The rapid integration of artificial intelligence (AI), machine learning, robotics, and intelligent automation has transformed the nature of work across industries. Human–machine collaboration (HMC) has become a strategic capability, allowing organizations to leverage the complementary strengths of humans—creativity, judgment, empathy—and machines—speed, precision, scalability. This paper develops a conceptual theory of Human–Machine Collaboration Patterns in Modern Workplaces, describing how tasks are distributed, coordinated, and integrated across humans and intelligent systems. Drawing upon theories of socio-technical systems, cognitive augmentation, human–AI teaming, and organizational design, this research proposes a comprehensive framework detailing five major collaboration patterns: human-led, machine-led, hybrid orchestration, autonomous teaming, and continuous learning loops. The article highlights implications for productivity, decision quality, employee experience, trust, and organizational performance. It concludes by outlining governance considerations and future research directions.