The Impact of Artificial Intelligence on Managerial Decision-Making in Sports Organizations

Mohsen Tahmasebi Pour; Zohreh  Gerami

Authors

Mohsen Tahmasebi Pour Department of Physical Education, Par.C., Islamic Azad University, Tehran, Iran Corresponding author https://orcid.org/0000-0002-8999-2135
Zohreh Gerami Ph.D., Department of Sports Management, Education, Tehran, Iran Author https://orcid.org/0009-0003-2907-1048

Keywords:

Artificial intelligence; Managerial decision-making; Sports organizations; Predictive analytics; Organizational readiness; Sports management

Abstract

This study aimed to investigate the effect of artificial intelligence on managerial decision-making effectiveness in sports organizations in Tehran. This applied study employed a quantitative, cross-sectional, correlational design. The statistical population comprised managers, deputy managers, department heads, supervisors, and senior administrative experts working in governmental sports organizations, national federations, municipal sports institutions, professional clubs, and private sports organizations in Tehran. Using multistage sampling, 210 eligible participants were included in the final analysis. Data were collected using a researcher-developed Artificial Intelligence Application in Sports Organizations Questionnaire and a researcher-adapted Managerial Decision-Making Effectiveness Questionnaire. The instruments assessed artificial intelligence infrastructure, intelligent data analysis, application in managerial processes, organizational readiness, decision quality, decision speed, information accuracy, predictive capacity, and decision transparency and consistency. Content validity was confirmed by experts, and construct validity and reliability were assessed through confirmatory factor analysis, Cronbach’s alpha, composite reliability, and average variance extracted. Data were analyzed using Pearson correlation, multiple regression, and partial least squares structural equation modeling with 5,000 bootstrap resamples. Artificial intelligence had a positive and statistically significant effect on overall managerial decision-making effectiveness (β = 0.74, t = 19.47, p < 0.001) and explained 55% of its variance. Significant effects were also found on decision quality (β = 0.67, p < 0.001), decision speed (β = 0.59, p < 0.001), information accuracy (β = 0.72, p < 0.001), predictive capacity (β = 0.75, p < 0.001), and decision transparency and consistency (β = 0.56, p < 0.001). Multiple regression analysis showed that artificial intelligence infrastructure, intelligent data analysis, managerial application, and organizational readiness jointly explained 61% of the variance in decision-making effectiveness, with managerial application emerging as the strongest predictor (β = 0.34, p < 0.001). Artificial intelligence substantially improves managerial decision-making in sports organizations, particularly by strengthening prediction, information accuracy, decision quality, and operational responsiveness. Its effectiveness depends on integrating intelligent systems into managerial processes alongside appropriate infrastructure, organizational readiness, human oversight, and ethical governance.

References

[1] F. Al-Zahrani, H. Balbaid, W. Sadek, and A.-F. A. Hamid, "The Role of AI in Management," International Journal of Financial Administrative and Economic Sciences, vol. 3, no. 5, pp. 233-260, 2024, doi: 10.59992/ijfaes.2024.v3n5p6.

[2] S. Spoelstra and N. Butler, "Algorithmic Leadership and the Game of Business," Leadership, vol. 22, no. 3, pp. 184-201, 2026, doi: 10.1177/17427150261436598.

[3] S. S. Champa and R. S. Segall, "Integrated Data Analytics, Business Intelligence, and Machine Learning Architecture for SMEs," International Journal of Business Analytics, vol. 13, no. 1, pp. 1-38, 2026, doi: 10.4018/ijban.409371.

[4] M. A. Islam, S. Somu, and F. M. F. Aldaihani, "The Rise of Agentic AI: Synthesis of Current Knowledge and Future Research Agenda," Global Business and Organizational Excellence, vol. 45, no. 3, pp. 402-416, 2025, doi: 10.1002/joe.70019.

[5] O. Kardes, S. Eti, O. Doguc, Ö. G. Ertosun, H. Dinçer, and S. Yüksel, "Psychological Drivers of Organizational Ambidexterity: Evidence From Agentic Artificial Intelligence Supported Fuzzy Decision Modeling," 2026, doi: 10.21203/rs.3.rs-8653058/v1.

[6] A. Bieńkowska, J. Małecki, A. Mathiesen-Ohman, and K. Tworek, "Person-Ai Bidirectional Fit - A Proof-of-Concept Case Study of Augmented Human-Ai Symbiosis in Management Decision-Making Process," 2025, doi: 10.48550/arxiv.2511.13670.

[7] C. Sirawattana and C. Poolsamral, "The Use of Artificial Intelligence in Sports Science to Enhance Athlete Performance," Journal of Arts Management, vol. 8, no. 4, pp. 700-710, 2024. [Online]. Available: https://so02.tci-thaijo.org/index.php/jam/article/view/274597.

[8] N. Mateus, E. Abade, D. Coutinho, M. Á. Gómez, C. L. Peñas, and J. Sampaio, "Empowering the sports scientist with artificial intelligence in training, performance, and health management," Sensors, vol. 25, no. 1, p. 139, 2024, doi: 10.3390/s25010139.

