# Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directions

arXiv: https://arxiv.org/abs/2510.25445 · HTML: https://mlsanity.com/paper/2510.25445/

## Key facts

- Cited by 48 papers in the map (data through 14 Oct 2026).
- Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use.
- Builds on 90 of its 177 references that are in the map.
- First posted on arXiv 29 Oct 2025.

## Placed in

- LLM agents and tool use / [General LLM agent frameworks and benchmarks](https://mlsanity.com/agents/general-llm-agent-frameworks-and-benchmarks/)

## Builds on (most cited first, 30 of 90)

- [A Survey of Large Language Models](https://mlsanity.com/paper/2303.18223/) (2023)
- [A Survey on Large Language Model based Autonomous Agents](https://mlsanity.com/paper/2308.11432/) (2023)
- [AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation](https://mlsanity.com/paper/2308.08155/) (2023)
- [Gorilla: Large Language Model Connected with Massive APIs](https://mlsanity.com/paper/2305.15334/) (2023)
- [AgentBench: Evaluating LLMs as Agents](https://mlsanity.com/paper/2308.03688/) (2023)
- [GAIA: a benchmark for General AI Assistants](https://mlsanity.com/paper/2311.12983/) (2023)
- [The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery](https://mlsanity.com/paper/2408.06292/) (2024)
- [Multi-Agent Collaboration Mechanisms: A Survey of LLMs](https://mlsanity.com/paper/2501.06322/) (2025)
- [Cognitive Architectures for Language Agents](https://mlsanity.com/paper/2309.02427/) (2023)
- [AI Alignment: A Comprehensive Survey](https://mlsanity.com/paper/2310.19852/) (2023)
- [Agent-as-a-Judge: Evaluate Agents with Agents](https://mlsanity.com/paper/2410.10934/) (2024)
- [Survey on Evaluation of LLM-based Agents](https://mlsanity.com/paper/2503.16416/) (2025)
- [Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks](https://mlsanity.com/paper/2503.09572/) (2025)
- [Agent S: An Open Agentic Framework that Uses Computers Like a Human](https://mlsanity.com/paper/2410.08164/) (2024)
- [Efficient Large Language Models: A Survey](https://mlsanity.com/paper/2312.03863/) (2023)
- [Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools](https://mlsanity.com/paper/2405.20362/) (2024)
- [Agent AI: Surveying the Horizons of Multimodal Interaction](https://mlsanity.com/paper/2401.03568/) (2024)
- [AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges](https://mlsanity.com/paper/2505.10468/) (2025)
- [The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey](https://mlsanity.com/paper/2404.11584/) (2024)
- [Magma: A Foundation Model for Multimodal AI Agents](https://mlsanity.com/paper/2502.13130/) (2025)
- [Harms from Increasingly Agentic Algorithmic Systems](https://mlsanity.com/paper/2302.10329/) (2023)
- [BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices](https://mlsanity.com/paper/2411.12990/) (2024)
- [Agentic Reasoning and Tool Integration for LLMs via Reinforcement Learning](https://mlsanity.com/paper/2505.01441/) (2025)
- [Agentic Large Language Models, a survey](https://mlsanity.com/paper/2503.23037/) (2025)
- [Large Multimodal Agents: A Survey](https://mlsanity.com/paper/2402.15116/) (2024)
- [Lifelong Learning of Large Language Model based Agents: A Roadmap](https://mlsanity.com/paper/2501.07278/) (2025)
- [InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning](https://mlsanity.com/paper/2309.13064/) (2023)
- [Visibility into AI Agents](https://mlsanity.com/paper/2401.13138/) (2024)
- [Agentic AI for Scientific Discovery: A Survey of Progress, Challenges, and Future Directions](https://mlsanity.com/paper/2503.08979/) (2025)
- [TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems](https://mlsanity.com/paper/2506.04133/) (2025)

