AI and System Evolution in CPD: Integrating CHAT with a Unified Theory of Emergent System Evolution

Artificial intelligence (AI) transforms how clinicians, teams, and patients make decisions and learn. That changes the activity systems in which continuing professional development (CPD) occurs. Most CPD scholarships focus on specific AI applications but lack frameworks to explain broader sociotechnical shifts across health care. This paper combines Cultural-Historical Activity Theory with a Unified Theory of Emergent System Evolution to examine how AI induces contradictions within and between activity systems and how those contradictions accelerate structural changes in learning, collaboration, identity, and governance. Cultural-Historical Activity Theory helps us observe how AI shapes tools, rules, roles, and community structures, whereas the four-phase evolutionary model describes how learning systems progress through recognizable developmental patterns: egocentric, technocentric, ecocentric, and holocentric. AI enhances transformation by amplifying tensions, creating new forms of distributed cognition across individual, team, organizational, professional, and societal levels, and ultimately, enabling expansive learning. The framework provides a conceptual toolset for designing learning ecosystems that are adaptive, relational, ethical, and resilient to changes in AI-enhanced clinical and CPD contexts.