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calendar9 феврал 2026
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STATISTIK HISOBOTLARNI QABUL QILISH JARAYONLARINI AVTOMATLASHTIRISHDA SUNʼIY INTELLEKTDAN FOYDALANISH

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MAQOLA ANNOTATSIYASI

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Mazkur maqolada statistik hisobotlarni avtomatlashtirishda sunʼiy intellekt texnologiyalaridan foydalanishning afzalliklari, imkoniyatlari va mavjud muammolar tahlil qilinadi. Sunʼiy intellekt yordamida hisobot tayyorlash jarayonlarining samaradorligi, vaqtni tejash va xatoliklarni kamaytirish kabi asosiy jihatlari o‘rganiladi. Shuningdek, O‘zbekistonda va dunyoning boshqa rivojlangan mamlakatlarida sunʼiy intellekt texnologiyalarining qo‘llanilishi va bu sohadagi mavjud qiyinchiliklar ham muhokama qilinadi. Maqola davomida sunʼiy intellektni joriy etishda yuzaga keladigan axborot xavfsizligi, kadrlar tayyorlash, texnik infratuzilma, etik va qonuniy muammolar keltirilgan. Ushbu tadqiqot texnologiyaning rivojlanishi uchun strategik tavsiyalarni ham taqdim etadi

MUALIFLAR

SH.Ochilov

Qarshi davlat texnika universiteti

Teglar

# avtomatlashtirish# samaradorlik# axborot xavfsizligi# sunʼiy intellekt# kadrlar tayyorlash# vaqtni tejash# statistik hisobotlar# texnik infratuzilma# etik masalalar

Maqolani baholang

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Maqola idintifikatorlari

Foydalanilgan adabiyotlar

Glickman, M., & Zhang, Y. (2024). AI and Generative AI for Research Discovery and Summarization. 2024, p. 15.

The state of AI: How organizations are rewiring to capture value / https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

https://hai.stanford.edu/ai-index/2025-ai-index-report

Acosta, J. N., et al. (2024). The Impact of AI Assistance on Radiology Reporting: A Pilot Study Using Simulated AI Draft Reports. 2024, p. 12

Giudici, P., et al. (2024). Explainable machine learning in credit risk management. Computational Economics, 58(3), 299-315. https://doi.org/10.1007/s10614-020-10111-3. 2024, p. 8

Li, L., et al. (2025). Transforming Evidence Synthesis: A Systematic Review of the Evolution of Automated Meta-Analysis in the Age of AI. 2025, p. 21.

The state of AI: How organizations are rewiring to capture value / https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

https://hai.stanford.edu/ai-index/2025-ai-index-report

Acosta, J. N., et al. (2024). The Impact of AI Assistance on Radiology Reporting: A Pilot Study Using Simulated AI Draft Reports. 2024, p. 12

Giudici, P., et al. (2024). Explainable machine learning in credit risk management. Computational Economics, 58(3), 299-315. https://doi.org/10.1007/s10614-020-10111-3. 2024, p. 8

Li, L., et al. (2025). Transforming Evidence Synthesis: A Systematic Review of the Evolution of Automated Meta-Analysis in the Age of AI. 2025, p. 21.

Glickman, M., & Zhang, Y. (2024). AI and Generative AI for Research Discovery and Summarization. 2024, p. 15.

Torre-López, J. de la, et al. (2024). Artificial intelligence to automate the systematic review of scientific literature. 2024, p. 19.

Acemoglu, D., et al. (2022). Advanced technology use and automation: Results from recent research. U.S. Census Bureau. 2022, p. 33.

McKinsey & Company. (2023). The state of AI in 2023: Generative AI's breakout year. McKinsey. https://www.mckinsey.com/capabil

https://dig.watch/resource/digital-economy-of-uzbekistan-the-state-of-digital-entrepreneurship-and-artificial-intelligence

Vention Teams. (2024). AI adoption statistics. Vention Teams

Muallif ishlanmasi

Torre-López, J. de la, et al. (2024). Artificial intelligence to automate the systematic review of scientific literature. 2024, p. 19.

Acemoglu, D., et al. (2022). Advanced technology use and automation: Results from recent research. U.S. Census Bureau. 2022, p. 33.

McKinsey & Company. (2023). The state of AI in 2023: Generative AI's breakout year. McKinsey. https://www.mckinsey.com/capabil

https://dig.watch/resource/digital-economy-of-uzbekistan-the-state-of-digital-entrepreneurship-and-artificial-intelligence

Vention Teams. (2024). AI adoption statistics. Vention Teams

Muallif ishlanmasi

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