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Yapay Zekâ Odaklı Ekonomik Rekabette Rusya: ABD ve Çin ile Topsis Modeli Üzerinden Karşılaştırmalı Bir Analiz

Yıl 2026, Sayı: 69, 1 - 14, 18.03.2026
https://doi.org/10.17498/kdeniz.1844236
https://izlik.org/JA79KG42CY

Öz

Yapay zekânın (YZ) çağdaş küresel ekonomide oyun değiştirici nitelik taşıyan temel özelliği, ulusal ekonomik performansa doğrudan ve orantılı katkı sunmasıdır. Yapay zekâ, salt bir teknolojik yenilik olmanın ötesine geçerek verimlilik, rekabet gücü ve yapısal dönüşümün stratejik bir itici gücü hâline gelmiştir. Bu çalışmanın amacı, yapay zekâ temelli bir ekonomik model geliştirmeye yönelik küresel yarışta Rusya’nın konumunu, iki temel rakibi olan Amerika Birleşik Devletleri ve Çin’in performanslarıyla karşılaştırmalı olarak değerlendirmektir. Patent üretimi, yatırım hacmi, hukuki çerçeveler, yapay zekâ odaklı işletmelerin ortaya çıkışı, finansman mekanizmaları ve kurumsal hazırlık düzeyi gibi çok boyutlu göstergelere dayanan karşılaştırmalı bir analiz yoluyla çalışma, yapay zekâ güdümlü ekonomik rekabet ortamında Rusya’nın göreli güçlü ve zayıf yönlerini ortaya koymayı amaçlamaktadır. Bu doğrultuda çalışmada bir karşılaştırmalı kıyaslama analiz modeli kullanılmaktadır. Analiz kapsamında örnek ülkelerin yapay zekâ performansları; Uluslararası Para Fonu (IMF) temelli Yapay Zekâ Hazırlık Endeksi (AI Preparedness Index-AIPI), Stanford Üniversitesi tarafından hazırlanan AI Index Report (AIIR) ve Oxford Üniversitesi temelli Government AI Readiness Index gibi endekslerdeki skorları üzerinden Kıyaslama Modeli aracılığıyla karşılaştırılmaktadır. Model çerçevesinde, söz konusu endekslerdeki sıralamalar R ortamında TOPSIS yaklaşımı kullanılarak analiz edilmiştir. Test sonuçlarına göre Rusya’nın (C* = 0,170), gerek yapay zekâya yönelik yatırım kapasitesi gerekse kurumsal altyapı açısından oldukça zayıf bir performans sergilediği ve küresel yapay zekâ ekonomisinde Amerika Birleşik Devletleri ile Çin’in belirgin biçimde gerisinde konumlandığı tespit edilmiştir. Bu bulgu, Rusya’nın mevcut yapay zekâ ekosisteminin teknolojik rekabetçiliği sürdürebilmek için gerekli mali kaynaklardan, politika uyumundan ve yenilik odaklı kurumsal yapılardan yoksun olduğunu göstermektedir.

