Event Round-Up: Quantum Readiness Series: An industry primer on quantum technologies

From academic origins to business readiness 
Once considered solely academic, the field has experienced a significant shift as hardware providers improve qubit quality and begin to reach performance levels that allow meaningful experimentation. With stronger hardware baselines and clearer lines of collaboration, enterprises can now test and shape applications that are grounded in business needs rather than speculative curiosity. 

Addressing the scaling challenge 
As quantum computers grow in size, the focus has shifted to managing and correcting the errors to which qubits are inherently prone. This represents an exciting inflection point: the technology is now robust enough that the conversation has moved from "if" to "how" these systems can be deployed. 

Near-term opportunities emerging 
Practical applications are emerging in optimisation and generative machine learning, where resilience to noise is higher and the path to early production is becoming more realistic. These are use cases that could reach production within the next year or two. 

From lab to production in sensing 
In quantum sensing, the shift has been particularly pronounced. Technologies are moving from university experiments to production devices that can be operated by non-specialists. This maturation reflects over a decade of research now yielding deployable solutions with clear industrial applications. 

Building foundational literacy 
It begins with building foundational literacy across relevant teams so that decision-makers understand where quantum might fit within their strategy. Organisations need to recognise that quantum encompasses multiple technology types – computing, sensing, communications, and PNT – each with different timelines and applications. 

Strategic alignment and use case identification 
Readiness includes mapping quantum's different application areas, aligning them to business roadmaps, and identifying the roles and skills that will be needed as adoption scales. The focus is on understanding which problems quantum technologies can solve rather than requiring staff to become quantum experts. 

Preparing for a hybrid future 
Organisations should be thinking about how quantum capabilities will integrate with existing infrastructure and compute power. The future of computing will be hybrid, combining classical compute, AI-based techniques, and quantum computing to solve problems that none of these approaches can tackle alone. The aim is to ensure that when the right use case appears, organisations can move with confidence and speed. 

Quantum sensing leading the way 
Sensing applications are moving from lab prototypes to deployable products, offering faster, safer, and more cost-effective insights across sectors such as infrastructure, energy, and healthcare. The technology has matured to the point where success will be measured not by mentioning "quantum" but by seamlessly solving problems. 

Diverse applications across quantum technologies 
Quantum random number generation is strengthening cryptographic systems and improving simulation capabilities. Quantum communications is advancing both security and network synchronisation. These tangible impacts demonstrate the breadth of quantum technologies beyond computing alone. 

Real-world examples in quantum sensing 

Several examples illustrated how quantum sensing is transforming measurement and diagnostics: 

• Subsurface mapping: Quantum gravimeters enable high-resolution subsurface mapping without excavation, producing real-time insights that reduce disruption and cost. This technology can identify features underground such as voids, utilities, or geological structures. These applications are valuable in oil and gas, mining, civil engineering, and utilities. The same sensors can also enable GPS-free navigation. 
• Non-destructive testing: Quantum sensors can detect subsurface cracks in metals without damaging components, improving safety and efficiency in materials testing. 
• Healthcare applications: Wearable brain scanners that support patients who cannot tolerate traditional scanning environments. Diamond-based sensors are being developed for precise analysis of blood components and other biomarkers, offering non-invasive technology to measure small changes in the body with high accuracy. 

Hardware development 
Current qubit-based quantum computers can perform roughly 1,000 operations before errors overwhelm the system. To unlock the transformative applications commonly associated with quantum computing, this needs to scale to approximately one trillion operations which is a target expected around 2035. This represents an extraordinary engineering challenge but one with a clear roadmap. 

Software accessibility 
Software needs to meet users where they are, with interfaces and libraries that allow developers to invoke quantum acceleration with minimal code changes. The goal is to create tools where existing experts can experiment by swapping out a single line of code to access quantum capabilities, rather than requiring wholesale retraining. 

Evolving user interfaces 
The interfaces for interacting with quantum computers are changing. Increasingly, users will submit problems to compute environments where intelligent compilers determine which parts of the stack – classical, quantum, or hybrid – should handle different aspects of the workload. The end goal is for quantum to become a tool in the toolkit that the end user might not even know is doing the work. 

Raising quantum literacy 
The people challenge is nearly as significant as the technological one. Organisations need to raise quantum literacy so end-users can adopt these tools without deep specialist training, much as they have with AI. This includes providing use case-specific interfaces that do not require heavy educational investment. 

Diverse pathways for engagement 
Public programmes, testbeds, accelerators, and cloud access points are designed to de-risk early engagement and broaden participation beyond a small number of major players. Different organisations across the ecosystem are working to introduce companies to quantum technologies, with substantial information available from UKRI to bring quantum technologies to broader applications. Digital Catapult’s Quantum Technology Access Programme (QTAP) is an example of a programme that helps organisations understand how quantum technologies can address their specific challenges. 

Accessible infrastructure and cloud integration 
Quantum capabilities are increasingly being integrated into mainstream compute environments to avoid concentration of benefits. Some cloud providers already offer access to quantum computing resources. The National Quantum Computing Centre (NQCC) testbed is exploring how different modalities can work together to solve problems within hybrid structures, aiming to make quantum as accessible as today's supercomputers. 

