AI-Twin: AI-Powered Digital Twin for Personalized Assistance and Predictive Decision- Making

Dr. Karthi Govindharaju, Janani R, Dr. Rajarajachozhan C and Mirudhula D
Additional contact information
Dr. Karthi Govindharaju: Artificial Intelligence and Data Science Saveetha Engineering College Chennai, India
Janani R: Artificial Intelligence and Data Science Saveetha Engineering College Chennai, India
Dr. Rajarajachozhan C: Electronics and Communication Engineering Saveetha Engineering College, Chennai, India
Mirudhula D: Artificial Intelligence and Data Science Saveetha Engineering College Chennai, India

International Journal of Research and Scientific Innovation, 2025, vol. 12, issue 3, 609-617

Abstract: AI-driven digital assistants are vital for automating operations and optimizing user interactions, but current systems tend to lack adaptability, contextuality, and real-time learning. AI Twin is a future-generation digital twin created with the intent of personalized assistance and predictive decision-making. With the use of reinforcement learning, it learns and adjusts to user actions in real-time, fine-tuning responses and enhancing decision-making capabilities with the passage of time. As opposed to traditional AI assistants, AI Twin focuses on privacy using local data processing, minimizing cloud dependency while ensuring security. The platform combines natural language processing, speech recognition, and multi-agent learning to improve personalization and automation in different domains, such as smart environments and real-time decision support. This paper introduces AI Twin architecture, contrasts it with current AI technology, and delineates its prospect to drive forward AI- based user support.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.rsisinternational.org/journals/ijrsi/d ... -issue-3/609-617.pdf (application/pdf)
https://rsisinternational.org/journals/ijrsi/artic ... ive-decision-making/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjc:journl:v:12:y:2025:i:3:p:609-617

Access Statistics for this article

International Journal of Research and Scientific Innovation is currently edited by Dr. Renu Malsaria

More articles in International Journal of Research and Scientific Innovation from International Journal of Research and Scientific Innovation (IJRSI)
Bibliographic data for series maintained by Dr. Renu Malsaria ().