Kaynakça

  • Acemoglu D, ‘The simple macroeconomics of AI’ (2025) 40(121) Economic Policy 13–58 https://doi.org/10.1093/epolic/eiae042
  • Balcerzak AP, ‘Technological Potential of European Economy. Proposition of Measurement with Application of Multiple Criteria Decision Analysis’ (2016) 12(3) Montenegrin Journal of Economics 7–17 https://doi.org/10.14254/1800-5845.2016/12-3/1
  • Cazzaniga M and others, Gen-AI: Artificial Intelligence and the Future of Work (IMF Staff Discussion Note SDN2024/001, International Monetary Fund 2024).
  • Dabija D-D and Vătămănescu E-M, ‘Artificial intelligence: The future is already here’ (2023) 14(4) Oeconomia Copernicana 1053–1057 https://doi.org/10.24136/oc.2023.031
  • Filippucci F and others, ‘The impact of Artificial Intelligence on productivity, distribution and growth: Key mechanisms, initial evidence and policy challenges’ (2024) OECD Artificial Intelligence Papers 15 (OECD Publishing) https://doi.org/10.1787/8d900037-en
  • Fiszer JM, ‘The Rivalry Between the United States, China and Russia in the Process of Shaping a New International Order in the 21st Century’ (2020) 48(1) Studia Polityczne 11–33.
  • George AS, ‘Artificial intelligence and the future of work: job shifting not job loss’ (2024) 2(2) Partners Universal Innovative Research Publication 17–37 https://doi.org/10.5281/zenodo.10936490
  • Gillham J, The economic impact of artificial intelligence on the global economy (Price Waterhouse Coopers, London 2017).
  • GreyB, Artificial Intelligence (AI) Patent Landscape: Global Innovation (2025) https://insights.greyb.com/global- artificial-intelligence-patent-landscape.
  • Hou Y, Huang J, Xie D and Zhou W, ‘The limits to growth in the AI-driven economy’ (2025) 94 China Economic Review https://doi.org/10.1016/j.chieco.2025.102510
  • IMD, IMD World Digital Competitiveness Ranking 2024: The digital divide: risks and opportunities (Institute for Management Development 2024).
  • IMF, AI Preparedness Index (2024) https://www.imf.org/external/datamapper/AI_PI@AIPI/ADVEC/EME/LIC/RUS/CHN.
  • IMF, Innovation and Economic Integration Index (2024) https://www.imf.org/external/datamapper/IEI@AIPI/ADVEC/EME/LIC/RUS/CHN.
  • Jonek-Kowalska I, ‘Assessing the energy security of European countries in the resource and economic context’ (2022) 13(2) Oeconomia Copernicana 301–334.
  • Kalai M, Becha H and Helali K, ‘Effect of artificial intelligence on economic growth in European countries: a symmetric and asymmetric cointegration based on linear and non-linear ARDL approach’ (2024) 13(22) Economic Structures 1–37 https://doi.org/10.1186/s40008-024-00345-y
  • Kamolov S, Molchanovskaya I and Kaunov E, ‘Artificial intelligence as a strategic instrument of economic development of Russia and improvement of its public administration’ in E3S Web of Conferences 291 (2021) 04002 https://doi.org/10.1051/e3sconf/202129104002.
  • Maksim B and Andrei S, ‘Central Asia: a region of economic rivalry among Russia, China, the US, and the EU’ (2009) 3(57) Central Asia and the Caucasus 79–88.
  • Maslej N and others, The AI Index 2025 Annual Report (AI Index Steering Committee, Institute for Human- Centered AI, Stanford University 2025).
  • Popkova EG and Stefanovic M, ‘Trends of the AI Economy in Russia’ (2024) 1(1) Journal of Trends and Challenges in Artificial Intelligence 1–14 https://doi.org/10.61552/JAI.2024.01.001
  • Popkova EG, Alekseev AN, Lobova SV and Sergi BS, ‘The theory of innovation and innovative development. AI scenarios in Russia’ (2020) 63 Technology in Society https://doi.org/10.1016/j.techsoc.2020.101390
  • Porter M, ‘The Competitive Advantage of Nations’ (1990) 68 Harvard Business Review 73–93 https://doi.org/10.1002/cir.3880010112
  • Prikhodko OV, ‘US Strategy on Great Power Rivalry’ (2025) (2) USA & Canada: economics, politics, culture 10–24.
  • Pu Y, Liu M and Yan C, ‘Economic evaluation of the Sichuan-Chongqing Region Based on Machine Learning’ (2021) International Conference on Information Science, Parallel and Distributed Systems (ISPDS), Hangzhou, 207–213 https://doi.org/10.1109/ISPDS54097.2021.00047
  • Qadri S, ‘The Impact of the US-China-Russia Rivalry on the Architecture of International Security at the Global and Regional Levels’ (2024) 7(1) Pakistan Journal of International Affairs 54–69.
  • Zhang Q, ‘AI-driven unemployment risk and household financial decision: Evidence from China’ (2025) 99 Journal of Asian Economics https://doi.org/10.1016/j.asieco.2025.101963
  • Zhang K and Dai J, ‘A novel TOPSIS method with decision-theoretic rough fuzzy sets’ (2022) 608 Information Sciences 1221–1244 https://doi.org/10.1016/j.ins.2022.07.009

Russia in the AI-Driven Economic Rivalry: Benchmarking the TOPSIS Model with the US and China

Yıl 2026, Sayı: 69, 1 - 14, 18.03.2026
https://doi.org/10.17498/kdeniz.1844236
https://izlik.org/JA79KG42CY

