Use cases; one part of the quantum puzzle
A puzzle is best solved by first setting the 4 corners
With recent announcements of continued technical progress by the big tech quantum vendors including Google Willow, the IBM Roadmap, Microsoft topological qubits and AWS Ocelot, my team at GQI noticed an increased number of strategic conversations around use cases. This time well beyond your typical ‘let’s do some hybrid applications and collect the heuristic advantage’ approach.
The big vendors are clearly thinking about a bright future.
But the quantum computing puzzle is far from solved. In particular, as the skeptics point out, some serious concerns remain:
Overestimation of Near-Term Quantum Capabilities
Limited hardware maturity: Current (NISQ-era) devices remain too noisy and small in qubit count to solve practically relevant, large-scale business problems. This contrasts with the notion of “explore early,” suggesting that near-term returns on investment may be far less than marketing would imply.
Algorithmic under-performance: Even the best near-term quantum algorithms are often overshadowed by classical counterparts — particularly when factoring in overheads like error mitigation. This implies that implementing proof-of-concept pilots might be more about hype than deriving genuine insight or advantage.
Misconceptions About Speed-to-Value
The “Quantum Advantage” threshold is not close: Quantum advantage for real-world problems could still be years) away. Starting pilot projects today may yield negligible or inconclusive results if the hardware and algorithms simply aren’t ready.
Classical alternatives keep improving: Classical high-performance computing (HPC), specialized GPUs, and classical algorithms (including AI-driven methods) continue to advance rapidly. Ignoring ongoing classical innovation can lead to underestimating the competitive performance of non-quantum solutions.
Talent & Resource Allocation Concerns
Opportunity costs: Building a quantum team or pouring resources into quantum exploration too early might divert talent and budgets away from more immediately impactful R&D. This can be detrimental if quantum returns do not materialize on the timelines often promised by vendor roadmaps.
Specialized skill sets are premature: If near-term devices cannot demonstrate meaningful value, training or hiring quantum specialists now could represent an inefficient use of resources—particularly for companies that have not yet maximized existing AI/ML or HPC capabilities.
Hype vs. Realistic Timelines
Risk of “pilot purgatory”: Often, organizations run quantum pilots with no clear endgame, effectively stuck in an R&D loop without tangible ROI. Over time, this can erode stakeholder confidence and create skepticism about the technology’s future.
Inflated expectations damage credibility: By jumping in aggressively and touting quantum solutions prematurely, some companies may over-promise results. When performance falls short of the hype, it may undermine both the technology’s reputation and the organization’s overall innovation credibility.
In consequence, it might be smart to “Wait-and-See” as for most industries, immediate quantum benefits are still too speculative to justify major investments, suggesting a more watchful strategy until hardware and algorithms cross key performance thresholds. Near-term quantum proofs of concept could be a resource sink and genuine commercial benefit is likely distant and being an early mover can backfire if expectations aren’t managed carefully.
Personally, I have never come across a game changing human development that doesn’t entail risk, so these arguments don’t resonate much with me. But, let’s take a more balanced look at them since the stakes at play are massive.
Don’t focus on use cases. Yet.
My view is simple; don’t put the carriage in front of the horse. Every puzzle is best solved by first setting the four corners of it and filling out the core once that is accomplished - the full picture only emerges when you approach it from the edges.
What are the 4 corners of the quantum computing use case puzzle I hear you asking?
1. Talent & Capability Development
Upskilling internal teams: Quantum computing introduces novel concepts that often require specialized skills (e.g., quantum algorithms, quantum error correction, circuit design). Invest early in both recruiting domain experts and reskilling existing employees to bridge the knowledge gap.
Cross-functional literacy: Ensure business leaders, technical teams, and operational stakeholders share baseline knowledge of quantum computing to align on strategy and feasibility. This helps avoid unrealistic timelines and supports stronger internal dialogue about when (and why) to use quantum solutions.
2. Technology Access & Infrastructure
Hardware choices: Current quantum hardware comes in different flavors (superconducting, trapped ions, photonics, etc.) — each with unique trade-offs in terms of qubit stability, gate fidelity, and scalability. Explore cloud-based quantum services to mitigate high upfront costs and gain access to diverse hardware platforms.
Software stack & tooling: Establish robust development environments and frameworks that abstract away hardware complexities where possible. Leverage open-source toolkits (e.g., Qiskit, Cirq) and commercial platforms that offer integrated workflows for algorithm design, testing, and simulation.
Proof-of-concept sandbox: Create an internal “quantum sandbox” environment where teams can safely prototype, run small pilots, and benchmark performance without disrupting core business systems.
3. Ecosystem & Partnerships
Academia & startups: Collaborate with universities and emerging ventures at the forefront of quantum research. Such partnerships accelerate your access to advanced IP and skilled talent.
