TITLE:
AI-Enhanced Behavioral Retirement Planning: A Conceptual Framework
AUTHORS:
Divya Srivastava
KEYWORDS:
Artificial Intelligence (AI), Generative AI, GPT Models, Reinforcement Learning, Behavioral Economics, Retirement Planning, Healthcare Simulation, Conversational Interfaces, Voice Assistants
JOURNAL NAME:
Open Access Library Journal,
Vol.12 No.11,
November
10,
2025
ABSTRACT: This paper introduces a novel AI-enhanced retirement planning platform that integrates behavioral economics principles with advanced machine learning techniques to optimize financial decision-making. Traditional financial planning models, while numerically sound, often fail to consider the cognitive biases and behavioral patterns that influence individual choices. Our system addresses this gap by incorporating mechanisms that counteract biases such as loss aversion, present bias, and overconfidence—common deterrents to long-term financial planning. The proposed architecture comprises modular layers for data integration, AI-driven analysis, and a responsive user interface that delivers personalized behavioral nudges. The platform leverages deep reinforcement learning, natural language processing using GPT-4, and predictive healthcare simulations to create a highly personalized and adaptive retirement planning experience. This work represents a significant advancement toward personalized, equitable, and behaviorally informed financial technologies.