The Future of Artificial General Intelligence (AGI): Quantum–AI Synergy for Human-Like Cognitive Systems

Authors

  • Muhammad Umar Khan Department of Computer Science, Abdul Wali Khan University, Mardan Author
  • Dr. Muhammad Khalid Assistant Professor, DHA Suffa University Author
  • Muhammad Burhan Azam Lecturer, Department of Computer Science, National University of Modern Languages - Lahore Campus Author
  • Adnan Ahmed Rafique Assistant Professor, Department of CS and IT, University of Poonch Rawalakot Author
  • Yasir Javaid Department of CS & IT, University of Poonch Rawalakot Author

DOI:

https://doi.org/10.53762/grjnst.03.04.23

Keywords:

AGI, artificial intelligence, cognitive systems, quantum computing, quantum–AI synergy, self-learning

Abstract

The future of Artificial General Intelligence (AGI) lies in the fusion of quantum computing and artificial intelligence, creating a synergistic framework capable of human-like cognitive reasoning and adaptability. This study examined how quantum–AI integration enhances computational efficiency, learning capacity, and contextual understanding beyond the limits of classical AI systems. The findings highlighted that quantum-inspired neural networks, through their ability to process complex data in parallel, can enable AGI systems to simulate decision-making, perception, and self-learning in a manner closer to human cognition. Moreover, the research emphasized the ethical and governance challenges that accompany such advancements, including issues of transparency, control, and the moral implications of autonomous systems. The study proposed that responsible innovation, combined with interdisciplinary collaboration, is essential for aligning AGI’s development with societal values and global policy frameworks. Overall, the quantum–AI synergy was found to be a critical driver toward achieving general intelligence, offering unprecedented potential for innovation across scientific, industrial, and educational domains while raising profound ethical considerations for the future of human–machine coexistence.

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Published

2026-01-02

Issue

Section

Articles