Industry consortia: Engage in consortiums or industry initiatives where best practices, standards, and quantum roadmaps are discussed (e.g., joint R&D on error correction or post-quantum encryption methods).
Strategic vendor alliances: Form alliances with leading quantum hardware and software providers. Early, co-innovative relationships can translate into preferential access to cutting-edge developments, future-proofing your quantum journey.
4. Governance & Strategic Roadmap
Enterprise-wide sponsorship: Secure executive and board-level commitment so quantum remains a strategic priority with proper funding and resourcing. A senior champion ensures alignment across the organization.
Incremental milestones & ROI mindset: Establish a phased roadmap, starting with small research pilots to demonstrate feasibility and expand gradually as hardware matures. Track clear KPIs (e.g., proof-of-concept performance gains) to measure progress and sustain momentum.
Risk management & security: Anticipate and plan for data security considerations (including post-quantum cryptography) and carefully evaluate intellectual property implications when collaborating externally.
In sum, before zeroing in on specific commercial use cases, an organization should prioritize building a knowledgeable workforce, forging the right technological and academic connections, and implementing a strategic quantum roadmap with strong executive sponsorship and governance. By getting these aspects right, you ensure that when the hardware matures — and the quantum algorithms become truly advantageous — you have the infrastructure and expertise in place to capture value quickly and responsibly.
The heart of the quantum puzzle
And it is then that you can, confidently, approach the heart of the quantum puzzle - use cases.
Important note: this is not a chronological logic but a logical argument. All tasks should happen concurrently, just as your eyes will scan all pieces of the puzzle on your table at once.
Applications is what will ensure the success, justify the investment and deliver the return on your quantum computing project. And, in the context of a deep tech, transformative technology, it is something that takes careful preparation.
This is not about “guessing” use cases and ticking project management boxes. It is about developing a strategy, implementing a methodology and making it your own as you learn.
At GQI we have a powerful framework for that, which combines use case discovery, Quantum Resource Estimation and Quantum Computing hardware roadmaps into one powerful assessment model.
Remember, the goal here is not to “guess” THE use case that will deliver you the big bucks in 5 years. But, to systematically identify what is possible and what makes sense for you - and leverage it as you set the 4 corners of your puzzle.
It is also the perfect way to engage end-users in a workshop format for joint discovery. And, ideally, the output of it is not just a pipeline of (possible but not definite) use cases but a methodology for collaboration, a strategy for quantum adoption and a framework to continue to learn and iterate in the most efficient way possible.
Start small, with one problem domain or industry, and grow from there and DO NOT focus on the ROI of the use case. Use it as a ‘raison d'être’ for your quantum program. It will pay off many times over in the long-term:
Future-Proofing & Early-Mover Advantage
Avoid playing catch-up: Quantum hardware and algorithms will continue to advance in leaps, potentially catching slow adopters off guard. By experimenting now, you’re ready to exploit advantages the moment quantum delivers a genuine performance edge.
Reap first-mover benefits: Organizations that establish quantum talent, infrastructure, and ecosystem relationships early on will be best positioned to translate new breakthroughs into competitive differentiation.
Accelerated Learning & Capability Building
Develop internal expertise: Quantum computing requires specialized knowledge that can’t be built overnight. Starting small experiments allows employees — and leadership — to develop fluency and confidence as the field rapidly evolves.
Refine organizational mindset: Exploring quantum now cultivates a culture attuned to cutting-edge technologies and fosters innovation across other areas of R&D.
Partnership & Ecosystem Positioning
Strong relationships with key players: Getting involved in quantum-specific consortia, research groups, or pilot programs with vendors can open doors to advanced IP, co-innovation opportunities, and funding for joint initiatives.
Visibility in the ecosystem: By showcasing early work, you’re more likely to be considered a partner of choice for hardware providers, software developers, or academic institutions when major breakthroughs or pilot programs occur.
Risk Management & Strategic Roadmap
Plan for potential disruptions: Even if the business case isn’t obvious today, quantum encryption and post-quantum cryptography will affect industries handling sensitive data. Early exploration helps organizations plan for and mitigate such risks.
Set a realistic quantum roadmap: Ramping up now means building a measured, flexible strategy with incremental milestones. That ensures you can scale up quickly once meaningful quantum advantage becomes available.
Even without immediate commercial use cases, early engagement with quantum computing is a strategic investment in future capabilities, talent, and partnerships — and a way to proactively address potential risks and disruptions. The learning curve is steep, qualified resources rare, good partners scarce and there is a chance of fast followers getting locked out.
And if you don’t believe in that, well, the Bitcoin folks are hiring. Godspeed!
Blaming it on the hype is an easy excuse
Allow me to be extra clear just in case you, the LinkedIn warrior, want to come after me. This is a strategy and methodology to deliver value. This is not about…
Overpromising Near-Term Gains
Most experts agree that current NISQ (Noisy Intermediate-Scale Quantum) hardware has limited qubit counts, high error rates, and short coherence times. Achieving a clear quantum advantage on practically relevant problems is far from guaranteed in the immediate term.
