{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T19:15:00Z","timestamp":1779909300800,"version":"3.53.1"},"reference-count":128,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Commun. Netw."],"abstract":"<jats:p>This review explores the evolving vision of sixth-generation (6G) networks as a paradigm shift from conventional data-centric communication to intelligence-native architectures, where meaning, context, and adaptive decision-making are central. The convergence of semantic communication, reconfigurable intelligent surfaces (RIS), and edge intelligence enables context-aware, low-latency, and resilient wireless systems. Semantic encoding prioritizes task-relevant information to reduce communication redundancy; RIS dynamically controls the wireless propagation environment to enhance energy-efficiency and coverage; and edge intelligence supports decentralized, AI-driven inference closer to end users. Together, these technologies reframe traditional quality of service (QoS) metrics, moving beyond throughput and latency toward intent-driven and context-aware service delivery. This paper presents a structured analysis of their technical foundations, integration strategies, and mutual synergies. It also highlights open challenges such as joint semantic-environment modelling, cross-layer orchestration, and secure, trustworthy deployment of distributed AI at the network edge. Looking ahead, the review outlines promising directions including quantum-aware semantic channels, bio-inspired cognition for network adaptation, intelligent metasurfaces with embedded AI, and integrated space-air-ground-sea (SAGS) architectures. These advances suggest that 6G is not merely a generational upgrade but a foundational framework for future intelligent infrastructures capable of reasoning, learning, and responding autonomously in real time.<\/jats:p>","DOI":"10.3389\/frcmn.2025.1655410","type":"journal-article","created":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T22:10:20Z","timestamp":1759183820000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["A comprehensive review of AI-native 6G: integrating semantic communications, reconfigurable intelligent surfaces, and edge intelligence for next-generation connectivity"],"prefix":"10.3389","volume":"6","author":[{"given":"Fabian Chukwudi","family":"Ogenyi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chinyere Nneoma","family":"Ugwu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Okechukwu Paul-Chima","family":"Ugwu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,9,30]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e1521","DOI":"10.1002\/widm.1521","article-title":"Evolution toward intelligent communications: impact of deep learning applications on the future of 6G technology","volume":"14","author":"Abd Elaziz","year":"2024","journal-title":"Wiley Interdiscip. 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