Artificial Intelligence Capability and Organizational Performance: The Mediating Role of Innovation Capability Across Education and Corporate Sectors

This study examined the relationship between artificial intelligence capability and organizational performance, with innovation capability as a mediating variable across the education and corporate sectors. Using a quantitative, non-experimental descriptive-correlational design, data were collected through an online survey from 400 respondents, consisting of 200 from the education sector and 200 from the corporate sector. The research instrument was subjected to expert validation and pilot testing prior to its actual administration. Data were analyzed using weighted mean, Pearson correlation, independent samples t-test, and mediation analysis. The findings revealed that artificial intelligence capability, innovation capability, and organizational performance were all rated high in both sectors, although the corporate sector consistently obtained higher mean scores than the education sector across all variables. Significant positive relationships were found between artificial intelligence capability and innovation capability (r = 0.67, p < .001), innovation capability and organizational performance (r = 0.70, p < .001), and artificial intelligence capability and organizational performance (r = 0.64, p < .001). Further analysis showed that innovation capability significantly mediated the relationship between artificial intelligence capability and organizational performance, indicating partial mediation. The study concludes that artificial intelligence capability is a significant organizational resource that enhances organizational performance both directly and indirectly through innovation capability, while sectoral context also influences the extent to which these capabilities are developed and translated into performance outcomes. The findings provide practical insights for organizations seeking to strengthen AI adoption, innovation practices, and performance improvement strategies.

Artificial intelligence capability, innovation capability, organizational performance

1. Asirit, B. L., & Hua, J. H. (2023). Converging perspectives: Assessing AI readiness and utilization in Philippine higher education. Polaris Global Journal of Scholarly Research and Trends, 2(3), 1–50. [Google Scholar] [Crossref]

2. https://doi.org/10.58429/pgjsrt.v2n3a152 [Google Scholar] [Crossref]

3. Betito, A. D., Dela Cruz, M. D. G., Sario, J. A., & Labalan, E. L. (2025). Strategic integration of artificial intelligence in total quality management: A model for sustainable transformation in Philippine higher education. TPM – Testing, Psychometrics, Methodology in Applied Psychology,32(S9),1–8. [Google Scholar] [Crossref]

4. Betito, A. D., Sario, J. A., & Bacay, R. B. R. (2025). An empirical study on the integration of artificial intelligence into total quality management: An assessment of benefits and challenges in higher education. International Journal of Research and Innovation in Applied Science, 10(6), 306–336. [Google Scholar] [Crossref]

5. https://doi.org/10.51584/IJRIAS.2025.10060020 [Google Scholar] [Crossref]

6. Ellström, D., Holtström, J., Berg, E., & Josefsson, C. (2022). Dynamic capabilities for digital transformation. Journal of Strategy and Management, 15(2), 272–286. [Google Scholar] [Crossref]

7. https://doi.org/10.1108/JSMA-04-2021-0089 [Google Scholar] [Crossref]

8. Gao, Y., Liu, S., & Yang, L. (2025). Artificial intelligence and innovation capability: A dynamic capabilities perspective. International Review of Economics & Finance, 98, 103923. [Google Scholar] [Crossref]

9. https://doi.org/10.1016/j.iref.2025.103923 [Google Scholar] [Crossref]

10. Gao, Y., Liu, Y., & Wu, W. (2025). How does artificial intelligence capability affect product innovation in manufacturing enterprises? Evidence from China. Systems, 13(6), 480. [Google Scholar] [Crossref]

11. https://doi.org/10.3390/systems13060480 [Google Scholar] [Crossref]

12. Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. [Google Scholar] [Crossref]

13. https://doi.org/10.1016/j.im.2021.103434 [Google Scholar] [Crossref]

14. Mikalef, P., Islam, N., Parida, V., Singh, H., & Altwaijry, N. (2023). Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective. Journal of Business Research, 164, 113998. [Google Scholar] [Crossref]

15. https://doi.org/10.1016/j.jbusres.2023.113998 [Google Scholar] [Crossref]

16. Mikalef, P., Lemmer, K., Schaefer, C., Ylinen, M., Fjørtoft, S. O., Torvatn, H. Y., Gupta, M., & Niehaves, B. (2023). Examining how AI capabilities can foster organizational performance in public organizations. Government Information Quarterly, 40(2), 101797. [Google Scholar] [Crossref]

17. https://doi.org/10.1016/j.giq.2022.101797 [Google Scholar] [Crossref]

18. Sulasula, J. (2023). Towards algorithmic university: Assessing the readiness of State Universities and Colleges (SUCs) in Zamboanga Peninsula, the Philippines. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4505296 [Google Scholar] [Crossref]

• The Role of Artificial Intelligence in Revolutionizing Library Services in Nairobi: Ethical Implications and Future Trends in User Interaction
• ESPYREAL: A Mobile Based Multi-Currency Identifier for Visually Impaired Individuals Using Convolutional Neural Network
• Comparative Analysis of AI-Driven IoT-Based Smart Agriculture Platforms with Blockchain-Enabled Marketplaces
• AI-Based Dish Recommender System for Reducing Fruit Waste through Spoilage Detection and Ripeness Assessment
• SEA-TALK: An AI-Powered Voice Translator and Southeast Asian Dialects Recognition