Advances and Challenges in the Integration of Quantum Computing in Artificial Intelligence: A Systematic Review

Valencia Y.R.V.; Flores A.N.S.; Huarez J.P.S.; Palomino J.A.C.; Falcon F.M.H.; Huaman O.P.; Castañeda L.B. · Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (2026) · DOI: 10.58346/jowua.2026.i1.001

Resumen

The main objective of the research is to analyze the incorporation of quantum computing in artificial intelligence, focusing on applications, tools, and challenges. Through a systematic approach of literature review in academic databases, a growing interest in this integration was detected, particularly in fields such as physics, medicine, chemistry, and cybersecurity. It highlights the effectiveness of quantum algorithms in complex Artificial Intelligence issues such as factorization and unordered search. Challenges include the vulnerability of qubits and the demand for scalable quantum hardware. The research recognizes booming tools for quantum data modeling for Artificial Intelligence, examines innovative applications in materials design and agriculture, and suggests areas for future research. It highlights the importance of creating more efficient quantum algorithms and optimizing their integration.

Instituciones: Universidad César Vallejo