[9] E. Narimani, F. Lotfi, and A. H. Mirzaei, "Artificial Intelligence in Team Sports: Applications and Perspectives," in Proceedings of the First International Conference on Information Technology, Management, and Computer Science, Sari, 2024, pp. 1-20. [Online]. Available: https://lutpub.lut.fi/handle/10024/168297.

[10] H. Rashki, J. Gholamian, K. Cheragh Birjandi, and M. Keshtidar, "Modeling the Functions of Artificial Intelligence in Iranian Sport Startups," Physiology and Management Research in Sport, 2024, doi: 10.22034/spmi.2025.494089.2690.

[11] E. Piri Ataei, M. Seyedameri, M. Behnam, and A. Farahani, "The Interaction of Artificial Intelligence and Strategic Management in the Future of Iran's Sport Industry," Communication Management in Sport Media, 2024, doi: 10.30473/jsm.2024.72081.1898.

[12] M. Swanson, H. Lee, and S. Kim, "Artificial intelligence-enabled surveillance systems in sports security management," Journal of Applied Security Technology, vol. 19, no. 1, pp. 50-66, 2024, doi: 10.1108/JAST-11-2023-0078.

[13] A. G. Ramírez-Gutiérrez, P. S. García, O. M. Matamoros, J. J. M. Escobar, and R. T. Padilla, "Systems Approach for the Adoption of New Technologies in Enterprises," Systems, vol. 11, no. 10, p. 494, 2023, doi: 10.3390/systems11100494.

[14] G. Shahzadi, F. Jia, L. Chen, and A. John, "AI Adoption in Supply Chain Management: A Systematic Literature Review," Journal of Manufacturing Technology Management, vol. 35, no. 6, pp. 1125-1150, 2024, doi: 10.1108/jmtm-09-2023-0431.

[15] R. Yu, L. Wu, G. Li, and Z. Wang, "Can Executives’ Digital Background Develop the Level of AI Utilization in Enterprises," Peerj Computer Science, vol. 11, p. e2848, 2025, doi: 10.7717/peerj-cs.2848.

[16] Y. Yusriadi, R. Rusnaedi, N. A. Siregar, S. Megawati, and G. Sakkir, "Implementation of Artificial Intelligence in Indonesia," International Journal of Data and Network Science, vol. 7, no. 1, pp. 283-294, 2023, doi: 10.5267/j.ijdns.2022.10.005.

[17] A. S. Odeibat, "Exploring the Impact of Managerial Capabilities on the Innovation Potential of Artificial Intelligence and Organizational Capabilities: A Literature Review," Review of Applied Socio-Economic Research, vol. 26, no. 2, 2023, doi: 10.54609/reaser.v26i2.420.

[18] R. Ramachandran, V. Babu, and V. P. Murugesan, "Human Resource Analytics Revisited: A Systematic Literature Review of Its Adoption, Global Acceptance and Implementation," Benchmarking an International Journal, vol. 31, no. 7, pp. 2360-2390, 2023, doi: 10.1108/bij-04-2022-0272.

[19] W. Hong, "Ethical Concerns Upon Artificial Intelligence Empowered Human Resource Management: A Qualitative Study Among Middle-Level Managers From Beijing Technology Companies," International Journal for Multidisciplinary Research, vol. 6, no. 5, 2024, doi: 10.36948/ijfmr.2024.v06i05.28860.

[20] L. Iosif, "The Sociology of Managerial Communication in the Era of Artificial Intelligence," Bulletin of the Transilvania University of Braşov Series Vii Social Sciences • Law, pp. 135-144, 2024, doi: 10.31926/but.ssl.2024.17.66.1.18.

[21] S. Barreno-Alcalde, A.-T. Delso-Vicente, and A. Rivera-Heredia, "Algorithmic Ethics in Corporate Contexts: Knowledge Mapping for Responsible Management," Journal of Management & Organization, vol. 32, no. 2, pp. 632-663, 2026, doi: 10.1017/jmo.2026.10089.

[22] D. Upadhyay, "How Does AI Pose Challenges for Leaders in Organizations? -a Conceptual Study," Journal of Educational & Psychological Research, vol. 5, no. 3, 2023, doi: 10.33140/jepr.05.03.03.

[23] S. Hossain, M. Fernando, and S. Akter, "The Influence of Artificial Intelligence-Driven Capabilities on Responsible Leadership: A Future Research Agenda," Journal of Management & Organization, vol. 31, no. 5, pp. 2360-2384, 2025, doi: 10.1017/jmo.2025.10010.

[24] L. W. Norton, A. W. Howell, J. A. DiGirolamo, and T. L. Hayes, "Using Artificial Intelligence in Consulting Psychology," Consulting Psychology Journal Practice and Research, vol. 76, no. 2, pp. 137-162, 2024, doi: 10.1037/cpb0000274.

[25] O. Flak, "Online Managerial Tools as Research Tools to Apply Artificial Management: Results of Research," International Conference on Ai Research, vol. 4, no. 1, pp. 115-125, 2024, doi: 10.34190/icair.4.1.3190.