This study examines the role of artificial intelligence-powered cyber threat intelligence sharing frameworks in enhancing national security across the United States public sector entities. Empirically, traditional silo-based cybersecurity approaches have proven insufficient for protecting government networks and critical infrastructure against the growing scale and sophistication of contemporary cyber threats. Although information sharing is widely recognized as an essential defensive strategy, existing frameworks face significant challenges, including delayed information dissemination, overwhelming data volumes, system interoperability issues, privacy protection requirements and inadequate inter-agency coordination. This study employed a comprehensive systematic literature review methodology, analyzing peer-reviewed journal articles, conference proceedings, government reports and policy documents published between 2016 and 2024, with a specific focus on information sharing frameworks, artificial intelligence architectures and empirical evidence from United States public sector organizations. The study found that AI-driven threat intelligence sharing frameworks significantly improve early warning capabilities, enhance threat detection accuracy and enable more timely cybersecurity decision-making across government agencies through automated threat detection and enhanced analytical capabilities. The findings of the study also indicated that adoption remains inconsistent across agencies due to resource disparities, fragmented governance structures and regulatory privacy constraints that limit effective data sharing among organizations. The study therefore concludes that effective AI-driven intelligence sharing requires coordinated governance frameworks, interoperable technical systems, privacy-preserving technologies and continued human oversight to strengthen national cyber defense posture, with important implications for policymakers, cybersecurity professionals and government administrators responsible for protecting critical national infrastructure.