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The rapid maturation of artificial intelligence and automation technologies is driving a fundamental shift in digital firms, where business processes evolve from human-managed or rule-based automated operations to fully autonomous systems capable of self-execution, adaptation, and decision-making. This theory-development article conceptualizes the emergence of autonomous business processes and delineates their transformative implications for organizational design. Integrating streams of research on robotic process automation, algorithmic management, digital transformation, and human–AI collaboration, we advance a novel theoretical framework that explains the mechanisms of transition and the resulting reconfiguration of structures, authority distribution, and governance. We argue that increasing automation sophistication diminishes traditional hierarchical controls, fosters hybrid human-machine ecosystems, and demands new accountability frameworks to sustain strategic oversight. Six propositions articulate the causal pathways linking AI-enabled execution, process autonomy, decision authority redistribution, and organizational redesign. A conceptual model visually maps the progression from human-controlled to autonomous layers, incorporating feedback loops for continuous learning. Contributions to digital business and management studies include a foundational theory for navigating automation-induced transformations, with implications for leaders seeking to balance machine autonomy with human strategic input while mitigating risks of opacity and power imbalances. This framework provides a platform for future inquiry into the performance and ethical outcomes of autonomous processes in digital organizations.