Öz

The main game-changing feature of Artificial Intelligence (AI) in the contemporary global economy lies in its direct and proportional contribution to national economic performance. AI has evolved from being a technological innovation into a strategic driver of productivity, competitiveness, and structural transformation. The aim of this study is to benchmark Russia’s position in the global race to develop an artificial intelligence (AI)-driven economic model against the performance of its two principal competitors, the United States and China. By conducting a comparative analysis based on multidimensional indica-tors such as patent generation, investment volume, legal frameworks, the emergence of AI-focused enterprises, funding mechanisms, and institutional readiness, the study seeks to identify Russia’s relative strengths and weaknesses within the evolving landscape of AI-driven economic competitiveness. In this regard, the study employs a benchmarking analysis model. Within the scope of the analysis, the artificial intelligence performance of the sample countries is compared using their scores on indices such as the International Monetary Fund (IMF)-based AI Preparedness Index (AIPI), the Stanford University-based AI Index Report (AIIR), and the Oxford-based Government AI Readiness Index, through Benchmark Model. Within the scope of the model, the rankings in the indices are analysed using the TOPSIS approach in ‘R’. According to the test results, it has been determined that Russia (C* = 0.170) performs very poorly both in terms of AI-related investment capacity and institutional infrastructure, positioning itself significantly behind the United States and China in the global AI economy. This outcome indicates that Russia’s current AI ecosystem lacks the necessary financial resources, policy coherence, and innovation-oriented institutions required to sustain technological competitiveness.

Kaynakça

  • Acemoglu D, ‘The simple macroeconomics of AI’ (2025) 40(121) Economic Policy 13–58 https://doi.org/10.1093/epolic/eiae042
  • Balcerzak AP, ‘Technological Potential of European Economy. Proposition of Measurement with Application of Multiple Criteria Decision Analysis’ (2016) 12(3) Montenegrin Journal of Economics 7–17 https://doi.org/10.14254/1800-5845.2016/12-3/1
  • Cazzaniga M and others, Gen-AI: Artificial Intelligence and the Future of Work (IMF Staff Discussion Note SDN2024/001, International Monetary Fund 2024).
  • Dabija D-D and Vătămănescu E-M, ‘Artificial intelligence: The future is already here’ (2023) 14(4) Oeconomia Copernicana 1053–1057 https://doi.org/10.24136/oc.2023.031
  • Filippucci F and others, ‘The impact of Artificial Intelligence on productivity, distribution and growth: Key mechanisms, initial evidence and policy challenges’ (2024) OECD Artificial Intelligence Papers 15 (OECD Publishing) https://doi.org/10.1787/8d900037-en
  • Fiszer JM, ‘The Rivalry Between the United States, China and Russia in the Process of Shaping a New International Order in the 21st Century’ (2020) 48(1) Studia Polityczne 11–33.
  • George AS, ‘Artificial intelligence and the future of work: job shifting not job loss’ (2024) 2(2) Partners Universal Innovative Research Publication 17–37 https://doi.org/10.5281/zenodo.10936490