## Built on by (most cited first, 30 of 48)

- [Agentic Artificial Intelligence (AI): Architectures, Taxonomies, and Evaluation of Large Language Model Agents](https://mlsanity.com/paper/2601.12560/) (2026)
- [QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities](https://mlsanity.com/paper/2602.00185/) (2026)
- [EvoGuard: An Extensible Agentic RL-based Framework for Practical and Evolving AI-Generated Image Detection](https://mlsanity.com/paper/2603.17343/) (2026)
- [Willful Disobedience: Automatically Detecting Failures in Agentic Traces](https://mlsanity.com/paper/2603.23806/) (2026)
- [Memanto: Typed Semantic Memory with Information-Theoretic Retrieval for Long-Horizon Agents](https://mlsanity.com/paper/2604.22085/) (2026)
- [Agentic AI in the Software Development Lifecycle: Architecture, Empirical Evidence, and the Reshaping of Software Engineering](https://mlsanity.com/paper/2604.26275/) (2026)
- [Towards trustworthy agentic AI: a comprehensive survey of safety, robustness, privacy, and system security](https://mlsanity.com/paper/2605.23989/) (2026)
- [The Path Ahead for Agentic AI: Challenges and Opportunities](https://mlsanity.com/paper/2601.02749/) (2026)
- [From Prompt-Response to Goal-Directed Systems: The Evolution of Agentic AI Software Architecture](https://mlsanity.com/paper/2602.10479/) (2026)
- [Agentic AI Systems in Electrical Power Systems Engineering: Current State-of-the-Art and Challenges](https://mlsanity.com/paper/2511.14478/) (2025)
- [A Formal Security Framework for MCP-Based AI Agents: Threat Taxonomy, Verification Models, and Defense Mechanisms](https://mlsanity.com/paper/2604.05969/) (2026)
- [Switchcraft: AI Model Router for Agentic Tool Calling](https://mlsanity.com/paper/2605.07112/) (2026)
- [Autonomy and Agency in Agentic AI: Architectural Tactics for Regulated Contexts](https://mlsanity.com/paper/2605.12105/) (2026)
- [Socio-technical aspects of Agentic AI](https://mlsanity.com/paper/2601.06064/) (2025)
- [DeepER-Med: Advancing Deep Evidence-Based Research in Medicine Through Agentic AI](https://mlsanity.com/paper/2604.15456/) (2026)
- [UniManip: General-Purpose Zero-Shot Robotic Manipulation with Agentic Operational Graph](https://mlsanity.com/paper/2602.13086/) (2026)
- [InconLens: Interactive Visual Diagnosis of Behavioral Inconsistencies in LLM-based Agentic Systems](https://mlsanity.com/paper/2603.28106/) (2026)
- [Context Kubernetes: Declarative Orchestration of Enterprise Knowledge for Agentic AI Systems](https://mlsanity.com/paper/2604.11623/) (2026)
- [Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges](https://mlsanity.com/paper/2605.02592/) (2026)
- [Discoverable Agent Knowledge -- A Formal Framework for Agentic KG Affordances (Extended Version)](https://mlsanity.com/paper/2605.19186/) (2026)
- [From Siloed Algorithms to Compliance-First Agentic Platforms: A Multi-Layered Architecture for Hospital AI Systems](https://mlsanity.com/paper/2608.06112/) (2026)
- [Agentic AI for Autonomous, Explainable, and Real-Time Credit Risk Decision-Making](https://mlsanity.com/paper/2601.00818/) (2025)
- [Visioning Human-Agentic AI Teaming: Continuity, Tension, and Future Research](https://mlsanity.com/paper/2603.04746/) (2026)
- [Semantic Feature Analysis: Improving Agents Without Searching Over Rollouts](https://mlsanity.com/paper/2604.10513/) (2026)
- [Agentic Frameworks for Reasoning Tasks: An Empirical Study](https://mlsanity.com/paper/2604.16646/) (2026)
- [Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures](https://mlsanity.com/paper/2604.18133/) (2026)
- [Fair Agents: Balancing Multistakeholder Alignment in Multi-Agent Personalization Systems](https://mlsanity.com/paper/2605.02379/) (2026)
- [Why Neighborhoods Matter: Traversal Context and Provenance in Agentic GraphRAG](https://mlsanity.com/paper/2605.15109/) (2026)
- [AI-Native Network Controller: A Modular Framework for Safe Agentic Control of Multi-Domain Network Infrastructure](https://mlsanity.com/paper/2606.20565/) (2026)
- [Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems](https://mlsanity.com/paper/2606.25533/) (2026)

## Abstract (arXiv)

Agentic AI represents a transformative shift in artificial intelligence, but its rapid advancement has led to a fragmented understanding, often conflating modern neural systems with outdated symbolic models -- a practice known as conceptual retrofitting. 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--2025), 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 adaptable and reliable. This work provides the essential conceptual toolkit to guide future research, development, and policy toward robust and trustworthy hybrid intelligent systems.