28 April 2026
Artificial intelligence and quantum computing are often presented as competing forces shaping the future of finance. A recent article from the CFA Institute challenges this narrative, arguing that the real opportunity lies not in choosing between the two, but in understanding how they can work together.
Artificial intelligence is already deeply embedded in financial workflows, powering applications from portfolio construction to risk management and data analysis. Quantum computing, by contrast, remains an emerging technology, still in its experimental phase but with the potential to address some of the most complex computational challenges in finance.
The CFA Institute analysis highlights that quantum computing’s most significant contribution may not be to replace AI, but to expand its capabilities. Quantum systems can process information in fundamentally different ways, enabling new approaches to modeling uncertainty, correlations and high-dimensional data structures. This could allow AI systems to tackle problems that are currently beyond the reach of classical computing.
Rather than a substitution effect, the relationship between the two technologies is increasingly seen as complementary. AI provides the data-driven learning and decision-making layer, while quantum computing has the potential to accelerate specific computational tasks and unlock new types of analysis. Research suggests that combining the two could significantly improve the accuracy and efficiency of models, particularly in complex or chaotic systems.
In finance, this convergence could have far-reaching implications. Quantum computing is particularly well suited to problems involving optimization, simulation and scenario analysis - areas where traditional computing approaches face limitations. These include portfolio optimization under multiple constraints, pricing of complex derivatives and advanced risk modeling.
However, the article also emphasizes that the impact of quantum computing will be gradual. Current systems are still limited in scale and stability, and widespread adoption will require significant technological advancements. In the near term, the most realistic applications are likely to involve hybrid models, where quantum and classical computing are combined to address specific bottlenecks rather than replacing existing systems entirely.
Another important dimension is risk—particularly in cybersecurity. Quantum computing has the potential to break existing encryption methods, raising important questions for financial institutions about data protection and the need to transition toward post-quantum cryptographic standards.
For investment professionals, the key takeaway is not to view AI and quantum computing as competing technologies, but as part of a broader evolution in computational finance. AI is already delivering tangible value, while quantum computing represents a longer-term shift that could redefine the boundaries of what is computationally possible.
For members of CFA Society Italy, this perspective reinforces the importance of staying informed not only about current tools, but also about emerging technologies that may shape the future of the industry. As financial markets become increasingly data-driven and complex, the ability to understand - and eventually integrate - these innovations will be critical.
Ultimately, the article suggests that the future of finance will not be defined by a single dominant technology, but by the interaction between multiple layers of innovation. In that landscape, the convergence of AI and quantum computing may prove to be one of the most powerful drivers of change.