In the race to make quantum computing commercially viable, attention often centers on physics and how to preserve coherence, reduce error rates, and scale up qubits. But in the shadows of these scientific triumphs lies a harder question: can it be built affordably and used profitably? Erik Hosler, a systems-focused quantum engineer who bridges research and real-world deployment, recognizes that the breakthrough moment for quantum computing won’t just arrive when it solves a hard problem but when it can do so without costing more than the answer is worth.
It is not a challenge that quantum computing can sidestep. It sits at the very heart of what makes any technology viable. As impressive as it is to build machines that exploit entanglement and superposition, success hinges on balancing performance with economic sustainability. The cost to build and operate a quantum system must be matched or, better yet, outweighed by the value of the problems it can solve. Without meeting this threshold, even the most advanced quantum hardware risks becoming a scientific novelty.
The Economic Bar for Disruptive Technologies
Throughout the history of computing, new paradigms had only taken hold when they crossed a simple but unforgiving line. They had to do something important, better or cheaper than existing methods. Classical computers didn’t just beat pen and paper. They outperformed human computation at a cost that made them indispensable.
Quantum computing is now approaching a similar threshold. For it to move from promise to practice, it must deliver computational outputs that have clear, actionable economic value, whether that’s accelerating pharmaceutical development, optimizing logistics, or securing communications. And it must do so at a cost that justifies the investment.
It doesn’t mean quantum systems must be inexpensive at first, but the value they generate must be compelling enough to fund their continued development.
Understanding the Full Cost of Quantum Systems
Quantum computers are complex machines with layers of interdependent components, each contributing to the cost:
- Cryogenic cooling systems to maintain qubit stability
- Precision electronics to deliver control pulses and timing
- Custom packaging to protect fragile quantum circuits
- Software stacks and error correction to enable meaningful computation
And that’s just the beginning. Every additional qubit adds complexity, not just in hardware but in calibration, operation, and long-term reliability. As quantum processors scale into the hundreds of thousands or even millions of physical qubits, these costs compound.
Erik Hosler emphasizes, “The value of the computations it performs exceeds the cost to build and operate the computer.” It isn’t just a budgetary concern. It’s a business imperative. A machine that solves million-dollar problems at a billion-dollar cost doesn’t mark progress. It marks a shortfall in design priorities.
Hardware Without ROI Is Just an Experiment
There’s no shortage of clever engineering in today’s quantum systems. Researchers have coaxed coherence from superconducting loops, trapped ions, photons, and even topological states. The question is no longer whether qubits can be built. It’s whether they can be built in sufficient numbers and at a cost that scales favorably with performance.
That is where economic thresholds become make-or-break. Just as early mainframes gave way to minicomputers and then microprocessors because they aligned better with business needs, quantum computers will only move beyond research labs if they offer a return on investment. That return might be scientific, operational, or financial, but it must be tangible.
Otherwise, even the most elegant hardware remains out of reach for all but a handful of well-funded institutions.
Aligning With Existing Manufacturing Ecosystems
One of the most promising strategies for managing economic thresholds is leveraging the existing semiconductor manufacturing infrastructure. Rather than building everything from scratch, some companies, like PsiQuantum, are designing quantum systems that are compatible with CMOS fabrication tools. This approach offers clear benefits:
- High precision from existing lithography and metrology tools
- Lower marginal costs thanks to industrial-scale production
- Easier integration into broader electronics ecosystems
More importantly, it helps control costs early before they spiral into custom-built complexity. If quantum chips can be fabricated on tools already used to produce smartphones and data center CPUs, the path to commercial viability becomes far more plausible.
Applications Must Justify the Hardware
Even if hardware is produced cost-effectively, the burden shifts to applications. Quantum computing’s most often cited “killer apps” include:
- Molecular simulation for drug discovery
- Materials optimization for better batteries and catalysts
- Cryptography through Shor’s algorithm
- Large-scale optimization in logistics and finance
For each of these, the value must be clearly quantified. For instance, if simulating a molecule enables a $100 million drug discovery shortcut, and the quantum computer used to simulate it costs $50 million, the case is made. If the same computer solves a minor optimization that saves $10,000, it’s harder to justify.
That is why quantum computing must remain laser-focused on high-value use cases, the kind of problems that classical computers cannot solve in any reasonable time, but which quantum systems could tackle with real-world impact.
Market Readiness and Timing
There is also a matter of timing. The economics of quantum computing will follow a curve familiar to other industries: early adopters pay a premium for groundbreaking capability, while later adopters benefit from cost reductions due to learning curves, tooling efficiency, and volume scaling.
Companies that position themselves well during the early phase, focusing on manufacturability, modularity, and high-value targets, are more likely to survive the transition to mainstream adoption. Those who burn cash chasing theoretical power without addressing deployment cost may find themselves with impressive machines but no practical path to return.
A Measured Equation for Quantum Success
Quantum computing has never lacked imagination. What it now needs is discipline, a measured approach to building systems that balance raw potential with economic rationality. The most successful quantum platforms of the future will not be those that push the most qubits or the deepest circuits, but those that do so at a cost aligned with the value of their output.
The true breakthrough won’t be when a quantum computer does something no classical computer can. It will be when it does something no classical computer can and does it at a price someone is willing to pay. That’s the real threshold. That’s where theory becomes technology.
