Modern technology products are increasingly defined by the convergence of embedded hardware platforms, sophisticated software ecosystems, cloud-connected services, and artificial intelligence capabilities. This convergence has fundamentally transformed the role of technical program management. Traditional coordination models designed for relatively independent development domains are often insufficient for managing the complexity generated by highly integrated hardware– software systems operating across organizational boundaries. As products become more intelligent, connected, and adaptive, technical program managers must function not only as coordinators but also as systems integrators capable of aligning engineering disciplines, product organizations, quality functions, operational teams, and AI development groups. This paper presents a systems-oriented framework for technical program management within contemporary hardware–software ecosystems. The analysis examines how complexity emerges across technical architectures and organizational structures simultaneously, requiring integrated approaches to governance, decision-making, dependency management, risk mitigation, and cross-functional execution. Particular attention is given to the growing influence of artificial intelligence on embedded product development and the organizational challenges associated with integrating AI systems into large-scale technology programs. The paper argues that successful product execution depends increasingly on the ability to manage relationships among interconnected technical and human systems. Organizations that adopt systems-oriented technical program management practices are better positioned to coordinate complexity, accelerate innovation, improve product quality, and sustain long-term operational effectiveness within rapidly evolving technology environments.