Quantum computing in logistics is moving from research papers to real industry conversation, and Quincus was part of that conversation this week at the Quantum Innovation Summit 2026 in Dubai, organized by Vernewell Group.
Katherina Lacey, Quincus's Co-Founder and Chief Product & Platform Officer, joined a panel of quantum computing specialists, hardware providers, and researchers to discuss where quantum technology is actually ready to help logistics and supply chain operations, and where the industry still has work to do.
The real question behind quantum readiness
One moment set the tone for the entire discussion. Simon Fried of Classiq, a quantum software company, asked the panel: if you'd known two years before ChatGPT what it would become, how would you have prepared?
Nobody had a confident answer, and that was the point. Most organizations don't prepare well for a transformative technology before its value is obvious. They wait for proof, then scramble to catch up once competitors have already moved.
The panel's conclusion applies directly to quantum computing in logistics today: the fix isn't waiting for proof. It's also not guessing at use cases in advance. It's knowing your hardest, highest-value problems well enough that you're ready the moment a new capability can solve them.
Why "start with the problem" matters for quantum computing
A recurring theme across the panel was a caution against chasing quantum computing for its own sake. The instinct with any emerging technology is to look for a problem that fits it, in order to justify the investment.
The panel pushed back on that instinct directly. A problem can be mathematically interesting and still deliver no value to a customer, and several early quantum computing pilots in logistics and other industries have stalled for exactly this reason: nobody checked which of the two tests the problem needed to pass.
The panel's recommended approach, instead:
- Identify the real business problem first: not a technically elegant one, but one with clear customer or operational value.
- Evaluate quantum computing against that problem, rather than searching for somewhere to apply it.
- Let the application and the hardware mature in parallel, instead of waiting for a "quantum advantage" milestone before starting.
AI, HPC, and quantum computing: a hybrid model, not a replacement
Perhaps the most important point for logistics leaders evaluating quantum computing: it isn't a replacement for AI or classical high-performance computing (HPC). It's a complement to both.
Each works best on a different kind of problem:
- AI: pattern recognition and prediction at scale.
- HPC (classical compute): problems it already solves efficiently and cheaply.
- Quantum computing: narrow, highly combinatorial problems such as network design, fleet and asset scheduling, and terminal and berth planning, where the number of possible solutions is too large for classical methods to search effectively.
This reframes the opportunity for supply chains specifically. A supply chain isn't one computational problem; it's thousands of smaller ones, each suited to a different tool. The near-term opportunity in quantum computing for logistics isn't replacing existing systems. It's building a hybrid model that applies the right technology to the right part of the problem.
What "progress" looks like in year one of a quantum program
For organizations starting to evaluate quantum computing, the panel offered a useful filter for measuring early progress:
A hardware milestone only matters when it changes the size or type of problem you can actually solve, not when it simply improves a technical benchmark that means little outside a research lab. Customers and business stakeholders care about outcomes, not qubit counts or error-correction rates.
Equally, learning where quantum computing is not yet the right fit is itself valuable progress, a point more than one panelist made directly, which isn't something organizations often hear from vendors selling the technology.
Looking ahead
Quincus thanks Quantinuum and Abu Dhabi Maritime Academy, the R&D arm of AD Ports Group, for the research partnership this discussion builds on, and Vernewell Group for convening the Quantum Innovation Summit. The event also highlighted a number of startups advancing this space, including Blue Titan, Artificial Brain, and Quantum Basel.
As quantum computing in logistics matures, Quincus remains focused on identifying where it can create measurable value for supply chain operations, guided by the same principle raised throughout the panel: start with the problem, not the technology.
Frequently asked questions
What is quantum computing's role in logistics today?
Quantum computing is still early-stage for logistics, but it shows particular promise for narrow, highly combinatorial problems like network design, fleet scheduling, and terminal planning, where the number of possible solutions is too large for classical computing to search efficiently.
Will quantum computing replace AI in supply chain operations?
No. Industry experts, including panelists at the Quantum Innovation Summit, describe a hybrid model where AI, high-performance computing, and quantum computing each handle the part of a problem they're best suited for, rather than one replacing the others.
How should a logistics company evaluate whether quantum computing applies to its business?
Start with your highest-value, hardest operational problems first, then assess whether quantum computing is the right tool for them, rather than searching for a use case to justify adopting the technology.
What does "progress" look like in an early-stage quantum computing program?
Progress means a milestone that changes the size or type of problem you can solve, or learning clearly where quantum computing is not yet the right fit, not simply hitting a technical hardware benchmark.