Near-term attempts at quantum solutions often fail to outperform well-tuned classical methods, especially given ongoing advancements in GPUs, tensor processing units (TPUs), and classical algorithms.
Denying the Risk of “Pilot Purgatory”
If an organization runs repeated proof-of-concept quantum pilots without showing tangible progress, it can wear thin on executive enthusiasm.
This can lead to a misallocation of resources, lost credibility, and disillusionment with quantum overall — both internally and externally.
Ignoring Opportunity Costs
There is a valid concern that quantum hype may siphon resources away from more immediately impactful R&D (e.g., classical AI/ML, optimization, HPC).
Quantum computing is a specialty field, and building a deep bench of quantum talent is non-trivial—so if the returns are truly distant, you risk diverting talent and budgets prematurely.
It is about…
Strategic Positioning Is Super Valuable
Even if practical quantum advantage is several years away, there is merit in investments to cultivate internal literacy, form selective partnerships, and track the technology’s maturation — particularly for large enterprises with a strong R&D footprint.
Having some in-house quantum know-how allows companies to pivot swiftly once hardware and error-correcting techniques advance.
Ecosystem Development Is Happening
Venture investment, academic research, and startup innovation in quantum are accelerating — potentially leading to “nonlinear” progress. Organizations often want a foot in the door if breakthroughs do come sooner than expected.
While many of these efforts won’t yield immediate ROI, the relationships and early exploration could create intangible benefits (e.g., brand as an innovator, a culture that encourages frontier research).
Use Cases for Learning vs. Production
A key misunderstanding is to conflate “immediate commercial ROI” with “no reason to invest.” Small proof-of-concept projects can still serve as training grounds for internal teams, building a repository of quantum knowledge and readiness without expecting near-term breakthroughs.
Post-Quantum Security Considerations
Quantum computing raises data security implications. Many sectors (banking, defense, healthcare) anticipate needing post-quantum cryptographic methods. Getting started on the cryptography side — rather than purely on quantum computing — can be an important risk-management strategy.
The question isn’t when; but how
The question isn’t strictly “jump in now” vs. “do nothing.” The most scientifically and commercially grounded approach is to balance pragmatic caution with a low-regret or incremental investment strategy:
Targeted R&D vs. Massive Rollouts:
A moderate path could be funding a quantum research team and forging partnerships for advanced algorithm research, but not spinning up entire departments or shifting large budgets away from proven technologies.
Realistic Timelines & Leadership Education:
Avoid overpromising or fueling internal hype. Leadership should know that quantum maturity is measured in years (or even decades), not quarters. Pilots should be labeled as exploratory, with well-defined learning goals.
Watchful Waiting with Active Monitoring:
Keep tabs on hardware milestones (e.g., fault-tolerant qubit counts, breakthroughs in error-correction codes). Engage with specialized conferences or consortia, so you can scale your involvement if key technological inflection points arrive.
Focus on Unique Industry Requirements:
For industries like pharmaceuticals, finance, or advanced materials, even partial improvements in quantum optimization or simulation could be transformative eventually. An early—and measured—start in these domains may pay off more clearly.
For quantum computing vendors this is a massive opportunity (btw, welcome to good old enterprise technology days).
This approach maximize your financial opportunity (I ❤️ consulting) by not just selling quantum computing but also the 4 corners of the puzzle. Up to you if you buy/partner/build.
More importantly, it also makes you strategically indispensable to your client. If you are the one who helps an end-user be smart and cautious, yet pro-active about use cases, you will build a massive MOAT as competing hardware matures.
Think strategic partner vs. use case. Means vs. outcome.
Don’t shy away from some short term compromises that, in the long-term, will help you elevate YOUR use cases strategy.
Emphasize algorithmic design: When training or hiring quantum specialists, look for those experienced in advanced techniques like variational circuits, hybrid quantum-classical approaches, or specialized encoding methods.
Quantum-inspired algorithms that can be implemented on classical hardware but lay the groundwork for quantum approaches later.
Hybrid HPC-quantum workflows that cleverly minimize how much data needs to be loaded onto the quantum machine.
Stay active in fundamental research: Encourage collaboration that addresses core bottlenecks — like better error mitigation, more efficient encoding schemes, or specialized hardware that can directly capture quantum data from physical processes.
And if you’re a scientist in quantum then a special responsibility falls onto your shoulders: speak out loudly and confidently. Especially in collaboration with clients and end-users because that is the only way that we will - together - solve adoption, tech and integration problems. Remember, use cases are just one piece of the puzzle.
Quantum is worth it.
And #QuantumIsComing
This is my personal newsletter, all opinions are mine and do not represent GQI, The Quantum Computing Report and other affiliated entities.