Autonomous Personalized Cinema: A Narrative Review and Conceptual Framework

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Artificial intelligence is increasingly used across screenplay development, audiovisual generation, editing, sound production, audience analysis, and media recommendation. However, these applications remain fragmented and typically depend on continuous human direction. This narrative review examines the technical, creative, cognitive, evaluative, and ethical requirements for an artificial intelligence system to achieve runtime creative autonomy and generate a coherent film personalized for an individual viewer. Literature published through August 2026 was synthesized across computational creativity, long-form narrative generation, multimodal media synthesis, multi-agent production, viewer modeling, digital twins, visual-attention analysis, temporal recommendation, psychoacoustics, spatial audio, and responsible artificial intelligence. The review indicates that current technologies demonstrate several necessary capabilities independently, but do not yet provide an empirically validated closed-loop architecture integrating viewer understanding, creative-intent formation, long-horizon narrative planning, multimodal production, autonomous evaluation, revision, and personalized exhibition. To address this gap, the study proposes Autonomous Personalized Cinema as a computational filmmaking paradigm in which an AI system independently plans, generates, evaluates, revises, and delivers a complete audiovisual narrative within explicit human-governance constraints. A seven-layer conceptual architecture is introduced, comprising a Viewer Digital Twin, Creative Intent Engine, Narrative and World Model, Multi-Agent Virtual Film Studio, Audiovisual Generation Engine, Self-Critique and Continuity System, and Personalized Exhibition Layer. The framework further introduces a Generative Preference Memory that represents favored cinematic attributes without directly reproducing existing works. Consent, uncertainty, local processing, data minimization, provenance, similarity screening, viewer control, and safeguards against psychological manipulation are embedded throughout the architecture. The resulting framework provides research questions, testable propositions, and a staged validation programme for developing and evaluating autonomous personalized cinema while preserving human oversight, creative coherence, individual rights, and institutional accountability.