Искусственный интеллект, зеленые инновации и организационное обучение в Пакистане

Развитие искусственного интеллекта и экологических инноваций меняет процессы управления знаниями, принятия решений и организационного обучения в компаниях цифрового сектора. Цель исследования провести оценку влияния внедрения искусственного интеллекта и зеленых инноваций на организационное обучение с учетом посреднической роли качества принятия решений и потенциала управления знаниями, а также модерирующей роли цифровой инфраструктуры в секторе информационно-коммуникационных технологий Пакистана. В исследовании использован количественный подход и метод поперечного опроса. Исходные данные получены на основе анкетирования 300 сотрудников компаний информационно-коммуникационного сектора г. Лахор, Пакистан. Результаты показали положительное влияние внедрения искусственного интеллекта на организационное обучение (β=0.650; t=5.520; p<0.001) и зеленых инноваций на организационное обучение (β=0.400; t=3.921; p=0.002). Качество принятия решений (β=0.504; t=4.134; p=0.008) и потенциал управления знаниями (β=0.555; t=5.428; p<0.001) также положительно связаны с организационным обучением. Цифровая инфраструктура усиливает связь между внедрением искусственного интеллекта и организационным обучением (β=0.220; t=2.45; p=0.031), а также между зелеными инновациями и организационным обучением (β=0.318; t=3.29; p=0.001). Полученные результаты имеют социальную значимость, поскольку развитие искусственного интеллекта, зеленых инноваций и цифровой инфраструктуры способствует улучшению обмена знаниями, совместного обучения и адаптивности работников в организациях.

1. Acevedo, J., & Diaz-Molina, I. (2023). Learning organizations in emerging economies: The effect of knowledge management on innovative culture in Chilean companies. The Learning Organization, 30(1), 37–54. https://doi.org/10.1108/TLO-01-2021-0009

2. Agarwal, M., Jain, E., Sharma, S. K., & Kumar, A. (2022). Influence of artificial intelligence on employee engagement and employee behavior. JIMS8I International Journal of Information Communication and Computing Technology, 10(1), 547–552. https://doi.org/10.5958/2347-7202.2022.00002.0

3. Akande, J. O., Hosu, Y. S., & Ndhleve, S. (2026). Green financing in emerging economies: Unlocking sustainable pathways for small enterprise growth. In J. O. Akande, Y. S. Hosu, & S. Ndhleve (Eds.), Green Financing in Emerging Economies: Empowering Small Enterprises for Sustainable Growth in Developing Countries (pp. 3–16). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-13446-2_1

4. Akhtar, S., Li, C., Sohu, J. M., Rasool, Y., Hassan, M. I. U., & Bilal, M. (2024). Unlocking green innovation and environmental performance: The mediated moderation of green absorptive capacity and green innovation climate. Environmental Science and Pollution Research, 31, 4547–4562. https://doi.org/10.1007/s11356-023-31403-w

5. Alhusban, M. I., Khatatbeh, I. N., & Alshurafat, H. (2025). Exploring the influence, implications and challenges of integrating generative artificial intelligence into organizational learning and development. Competitiveness Review: An International Business Journal. https://doi.org/10.1108/CR-06-2024-0121

6. Argote, L., & Fahrenkopf, E. (2016). Knowledge transfer in organizations: The roles of members, tasks, tools, and networks. Organizational Behavior and Human Decision Processes, 136, 146–159. https://doi.org/10.1016/j.obhdp.2016.08.003

7. Bawa, S., Attah, P. K., Agougil, A., & El Harch, M. (2023). Impact of knowledge management on firms’ innovation performance. Technology and Investment, 14(4), 293–328. https://doi.org/10.4236/ti.2023.144018

8. Chen, Y.-S., Lai, S.-B., & Wen, C.-T. (2006). The influence of green innovation performance on corporate advantage in Taiwan. Journal of Business Ethics, 67(4), 331–339. https://doi.org/10.1007/s10551-006-9025-5

