One of the consistent surprises of 2026 is how many companies have a quantum strategy in their slide deck and zero practical experience running anything on a real QPU. The barrier is not capability — it is unfamiliarity. The cloud providers have made quantum hardware genuinely accessible. You can be running a real quantum circuit on a real machine, getting real results, this afternoon. This topic walks through how.
This material is also the bridge to the bigger commitment we are making with Ireland Quantum — Ireland's first sovereign quantum compute facility, delivered by Q2 2027. Most teams should not wait for that to start learning the workflow. Start now on existing infrastructure; migrate workloads to sovereign Irish hardware when it comes online.
Where you can run today
Four providers cover the great majority of practical quantum access in 2026:
IBM Quantum
The most mature platform for educational and research workloads. Free tier with usable systems for getting started. Paid plans give you serious queue priority and access to the larger superconducting systems. Their Qiskit SDK is the de facto standard for circuit construction; if your team is going to learn one quantum programming framework, Qiskit is the safe bet.
AWS Braket
Multi-vendor managed access — superconducting hardware from Rigetti, ion-trap from IonQ, neutral-atom from QuEra — through a single AWS console and a single SDK. Best choice if you want to compare hardware modalities for the same workload without learning four different stacks. Pay-per-shot pricing.
Azure Quantum
Similar multi-vendor model with a focus on integration into the broader Azure ecosystem. Strong on the algorithmic side — Q# is interesting if your team has a .NET background, less interesting otherwise.
Direct from IonQ and Quantinuum
Both providers will sell you direct access if your usage is non-trivial. IonQ's ion-trap hardware has the highest two-qubit gate fidelities in commercial production, which matters for any algorithm where error compounds. Quantinuum's H-series machines are the lead candidates for early fault-tolerant work with their integrated error-correction roadmap.
Workloads that are commercially real today
Resist the temptation to put a workload on a QPU because it sounds futuristic. The workloads where there is actual commercial value, today, are narrow and worth knowing:
- Quantum chemistry simulation. The first commercial application of quantum computing that has crossed the line from “research showcase” to “some pharma teams use it weekly.” Not for full drug discovery yet, but for specific subroutines — ground-state energy of small molecules, reaction-pathway exploration — quantum methods are competitive with the best classical methods on some classes of molecule.
- Materials science. Same story as chemistry, applied to battery materials, photovoltaics, and catalysts. Useful for narrow questions; not useful for full materials discovery loops.
- Sampling and Monte Carlo subroutines. Particularly in finance (option pricing, risk simulation) where quantum-accelerated sampling can give measurable speed-ups on specific shapes of problem.
- Optimisation. Mostly hype, narrowly real. Quantum approximate optimisation algorithms can beat classical heuristics on some structured problems; on general combinatorial optimisation they don't, yet. Be skeptical of vendor claims here.
- Cryptanalysis & PQ readiness. Most importantly for security teams: running real quantum circuits against simplified versions of your cryptographic protocols, to understand what fully fault-tolerant attacks would look like. This is education work, not a real attack, but the work pays back when NIST's PQ migration deadlines bite.
What to start with on Monday morning
If your team has not run anything on a QPU yet, the first three weeks should look like this:
- Week one. Set up an IBM Quantum account, install Qiskit, run a Bell-state preparation, run a small variational quantum eigensolver on H2. By Friday everyone in the team has put a circuit on real superconducting hardware.
- Week two. Pick the one commercial use case that matches your industry — chemistry if you're pharma, sampling if you're finance, optimisation if you're logistics — and reproduce a published benchmark. The literature is now thick enough that you can find a paper for almost any sector. The point is to feel the workflow, not to invent.
- Week three. Compare hardware modalities through Braket or Azure. Run the same circuit on superconducting and on ion-trap. Note where each one wins. This is the bit that gives your team an opinion, which is what you actually need before making a vendor decision later.
Three weeks of light effort and your team has gone from zero quantum to confident-enough-to-make-decisions. That is the real ROI of starting now.
Where Ireland Quantum changes the equation
By the time the Ireland Quantum facility comes online in Q2 2027, your team's quantum work should already be running on existing infrastructure. The migration path is straightforward — most quantum workloads are written against vendor-agnostic SDKs (Qiskit, Cirq, OpenQASM) and move between hardware backends without code changes.
What changes when sovereign Irish hardware is available is jurisdiction, data residency, and economics. You will be able to run your most sensitive workloads — pharmaceutical IP, post-quantum cryptography testing, government-adjacent simulation work — on Irish hardware in Irish jurisdiction at predictable per-shot pricing in euro under Irish contract law. For some workloads, that combination is the difference between “we run this” and “we don't.”
What we'll do in the workshop
Day 2 afternoon of the Clonmel workshop puts everyone in the room on a real QPU. Bring a laptop. Leave with a working IBM Quantum account, a Qiskit script you wrote yourself running on real superconducting hardware, and a clear sense of which of the five workload classes above are relevant to your industry.