  • Gillham J, The economic impact of artificial intelligence on the global economy (Price Waterhouse Coopers, London 2017).
  • GreyB, Artificial Intelligence (AI) Patent Landscape: Global Innovation (2025) https://insights.greyb.com/global- artificial-intelligence-patent-landscape.
  • Hou Y, Huang J, Xie D and Zhou W, ‘The limits to growth in the AI-driven economy’ (2025) 94 China Economic Review https://doi.org/10.1016/j.chieco.2025.102510
  • IMD, IMD World Digital Competitiveness Ranking 2024: The digital divide: risks and opportunities (Institute for Management Development 2024).
  • IMF, AI Preparedness Index (2024) https://www.imf.org/external/datamapper/AI_PI@AIPI/ADVEC/EME/LIC/RUS/CHN.
  • IMF, Innovation and Economic Integration Index (2024) https://www.imf.org/external/datamapper/IEI@AIPI/ADVEC/EME/LIC/RUS/CHN.
  • Jonek-Kowalska I, ‘Assessing the energy security of European countries in the resource and economic context’ (2022) 13(2) Oeconomia Copernicana 301–334.
  • Kalai M, Becha H and Helali K, ‘Effect of artificial intelligence on economic growth in European countries: a symmetric and asymmetric cointegration based on linear and non-linear ARDL approach’ (2024) 13(22) Economic Structures 1–37 https://doi.org/10.1186/s40008-024-00345-y
  • Kamolov S, Molchanovskaya I and Kaunov E, ‘Artificial intelligence as a strategic instrument of economic development of Russia and improvement of its public administration’ in E3S Web of Conferences 291 (2021) 04002 https://doi.org/10.1051/e3sconf/202129104002.
  • Maksim B and Andrei S, ‘Central Asia: a region of economic rivalry among Russia, China, the US, and the EU’ (2009) 3(57) Central Asia and the Caucasus 79–88.
  • Maslej N and others, The AI Index 2025 Annual Report (AI Index Steering Committee, Institute for Human- Centered AI, Stanford University 2025).
  • Popkova EG and Stefanovic M, ‘Trends of the AI Economy in Russia’ (2024) 1(1) Journal of Trends and Challenges in Artificial Intelligence 1–14 https://doi.org/10.61552/JAI.2024.01.001
  • Popkova EG, Alekseev AN, Lobova SV and Sergi BS, ‘The theory of innovation and innovative development. AI scenarios in Russia’ (2020) 63 Technology in Society https://doi.org/10.1016/j.techsoc.2020.101390
  • Porter M, ‘The Competitive Advantage of Nations’ (1990) 68 Harvard Business Review 73–93 https://doi.org/10.1002/cir.3880010112
  • Prikhodko OV, ‘US Strategy on Great Power Rivalry’ (2025) (2) USA & Canada: economics, politics, culture 10–24.
  • Pu Y, Liu M and Yan C, ‘Economic evaluation of the Sichuan-Chongqing Region Based on Machine Learning’ (2021) International Conference on Information Science, Parallel and Distributed Systems (ISPDS), Hangzhou, 207–213 https://doi.org/10.1109/ISPDS54097.2021.00047
  • Qadri S, ‘The Impact of the US-China-Russia Rivalry on the Architecture of International Security at the Global and Regional Levels’ (2024) 7(1) Pakistan Journal of International Affairs 54–69.
  • Zhang Q, ‘AI-driven unemployment risk and household financial decision: Evidence from China’ (2025) 99 Journal of Asian Economics https://doi.org/10.1016/j.asieco.2025.101963
  • Zhang K and Dai J, ‘A novel TOPSIS method with decision-theoretic rough fuzzy sets’ (2022) 608 Information Sciences 1221–1244 https://doi.org/10.1016/j.ins.2022.07.009