9. Donelan, R., Walker, S., & Salek, S. (2016). The development and validation of a generic instrument, QoDoS, for assessing the quality of decision making. Frontiers in Pharmacology, 7, 180. https://doi.org/10.3389/fphar.2016.00180

10. Gavrilova, J. A., Didenko, O. N., & Kalashnikova, N. A. (2026). Legal support for digital economy infrastructure: Russian and international experience. In S. S. Shaumarov (Ed.), Smart Transport Systems and the Digital Economy Infrastructure (pp. 49–58). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-12181-3_6

11. Ghosh, M. (2009). Digital infrastructure and attitudes towards access and sharing: A case study of selected engineering libraries in the Maharashtra state of India. The International Information & Library Review, 41(2), 89–120. https://doi.org/10.1016/j.iilr.2009.04.003

12. Han, S., Zhang, D., Zhang, H., & Lin, S. (2025). Artificial intelligence technology, organizational learning capability, and corporate innovation performance: Evidence from Chinese specialized, refined, unique, and innovative enterprises. Sustainability, 17(6), 2510. https://doi.org/10.3390/su17062510

13. Jamil, K., Zhang, W., Anwar, A., & Mustafa, S. (2025). Exploring the influence of AI adoption and technological readiness on sustainable performance in Pakistani export sector manufacturing small and medium-sized enterprises. Sustainability, 17(8), 3599. https://doi.org/10.3390/su17083599

14. Mironova, M., & Rubtsov, V. (2025). Digital infrastructure as an element of resource potential in the service economy. The Eurasian Scientific Journal, 17(S6), 01FAVN625. https://doi.org/10.15862/01FAVN625

15. Olusegun, S., Hinson, R. E., & Zekeri, O. (2025). Artificial intelligence: A catalyst to organizational learning and development in 21st century. Development and Learning in Organizations: An International Journal, 39(2), 33–35. https://doi.org/10.1108/DLO-02-2024-0037

16. Pérez-López, S., & Alegre, J. (2012). Information technology competency, knowledge processes and firm performance. Industrial Management & Data Systems, 112(4), 644–662. https://doi.org/10.1108/02635571211225521

17. Riaz, M., Jie, W., Ali, Z., Sherani, M., & Yutong, L. (2023). Do knowledge-oriented leadership and knowledge management capabilities help firms to stimulate ambidextrous innovation: Moderating role of technological turbulence. European Journal of Innovation Management, 28(2), 235–270. https://doi.org/10.1108/EJIM-08-2022-0409

18. Salisu, Y., & Abu Bakar, L. J. (2020). Technological capability, relational capability and firms’ performance: The role of learning capability. Revista de Gestão, 27(1), 79–99. https://doi.org/10.1108/REGE-03-2019-0040

19. Sinkula, J. M., Baker, W. E., & Noordewier, T. (1997). A framework for market-based organizational learning: Linking values, knowledge, and behavior. Journal of the Academy of Marketing Science, 25(4), 305–318. https://doi.org/10.1177/0092070397254003

20. Sposato, M. (2025). Harnessing AI and data for organizational learning and development. In H. Rai, A. Gupta, & R. Bansal (Eds.), Impact of Artificial Intelligence on Data-Driven Decision Making in HR for Revolutionizing Organizational Growth (pp. 235–251). Emerald Publishing Limited. https://doi.org/10.1108/978-1-83662-982-520251013

21. Tripopsakul, S. (2025). ESG practices, green innovation, and financial performance: Panel evidence from ASEAN firms. Journal of Risk and Financial Management, 18(8), 467. https://doi.org/10.3390/jrfm18080467

22. Tu, Y., & Wu, W. (2021). How does green innovation improve enterprises’ competitive advantage? The role of organizational learning. Sustainable Production and Consumption, 26, 504–516. https://doi.org/10.1016/j.spc.2020.12.031

23. Ye, D., Yao, M., Ge, B., & Zhao, L. (2023). The mechanism of digital technology driving digital innovation performance in non-internet enterprises: The moderating effect of organizational legitimacy. Science & Technology Progress and Policy, 40(11), 11–18. https://doi.org/10.6049/kjjbydc.2021120462