Applied Sciences | Open Access | DOI: https://doi.org/10.37547/tajas/Volume07Issue11-07

The Rise of the "Product-Program" Manager: How AI and Analytics Are Merging Two Critical Roles

Latypov Viacheslav , Senior Project Manager, PMO Lead/Hercules Dynamics Toronto, Canada

Abstract

The article presents a theoretical and analytical review of the transformation of management practices in the context of implementing artificial intelligence and advanced analytics. The study is based on an interdisciplinary approach that combines methods of strategic management, innovation analysis, and digital technologies. Particular attention is paid to the formation of the hybrid role of the "product-program manager," which integrates the functions of product and program management. Scenarios of AI applications are examined, including the automation of routine management processes and predictive resource allocation. A comparative analysis of traditional and hybrid managerial roles is conducted, with an emphasis on the changing role of data and the integration of analytical platforms into business processes. It is established that the implementation of AI ensures a shift from reactive to predictive management, contributes to cost reduction and faster time-to-market, and strengthens the manager’s role as an architect of the innovation cycle. Identified limitations are associated with differences in technological maturity and the need to adapt organizational structures. The article proposes a conceptual model of the evolution of managerial functions based on AI, integrating strategy, tactics, and operational execution into a single analytical framework. This work will be useful to researchers in innovation management, practitioners of digital transformation, analytics specialists, and project leaders interested in building sustainable business models in the digital economy.

Keywords

artificial intelligence, data analytics, product management, program management, product-program manager, innovation cycle, digital transformation

References

Babina, T., Fedyk, A., He, A., & Hodson, J. (2024). Artificial intelligence, firm growth, and product innovation. Journal of Financial Economics, 151, 103745. https://doi.org/10.1016/j.jfineco.2023.103745

Barcaui, A., & Monat, A. (2023). Who is better in project planning? Generative artificial intelligence or project managers? Project Leadership and Society, 4, 100101. https://doi.org/10.1016/j.plas.2023.100101

Fichtler, T., Kirchberg, L., Grigoryan, K., Koldewey, C., & Dumitrescu, R. (2024). A method for identifying use cases in data-driven product management. Procedia CIRP, 122, 539–544. https://doi.org/10.1016/j.procir.2024.01.079

Georgiev, S., Polychronakis, Y., Sapountzis, S., & Polychronakis, N. (2024). The role of artificial intelligence in project management: A supply chain perspective. Supply Chain Forum: An International Journal, 1–14. https://doi.org/10.1080/16258312.2024.2384823

Grigoryan, K., Fichtler, T., Schreiner, N., Rabe, M., Panzner, M., Kühn, A., Dumitrescu, R., & Koldewey, C. (2023). Data-driven product management: A practitioner-driven research agenda. Procedia CIRP, 119, 290–295. https://doi.org/10.1016/j.procir.2023.03.099

Mariani, M., & Dwivedi, Y. K. (2024). Generative artificial intelligence in innovation management: A preview of future research developments. Journal of Business Research, 175, 114542. https://doi.org/10.1016/j.jbusres.2024.114542

Marnewick, C., & Marnewick, A. L. (2022). Digitalization of project management: Opportunities in research and practice. Project Leadership and Society, 3, 100061. https://doi.org/10.1016/j.plas.2022.100061

Panzner, M., von Enzberg, S., & Dumitrescu, R. (2024). Developing a data analytics toolbox for data-driven product planning: A review and survey methodology. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 38, e18. https://doi.org/10.1017/S0890060424000209

Qin, W., Zhang, Y., Qu, T., & Li, X. (2022). Special issue on data-driven modeling and analytics for optimization of complex manufacturing systems. International Journal of Computer Integrated Manufacturing, 35(10–11), 1025–1027. https://doi.org/10.1080/0951192X.2022.2141948

Roberts, D. L., & Candi, M. (2024). Artificial intelligence and innovation management: Charting the evolving landscape. Technovation, 136, 103081. https://doi.org/10.1016/j.technovation.2024.103081

Stark, D., & Vanden Broeck, P. (2024). Principles of algorithmic management. Organization Theory, 5(2). https://doi.org/10.1177/26317877241257213

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How to Cite

Latypov Viacheslav. (2025). The Rise of the "Product-Program" Manager: How AI and Analytics Are Merging Two Critical Roles. The American Journal of Applied Sciences, 7(11), 61–69. https://doi.org/10.37547/tajas/Volume07Issue11-07