Yıl 2026, Sayı: 69, 1 - 14, 18.03.2026
https://doi.org/10.17498/kdeniz.1844236
https://izlik.org/JA79KG42CY

Öz

Kaynakça

  • Acemoglu D, ‘The simple macroeconomics of AI’ (2025) 40(121) Economic Policy 13–58 https://doi.org/10.1093/epolic/eiae042
  • Balcerzak AP, ‘Technological Potential of European Economy. Proposition of Measurement with Application of Multiple Criteria Decision Analysis’ (2016) 12(3) Montenegrin Journal of Economics 7–17 https://doi.org/10.14254/1800-5845.2016/12-3/1
  • Cazzaniga M and others, Gen-AI: Artificial Intelligence and the Future of Work (IMF Staff Discussion Note SDN2024/001, International Monetary Fund 2024).
  • Dabija D-D and Vătămănescu E-M, ‘Artificial intelligence: The future is already here’ (2023) 14(4) Oeconomia Copernicana 1053–1057 https://doi.org/10.24136/oc.2023.031
  • Filippucci F and others, ‘The impact of Artificial Intelligence on productivity, distribution and growth: Key mechanisms, initial evidence and policy challenges’ (2024) OECD Artificial Intelligence Papers 15 (OECD Publishing) https://doi.org/10.1787/8d900037-en
  • Fiszer JM, ‘The Rivalry Between the United States, China and Russia in the Process of Shaping a New International Order in the 21st Century’ (2020) 48(1) Studia Polityczne 11–33.
  • George AS, ‘Artificial intelligence and the future of work: job shifting not job loss’ (2024) 2(2) Partners Universal Innovative Research Publication 17–37 https://doi.org/10.5281/zenodo.10936490
  • Gillham J, The economic impact of artificial intelligence on the global economy (Price Waterhouse Coopers, London 2017).
  • GreyB, Artificial Intelligence (AI) Patent Landscape: Global Innovation (2025) https://insights.greyb.com/global- artificial-intelligence-patent-landscape.
  • Hou Y, Huang J, Xie D and Zhou W, ‘The limits to growth in the AI-driven economy’ (2025) 94 China Economic Review https://doi.org/10.1016/j.chieco.2025.102510
  • IMD, IMD World Digital Competitiveness Ranking 2024: The digital divide: risks and opportunities (Institute for Management Development 2024).
  • IMF, AI Preparedness Index (2024) https://www.imf.org/external/datamapper/AI_PI@AIPI/ADVEC/EME/LIC/RUS/CHN.
  • IMF, Innovation and Economic Integration Index (2024) https://www.imf.org/external/datamapper/IEI@AIPI/ADVEC/EME/LIC/RUS/CHN.
  • Jonek-Kowalska I, ‘Assessing the energy security of European countries in the resource and economic context’ (2022) 13(2) Oeconomia Copernicana 301–334.
  • Kalai M, Becha H and Helali K, ‘Effect of artificial intelligence on economic growth in European countries: a symmetric and asymmetric cointegration based on linear and non-linear ARDL approach’ (2024) 13(22) Economic Structures 1–37 https://doi.org/10.1186/s40008-024-00345-y
  • Kamolov S, Molchanovskaya I and Kaunov E, ‘Artificial intelligence as a strategic instrument of economic development of Russia and improvement of its public administration’ in E3S Web of Conferences 291 (2021) 04002 https://doi.org/10.1051/e3sconf/202129104002.
  • Maksim B and Andrei S, ‘Central Asia: a region of economic rivalry among Russia, China, the US, and the EU’ (2009) 3(57) Central Asia and the Caucasus 79–88.
  • Maslej N and others, The AI Index 2025 Annual Report (AI Index Steering Committee, Institute for Human- Centered AI, Stanford University 2025).
  • Popkova EG and Stefanovic M, ‘Trends of the AI Economy in Russia’ (2024) 1(1) Journal of Trends and Challenges in Artificial Intelligence 1–14 https://doi.org/10.61552/JAI.2024.01.001
  • Popkova EG, Alekseev AN, Lobova SV and Sergi BS, ‘The theory of innovation and innovative development. AI scenarios in Russia’ (2020) 63 Technology in Society https://doi.org/10.1016/j.techsoc.2020.101390
  • Porter M, ‘The Competitive Advantage of Nations’ (1990) 68 Harvard Business Review 73–93 https://doi.org/10.1002/cir.3880010112
  • Prikhodko OV, ‘US Strategy on Great Power Rivalry’ (2025) (2) USA & Canada: economics, politics, culture 10–24.
  • Pu Y, Liu M and Yan C, ‘Economic evaluation of the Sichuan-Chongqing Region Based on Machine Learning’ (2021) International Conference on Information Science, Parallel and Distributed Systems (ISPDS), Hangzhou, 207–213 https://doi.org/10.1109/ISPDS54097.2021.00047
  • Qadri S, ‘The Impact of the US-China-Russia Rivalry on the Architecture of International Security at the Global and Regional Levels’ (2024) 7(1) Pakistan Journal of International Affairs 54–69.
  • Zhang Q, ‘AI-driven unemployment risk and household financial decision: Evidence from China’ (2025) 99 Journal of Asian Economics https://doi.org/10.1016/j.asieco.2025.101963
  • Zhang K and Dai J, ‘A novel TOPSIS method with decision-theoretic rough fuzzy sets’ (2022) 608 Information Sciences 1221–1244 https://doi.org/10.1016/j.ins.2022.07.009
Toplam 26 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Bölgesel Çalışmalar, Uluslararası Güvenlik, Uluslararası İlişkilerde Siyaset
Bölüm Araştırma Makalesi
Yazarlar

Ahmet Turan 0000-0002-0227-6161

Gönderilme Tarihi 19 Aralık 2025
Kabul Tarihi 26 Ocak 2026
Yayımlanma Tarihi 18 Mart 2026
DOI https://doi.org/10.17498/kdeniz.1844236
IZ https://izlik.org/JA79KG42CY
Yayımlandığı Sayı Yıl 2026 Sayı: 69

Kaynak Göster

APA Turan, A. (2026). Russia in the AI-Driven Economic Rivalry: Benchmarking the TOPSIS Model with the US and China. Karadeniz Uluslararası Bilimsel Dergi, 69, 1-14. https://doi.org/10.17498/kdeniz.1844236