Sector-specific focus 
Finance, health, and defence are emerging as early adopters due to strong use cases, but the aim is to ensure benefits extend across society. The quantum missions are specifically designed to provide funding that helps organisations de-risk applications and work with or develop quantum solutions according to their needs. Significant untapped potential remains in sectors yet to engage, underscoring the need for inclusive outreach and collaborative development. 

Deployment Challenges and Technology Maturity 

Moving from lab to market 
The central challenge is transforming devices from laboratory experiments into tools that are robust, repeatable, and operable by non-specialists in real environments. Historically, operating quantum sensors required a quantum physicist. The breakthrough is making these technologies simple enough that anyone wearing high-visibility clothing can use them safely on site. 

Error correction and modality maturity 
A question explored whether particular computing modalities are more reliant on error correction than others. The panel noted that whilst there was an initial expectation that one modality would dominate, all major approaches seem to be following similar trajectories. Most qubit-based systems have crossed the threshold of 99.9% fidelity at which quantum error correction becomes necessary. Certain quantum computers may prove better suited to specific problems, and as the technology scales further, some modalities may fall away, but currently the playing field remains wide open. 

Photonics and near-term advantages 
Photonic quantum computers have a special architecture that, in the short term, doesn't suffer from the same type of noise as other quantum systems. They are affected by photon loss rather than decoherence, meaning certain algorithms that would collapse in qubit-based systems may not face the same issues in photonics-based systems. This creates opportunities for near-term advantages in optimisation and generative machine learning without requiring full error correction. 

Energy considerations 
The energy conversation added nuance to the deployment picture. When workloads are well-matched, hybrid orchestration can reduce overall energy consumption by applying quantum resources where they are most efficient and classical compute where it excels. In specific scenarios, today's quantum racks may consume less power than equivalently sized GPU installations for targeted tasks, though fully error-corrected systems will introduce additional overhead. The trajectory is towards smarter, workload-aware allocation of compute that drives efficiency through integration rather than relying on any single device characteristic. 

Adoption, Readiness, and Business Decision-Making 

When to consider quantum computing 
One question sought a simple guideline for how much day-to-day compute an organisation uses that would justify a move to quantum computing. The panel advised against rigid thresholds, suggesting that adoption should be anchored in the nature of the problem and the business bottleneck, whether the constraint is solution quality, speed, or the scale of instances that can be addressed. 

Different types of compute problems exist, and not all are suitable for quantum computing. Some will always be better suited to CPUs or GPUs. Where classical methods are fundamentally limited, or where small improvements would generate outsized value, organisations should explore quantum approaches through targeted proofs of concept with technology partners and government agencies. As a specific example, if there is no mechanism to solve a problem through classical computing, quantum is definitely worth considering. 

Post-quantum cryptography and harvest-now-decrypt-later risks 
A question addressed cryptography in a harvest-now-decrypt-later context and when organisations should move to post-quantum cryptography (PQC). The guidance was to prioritise long-lived sensitive data such as medical records, legal contracts, and certain financial information, because confidentiality requirements stretch across decades. 

Whilst precise timelines for cryptographically relevant quantum computers remain uncertain, NIST has already released standards. The key learning is that organisations have historically been slow to adopt new cryptographic standards, so building cryptographic agility now is essential to mitigate future risk.  

Skills and workforce development 
Readiness does not require hiring exclusively from quantum physics backgrounds. Many needs can be met by professionals with transferable STEM expertise in areas such as data science, software engineering, systems integration, and product management, augmented with targeted training. The UK offers numerous programmes and resources, including the NQCC's SparQ programme, the Hartree Centre's retraining programme, and public engagement resources from the QCi3 Hub.  

Quantum companies themselves have many PhDs but often lack knowledge of how to bring technology to market, meaning there is strong demand for standard business skills. Interest in STEM disciplines provides the foundation, and companies are willing to invest in upskilling. This creates opportunities for professionals outside the industry to bring their expertise and apply it in quantum contexts. 

Standards, Infrastructure, and the Future of Telecoms 

Standards and regulatory frameworks 
Questions on standards underscored the importance of aligning quantum with existing data centre and software practices. Efforts are underway through initiatives like the Open Compute Forum to ensure that hosting, management, and integration are coherent, with common interfaces and APIs that allow vendors to plug into established workflows. 

From a sensing perspective, building confidence will depend on demonstrated performance within current regulatory frameworks. In some cases, certain sensing technologies may be mandated by existing regulations, and the focus is on showing that quantum technologies can significantly improve these processes. Timing, for example, is already done with quantum clocks, which are setting the standards for how timing is measured and communicated. 

Applications in telecommunications beyond QKD and PQC 
Beyond quantum key distribution (QKD) and post-quantum cryptography, quantum technologies can enhance telecoms through several mechanisms: 

• Timing and synchronisation: Quantum-enabled timing can make network communications and synchronisation more efficient, though this remains in early stages. 
• Network optimisation: Quantum computing could help solve complex planning problems, such as determining where to build fibre networks to maximise bandwidth and service quality whilst minimising the amount of road that needs to be excavated and overall cost. 
• Signal processing: Current limitations on bandwidth from each frequency band exist partly because it is economically unviable to run enough classical compute to perform the error correction algorithms needed to use bandwidth most efficiently. Proposals exist to use quantum computing for this purpose, potentially unlocking ten or even a hundred times the amount of bandwidth from existing radio spectrum.