Quantum computing applications: where it really creates value

The potential of quantum computing is at the centre of the global debate, but it is rarely told objectively. Between those who promise imminent revolutions and those who dismiss the technology as mere hype, a pragmatic guide to understanding the real state of affairs is often missing. This page was created to fill that gap and offers a concrete map built on three pillars.

• The four real application families, namely optimisation, simulation, security and machine learning.
• An objective analysis of the documented state of maturity and of the industrial sectors actually involved.
• An operational approach, with practical guidance for taking the first steps in a company.

While the specialist sections of the site – from post-quantum cryptography to the vertical applications for healthcare and finance – explore the individual territories in depth, this page offers the overall picture and the strategic criteria for finding one's bearings. The yardstick remains constant. Quantum computing applications are always judged in direct comparison with the best classical baselines, on measured numbers and not on future promises.

What are the application families of quantum computing?

There are four families and it is worth learning them as a stable taxonomy. Combinatorial optimisation covers routing, scheduling and allocation, that is, the problems in which the number of combinations explodes. The simulation of natural quantum systems concerns molecules, materials and catalysts, the territory of quantum simulation with the most solid theoretical advantage. Security stems from the threat posed by Shor's algorithm to current cryptography and from the post-quantum transition that follows. Quantum machine learning remains the most exploratory family, treated with due realism on the page on quantum machine learning. Every serious use case falls into one of these four boxes.

What is mature and what is promising?

Mature for immediate action is cryptographic preparation, because the ‘harvest now, decrypt later’ threat is active today and the defence standards already exist. Mature for prototyping are optimisation and molecular simulation on reduced instances, where variational algorithms are developed entirely in emulation. Promising is quantum advantage on small-scale industrial problems, such as scheduling, as well as simulation in chemistry. Exploratory, instead, is quantum machine learning on classical data. No application with a demonstrated advantage is in production today, and whoever claims otherwise has yet to present the classical baseline. This snapshot, promising even if limited, is the right starting point for investing well, because it distinguishes real deadlines from futuristic promises.

How do optimisation applications work?

The problem is formulated as the minimisation of a cost function, often in QUBO form, and entrusted to variational algorithms such as QAOA or to dedicated quantum annealing machines. Typical cases include fleet routing and last-mile logistics, production and maintenance scheduling, portfolio allocation and risk management, and the sizing of energy networks. The state of the art, however, demands clarity. On these problems classical solvers are excellent, and the comparison must be made against them, not against brute force. The current value lies in prototyping the formulations, measuring how they scale and being ready; work that is done today, in emulation and at extremely low cost.

How do simulation applications work?

This is the family of applications with the most solid and impactful theoretical foundation. Natural quantum systems can be mapped natively and directly onto quantum hardware, outperforming classical computers which, by contrast, run up against an exponential computational cost. The concrete applications span several strategic sectors.

• Industrial chemistry, with the calculation of binding energies and the modelling of catalytic sites.
• Pharmaceuticals, with the study of binding affinity for the development of new drugs.
• Materials science, with the analysis of electronic properties to optimise batteries and new components.

The overall workflow – from the definition of the Hamiltonian to the design of the VQE (Variational Quantum Eigensolver) circuit – is explored in depth on the page dedicated to quantum simulation, while the clinical impact is covered in the section on quantum computing in healthcare. Although the scale of current devices is still small, the growth trajectory of this segment remains the most concrete and credible in the entire sector.

Why is security the most urgent application?

Because it is the only one in which the calendar is not decided by the hardware. A competitor or a malicious actor can archive encrypted data today and decrypt it when the machines mature. For any data with a long useful life, such as trade secrets, health data and intellectual property, the risk is therefore already active. The response is migration to post-quantum cryptography, with NIST standards already published and regulatory deadlines already set for critical infrastructure. It is the paradoxical application of quantum computing, the one that generates immediate work for those who will never use a quantum computer, but must defend themselves against those who will use one in the future.

Which sectors are most involved?

In order of documented investment intensity we find pharmaceuticals and chemistry, for molecular simulation; finance, for portfolio optimisation, pricing and risk management, as detailed on the page on quantum computing in finance; energy and materials, for batteries, grids and catalysts; logistics and manufacturing, for routing and scheduling; defence and aerospace, where the subject intertwines with technological sovereignty and the Golden Power perimeter; telecommunications and public administration, driven by the cryptographic transition. Healthcare, for the breadth of its use cases, deserves the dedicated treatment that you will find elsewhere on the site. In every sector the geography is the same, with a cross-cutting cryptographic obligation and a portfolio of computational opportunities to be filtered methodically. And the most publicised quantum computing applications are almost never the closest.

Which applications concern public administration?

Three in particular. The cryptographic transition of critical infrastructure, an obligation already scheduled in several jurisdictions and a priority for public healthcare, justice and defence. The optimisation of services, from public transport to network management to resource planning, where combinatorial problems abound. And industrial policy, that is, the choice to equip oneself with national capabilities, such as the Italian Quantum Emulation Centre (Centro Italiano di Emulazione Quantistica), so as not to depend entirely on foreign infrastructure in a domain classified among critical technologies. For the public sector, quantum computing is not a futuristic subject; it is already a multi-year planning item, with cryptography at the top. And public administration has a rare structural advantage, namely long planning horizons, which are exactly what this technology requires in order to be governed well rather than chased badly.

How do you evaluate a concrete use case?

The process comprises three sequential questions.

• Does the problem belong to one of the four quantum families and does it present a complexity that explodes as the scale grows? If the answer is no, the classical computational approach is more than sufficient.
• Does a quantified classical baseline exist? In other words, do we know exactly how much it costs today to solve the problem with the best traditional methods available? Without a clear baseline, any ‘quantum advantage’ remains merely an opinion.
• Does the economic value generated by surpassing that baseline justify the investment in an experimentation programme?

If the answer to all three questions is yes, the next step is not to purchase immediate access to quantum hardware, but to prototype in emulation. This guarantees controlled costs, reproducible results and an intellectually honest comparison with classical systems. This rigorous selection process is the filter that separates concrete projects from mere market suggestions. It is a logic that applies identically to the large multinational and to the medium-sized enterprise; what changes is the scale of the problems, not the method of evaluating quantum computing.

What role does emulation play in applications?

The role of the universal development bench. Every application described on this page, from the QUBO formulation to the molecular simulation circuit, is built and validated today in an emulation environment. It is there that algorithms are written, resources are measured, baselines are compared and teams are trained, without waiting for mature hardware or paying for access to it. The emulation platform is designed precisely for this cycle, from idea to proof of concept, with the additional advantage of total inspectability. One sees why an approach works or fails, not just that it works or fails. This is how quantum computing applications are prepared today.

Where to start in practice?

The starting point is the quantum readiness path, a structured approach that unfolds in a few clear stages.

• Process assessment, to identify the business problems that have the right mathematical structure.
• Cryptographic inventory, to map and quantify the company's security exposure to future quantum risks.
• Essential team training, to align internal skills.
• Proof of Concept (PoC) in emulation, to be developed on a circumscribed use case with a clear baseline for comparison.

This path takes a few months and a modest initial investment, guaranteeing a valuable result in every scenario. The outcome, in fact, is twofold. One may discover a potential advantage to cultivate, or one may show, with data in hand, that for the time being the prerequisites for proceeding are not there. This second conclusion is worth as much as the first, because it protects the company from investments driven only by market hype. It is the difference between following the evolution of quantum computing through press releases and possessing a verified map of one's own terrain. The map requires a slightly higher economic effort, but offers incomparably higher value. In both cases, the organisation comes away with a body of strategic skills that remain in the company permanently.