AI-generated summary
Quantum computing is poised to transform the computing landscape by enabling faster and more complex calculations, especially when combined with artificial intelligence (AI) and machine learning. Experts at the Bankinter Innovation Foundation forum highlighted its potential applications across various sectors, as detailed in McKinsey & Company’s report “Quantum computing: An emerging ecosystem and industry use cases.” The report categorizes quantum computing applications into quantum simulation, quantum linear algebra for AI, quantum optimization and search, and quantum factorization, with near-term benefits expected in pharmaceuticals, chemicals, automotive, finance, logistics, and energy.
In pharmaceuticals, quantum computing could significantly speed up drug discovery and development, reducing costs and time. The chemical industry can leverage quantum simulations to develop more efficient and sustainable materials. Automotive uses include R&D, design, and smart city traffic management, while finance benefits from improved portfolio and risk management through advanced quantum algorithms. Quantum computing also promises enhanced logistics optimization and more efficient energy grid management by integrating renewable sources. However, challenges remain, including maintaining quantum coherence, error correction, and developing practical algorithms. Security concerns arise from quantum computers’ ability to break current cryptographic standards, necessitating new protections. Governments must accelerate investments, streamline regulations, and foster collaboration across sectors, alongside workforce training, to harness this technology’s potential. As Brian Lenahan emphasizes, cultivating “quantum inspired” thinking is essential for innovation and gaining competitive advantage in this rapidly evolving field.
Various industries will see their business opportunities increase as this technology evolves
Quantum computing is redefining the boundaries of computing and will enable increasingly innovative solutions, thanks to the ability to perform more complex and potentially much faster calculations for specific problems. This technology, especially in combination with artificial intelligence and machine learning, has captured the attention of the technological world for its promising applications in a wide range of sectors, as advanced by the experts participating in the forum dedicated to the ‘silent revolution of AI and quantum computing’ organized by the Bankinter Innovation Foundation.
The report ‘Quantum computing: An emerging ecosystem and industry use cases‘ prepared by McKinsey & Company lists several use cases divided into four categories: quantum simulation, quantum linear algebra for AI and machine learning, quantum optimization and search, and quantum factorization. From the point of view of practical applications, the report focuses on the sectors that could benefit most in the short term from this technology: pharmaceuticals, chemicals, automotive and finance.
In the biopharmaceutical industry, quantum computing combined with AI could revolutionize the research and development of molecular structures, as well as generate value in production. For example, today new drugs require an average of two billion dollars and more than ten years to reach the market after their discovery: quantum computing could make the path faster and the results more accurate.
Similarly, in the chemical industry, quantum computing can be used to obtain an accurate and detailed simulation of complex chemical reactions, favoring and accelerating the development of new, more efficient and sustainable materials, catalysts, and chemical processes. In this way, researchers can explore the behavior of molecular systems more deeply and predict the properties of new compounds with unprecedented precision. This opens the door to significant innovations in sectors such as pharmaceuticals, advanced materials production, and green chemistry.
The automotive sector can also benefit from quantum computing+AI in the functions of R+D, design, supply chain management, production, and mobility and traffic management in a Smart City context. Instead, quantum computing use cases in finance focus on portfolio and risk management. Advanced algorithms allow for more accurate and faster simulation of financial markets, favoring faster and more accurate decisions. A significant example is the evolution of the Monte Carlo method with quantum circuits.
In the logistics and transportation sector, quantum computing can optimize transport routes, reducing delivery times and operating costs. Quantum algorithms can solve problems in distribution planning more efficiently, improving supply chain management and the overall customer experience, also finding optimal solutions to complex problems in much shorter times than those employed by classical algorithms, thus improving operational efficiency in various industrial sectors.
But the opportunities also concern other sectors. For example, quantum computing offers potentially revolutionary applications in the energy sector, contributing to the design of more efficient and sustainable energy grids and systems. With the ability to optimize complex models for forecasting energy demand and supply, quantum computers can maximize resource efficiency and integrate renewable energy sources more effectively into the power grid.
Quantum computing combined with AI therefore represents a significant shift in the evolution of technology, with transformative impacts across a wide range of market sectors. However, it is a field in which research is still far from providing definitive answers and the challenges remain many. For example, the ability to solve complex cryptographic problems much faster than classical computers entails the need to develop new security standards to ensure the protection of sensitive information.
In addition, one of the main scientific obstacles to quantum computing is the consistency of the results, compromised by the physical environment. It is necessary to develop quantum algorithms for real use cases and to mature technologically by moving from prototypes to production systems. Maintaining quantum coherence and handling errors are crucial problems to solve in order to make quantum computers a practical reality.
On the other hand, governments must speed up bureaucratic processes and invest significantly in these technologies, boosting industry and creating a favorable environment for innovation, facilitating collaboration between research institutions, industries and startups. In addition, training and continuing education are essential to develop a workforce capable of determining where and how to invest in quantum technologies.
As Brian Lenahan, founder of the Quantum Strategy Institute, suggests, it is necessary to promote ‘quantum inspired‘ thinking throughout the organization and in society in general, fostering a curious and innovative mindset. The speed with which significant developments are expected in this field underlines the importance of acting promptly and strategically: those who are able to fully understand and exploit the potential of this technology will enjoy a decisive competitive advantage.
