AGENTIC AI AND THE FUTURE OF ARTIFICIAL GENERAL INTELLIGENCE: A STUDY ON HOW GOAL-ORIENTED AUTONOMOUS AGENTS CONTRIBUTE TO THE DEVELOPMENT OF MORE HUMAN-LIKE INTELLIGENCE, REASONING, AND DECISION-MAKING ABILITIES

Divye Dwivedi

doi:10.29121/JISSI.v2.i1.2026.44

Authors

Divye Dwivedi Performance Test Lead, Orpine Inc., USA Author

DOI:

https://doi.org/10.29121/JISSI.v2.i1.2026.44

Keywords:

Agentic AI, Artificial General Intelligence, Goal-Oriented Agents, Human-Like Reasoning, Autonomous Decision-Making, Multi-Agent Systems, Neuro-Symbolic Architectures, AI Benchmarks

Abstract

This study explores the transformative role of agentic AI goal-oriented autonomous systems in advancing toward artificial general intelligence (AGI). By integrating recent advancements in large language models (LLMs), reinforcement learning, and multi-agent frameworks, agentic AI enhances human-like reasoning, planning, and decision-making. Employing a mixed-methods approach, including analysis of benchmark datasets like AgentBench and GAIA, and surveys from over 1,300 AI professionals, the research evaluates performance metrics across cognitive tasks. Key findings reveal that agentic systems achieve 88.3% faster task completion and 90.4–96.2% cost reductions compared to human workflows, while improving reasoning accuracy by 32.5% in multi-step scenarios. However, limitations in handling edge cases and ethical biases persist. Conclusions underscore agentic AI's pivotal contribution to AGI, advocating hybrid neuro-symbolic architectures for robust, trustworthy intelligence. Implications extend to policy frameworks for safe deployment in sectors like finance and healthcare.

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