review Quarterly. 2025. P. 1-38. DOI: 10.1007/s11301-025-00533-5 EDN: WMMKWC.

Куровский С.В., Мишин Д.А., Шугаев М.О. Финансовые аспекты управления рисками в международных инвестиционных проектах // Финансовый менеджмент. 2024. № 11-2. С. 473-482. EDN: GVADCD.

Al-Kfairy M. Strategic integration of generative AI in organizational settings: Applications, challenges, and adoption requirements // IEEE Engineering Management Review. 2025. Vol. 53. No. 6. P. 80-97.

Куровский С.В., Мишин Д.А., Булыгин Ф.А. Исследование математических методов в рамках анализа финансовых рынков // Экономика строительства. 2025. № 2. С. 412-417. EDN: UMWSAB.

Corvello V. Generative AI and the future of innovation management: a human centered perspective and an agenda for future research // Journal of Open Innovation: Technology, Market, and Complexity. 2025. Vol. 11. No. 1. P. 1-5. DOI: 10.1016/j.joitmc.2024.100456 EDN: CLSGCS.

Куровский С.В., Мишин Д.А., Гугкаева С.С. Финансово-экономический анализ группы компании "Лента" и оценка успешности стратегии для развития финансовых показателей // Управленческий учет. 2025. № 1. С. 24-34. EDN: YWKBUL.

Shafiee S. Generative AI in manufacturing: a literature review of recent applications and future prospects // Procedia CIRP. 2025. Vol. 132. P. 1-6. DOI: 10.1016/j.procir.2025.01.001 EDN: ESLMOT.

Sikandar H. et al. Generative AI for Sustainable Product Design: A Technology Convergence Framework Integrating Multi-Objective Optimisation and Smart Manufacturing // IET Collaborative Intelligent Manufacturing. 2026. Vol. 8. No. 1. P. 1-25.

Tingelhoff F., Brugger M., Leimeister J. M. A guide for structured literature reviews in business research: The state-of-the-art and how to integrate generative artificial intelligence // Journal of Information Technology. 2025. Vol. 40. No. 1. P. 77-99.

Salih S. et al. Generative AI for industry transformation: a systematic review of chatgpt's capabilities and integration challenges // International Journal of Computer Science & Network Security. 2025. Vol. 25. No. 5. P. 221-249.

Published

2026-04-14

Issue

Section

Economic theory, management and other research