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This survey cuts through this confusion by introducing a novel dual-paradigm framework that categorizes agentic systems into two distinct lineages: the symbolic\/classical (relying on algorithmic planning and persistent state) and the neural\/generative (leveraging stochastic generation and prompt-driven orchestration). Through a systematic PRISMA-based review of 90 studies (2018\u20132025), we provide a comprehensive analysis structured around this framework across three dimensions: (1) the theoretical foundations and architectural principles defining each paradigm; (2) domain-specific implementations in healthcare, finance, and robotics, demonstrating how application constraints dictate paradigm selection; and (3) paradigm-specific ethical and governance challenges, revealing divergent risks and mitigation strategies. Our analysis reveals that the choice of paradigm is strategic: symbolic systems dominate safety-critical domains (e.g., healthcare), while neural systems prevail in adaptive, data-rich environments (e.g., finance). Furthermore, we identify critical research gaps, including a significant deficit in governance models for symbolic systems and a pressing need for hybrid neuro-symbolic architectures. The findings culminate in a strategic roadmap arguing that the future of Agentic AI lies not in the dominance of one paradigm, but in their intentional integration to create systems that are both\n                    <jats:italic>adaptable<\/jats:italic>\n                    and\n                    <jats:italic>reliable<\/jats:italic>\n                    . This work provides the essential conceptual toolkit to guide future research, development, and policy toward robust and trustworthy hybrid intelligent systems.\n                  <\/jats:p>","DOI":"10.1007\/s10462-025-11422-4","type":"journal-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T14:59:48Z","timestamp":1763132388000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":83,"title":["Agentic AI: a comprehensive survey of architectures, applications, and future directions"],"prefix":"10.1007","volume":"59","author":[{"given":"Mohamad","family":"Abou Ali","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fadi","family":"Dornaika","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinan","family":"Charafeddine","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,14]]},"reference":[{"key":"11422_CR2","doi-asserted-by":"publisher","unstructured":"Acharya DB, Kuppan K, Divya B (2025) Agentic AI: Autonomous intelligence for complex goals\u00e2\u20ac\u201dA comprehensive survey. 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