<![CDATA[The proliferation of AI-generated content (AIGC) has introduced a profound crisis of information authenticity across modern communication ecosystems. As large language models, generative image systems, and automated content pipelines become ubiquitous, the capacity of both individuals and institutions to distinguish authentic human-produced information from algorithmically synthesized content has been severely compromised. This systematic literature review examines the nature, scope, and communication science implications of the AIGC-driven authenticity crisis, drawing on 20 peer-reviewed studies published between 2021 and 2025. The review synthesizes evidence on how AIGC challenges fundamental epistemological assumptions embedded in communication theory, including source credibility, message authenticity, media trust, and information verification. Key findings reveal that human cognitive heuristics for detecting AI-generated language are systematically unreliable; that AIGC-enabled disinformation, deepfakes, and academic fabrication pose escalating societal risks; and that current detection and regulatory frameworks remain inadequate to the scale and velocity of AIGC proliferation. Drawing on communication science theory, this review proposes an Authentic Information Communication Framework (AICF) comprising four strategic dimensions: technological detection infrastructure, communicator transparency norms, audience critical digital literacy, and regulatory-ethical governance. Implications for communication scholars, media practitioners, policymakers, and educational institutions are discussed.]]>
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