A Comprehensive Study of Digital Deception Prevention through Agentic AI

Abstract

In the age of the internet, the spread of manipulative content ranging from deepfakes to AI-driven disinformation challenges online security and trust to a great extent. Conventional detection models lag in managing such emerging threats, and the call for more adaptive approaches is made here. This paper presents a new framework that employs Agentic AI autonomous agents with perception, reasoning, and action capabilities to actively detect and counter digital deception. By integrating ideas from recent studies and employing multilayered, context-sensitive analysis, our system detects fake content more accurately, whether it is text, images, or videos. We also propose a hybrid workforce integration model that integrates human intelligence with autonomous agents through feedback loops and real-time collaboration, ensuring accountability and scalability. Our findings show that the integrated approach not only improves detection effectiveness but also constructs a more secure digital ecosystem. Overall, the integration of Agentic AI and a hybrid workforce model offers an encouraging solution to the battle against digital deception and the restoration of trust in online communities. Furthermore, the proposed solution demonstrates strong deployment feasibility with an estimated ROI timeline of 11 months, offering practical value and scalability for organizations combating digital deception.