A combination of quantum computing and artificial intelligence is referred to as quantum AI. Normal computers process data in the form of 0 or 1, whereas quantum computers use qubits, which process both 0 and 1 simultaneously. This increases the speed and efficiency of quantum computers. Artificial intelligence algorithms analyze large amounts of data to recognize patterns and make informed decisions. These algorithms also focus on incorporating human intelligence into their decision-making processes.
Faster processing is achieved when quantum computing and artificial intelligence are combined. Quantum AI is an emerging field that aims to achieve optimization, develop new materials, and simulate complex systems. The global quantum AI market accounted for $0.2 billion in 2023 and is expected to reach $3.9 billion by 2032, growing at a CAGR of 36.6% from 2024 to 2032.
Usage of Quantum AI across industries
Quantum AI is mainly used to handle large amounts of data and optimize problems quickly and accurately. Innovations in quantum processors, such as the application of advanced algorithms or qubit technology, enable the efficient solution of complex problems. It is used in cybersecurity, material science, drug discovery, financial modelling, and other sectors. It is used to develop enhanced encryption methods in cybersecurity.
Also, it helps detect security breaches in the cybersecurity field. By studying the behavior of materials at the quantum level, quantum AI helps enhance energy storage or lead to the discovery of advanced materials in the field of material science. Similarly, it can be used to understand molecular interactions in various drugs, which helps accelerate the drug discovery process. It helps analyze market behavior and improves risk management in the field of financial modelling.
Apart from the above, quantum AI is also useful in optimizing problems related to logistics and supply chain management. Furthermore, based on the ability of AI to process and understand human language, quantum AI is utilized to enhance machine translation, thereby improving the natural language processing sector of artificial intelligence, which is currently applied in various fields.
Role of Quantum AI in cybersecurity and banking
There is an increasing need for enhanced security measures to prevent data breaches across all sectors. The development of powerful AI solutions helps improve speed and power, thereby reducing the likelihood of security breaches.
There is a rise in the use of digital banking and fintech services, which increases the volume of electronic financial records, including information about banks and their customers. These data are not immune to cybercrime, which increases the adoption of quantum cryptography solutions that help prevent data from being compromised by cyberattacks.
These quantum cryptography solutions utilize quantum computing, which has the potential to solve complex problems that traditional computers cannot handle. This increases the need for AI solutions that help strengthen encryption methods, in turn enhancing the security of the data.
In FY 2023, India recorded nearly 114 billion digital payment transactions, according to the RBI. There is an increase in the prevalence of digital payments, which leads banks to adopt quantum cryptography as electronic transactions depend on encryption to protect businesses and customers from cyberattacks.
Notable initiatives taken by industry leaders in Quantum AI
In June 2024, Microsoft announced two new functions for its Azure Quantum Elements platform: accelerated density functional theory (DFT) and generative chemistry. These two new functions aim to accelerate quantum mechanical simulations, simplify molecular discovery, and support the development of a future quantum supercomputer for handling complex simulations.
In April 2025, Terra Quantum introduced its closed beta of TQ42 Studio, a new platform for integrated quantum-classical AI development. It announced the QAI Hub and Qode Engine. The QAI Hub is a no-code quantum ML platform, and the Qode Engine is a Python SDK that enables hybrid quantum-classical AI development.
In February 2025, Quantinuum launched a generative quantum AI framework (Gen QAI) that utilizes quantum-generated data to solve complex problems that conventional classical computers cannot handle. They helped Quantinuum enable commercial applications in various sectors, such as healthcare, to develop new medicines and secure financing for accurate predictive modeling in financial industries.
Conclusion
The quantum AI industry holds immense potential to transform industries such as healthcare, finance, cybersecurity, and materials science, enabling advanced problem-solving as data becomes increasingly complex. The demand for faster and more secure solutions continues to grow. Continuous innovations and the growing demand for quantum-safe security solutions are expected to drive industry growth in the years to come.
