What quantum technology can learn from AIs development

Date:
Tue, 31 Mar 2026 10:20:36 +0000

Description:
Unlike AI, quantum must embed standards from the start to create an
investable market.

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now subscribed Your newsletter sign-up was successful Join the club Get full access to premium articles, exclusive features and a growing list of member rewards. Explore An account already exists for this email address, please log in. Subscribe to our newsletter Quantum has reached an inflection point. Across computing, sensing, communications and navigation, the science is progressing quickly and the commercial pull is growing just as fast.

But if we want quantum technologies to move beyond pilots and prototypes into reliable, scalable products, we need to pay attention to something that
rarely makes headlines: standards. That lesson is hiding in plain sight in
the story of artificial intelligence and AI tools . Article continues below You may like Forget the AI Armageddonquantum computing is the real threat to digital security How network modernization enables AI success and quantum readiness What the post-quantum shift means for your security strategy Tim Prior Social Links Navigation

Quantum Programme Manager, National Physical Laboratory (NPL). AIs uptake has been extraordinarily rapid, but it also demonstrates the pressures that
emerge when powerful technologies are adopted faster than the frameworks needed to compare them, integrate them safely and build long-term trust.

Quantum can, and should, take a different path, embedding measurement and standardization early so innovation can scale with confidence.
Standardization isnt a brake on innovation. Its how you scale it. For many businesses, standards can sound like bureaucracy: extra time, extra cost, and a risk of locking-in todays best guess before the science is settled. Historically, that perception has encouraged companies to treat standardization as something that happens later, once products are mature and markets are established. But quantum flips that logic on its head.

In quantum, the barriers to adoption often arent about whether the technology is transformative. Theyre about whether it can be evaluated fairly, compared objectively, and integrated reliably into complex systems and supply chains. Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors By submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over.

Without shared terminology, agreed performance metrics and trusted test methods, it becomes really hard to attract investment and create a supply chain as neither customers nor investors can easily answer the practical questions that matter.

When we talk about standards in this context, were not talking about slowing progress. Were talking about building the foundations of progress: best practice, interoperability, methods of comparison, and shared terminologya common language that enables innovators to prove what they have built, and buyers to trust what they are adopting. Learning from graphene: hype isnt enough without measurement infrastructure A useful parallel is the story of graphene and other 2D materials. Graphenes remarkable properties sparked intense excitement, rapid investment and big expectations. What to read next We built a technology which uses light to control light: Finchetto CEO on ditching electronics to make networks faster Before you roll out more AI, answer this: Who's accountable? 'The future lies in quantum-centric supercomputing': IBM reveals its next big plan for developing next-gen
quantum computing, but are we any closer to real-world launches?

Yet commercial uptake was slower and more uneven than many predicted, partly because the measurement and comparison infrastructure wasnt mature enough to let the market distinguish consistently between materials, performance claims and real-world outcomes. In the UK, this gap became prominent enough to trigger serious scrutiny into why the supporting measurement infrastructure wasnt in place to capitalize on the opportunity.

The takeaway isnt that graphene failed. Its that breakthrough science doesnt automatically translate into commercial certainty. Without agreed definitions and consistent ways to measure and validate performance, markets struggle to reward the best solutions, and supply chains struggle to form around them. Standardization helps solve that by creating the basis for comparability, repeatability and trust. The AI lesson: adoption can outpace frameworks, then everyone pays the price AI shows the other side of the story. It has scaled
at astonishing speed and delivered real value across sectors. But it has also highlighted what happens when capability outpaces common frameworks and guardrails.

Organizations have faced challenges around consistent evaluation, governance, and the absence of widely accepted protocols for things like comparing performance and making robust decisions about deployment.

Quantum has the advantage of foresight: we can see the challenges that appear when everyone moves fast without shared approaches to evaluation, interoperability and risk management.

We have an opportunity to put the control rods in early, building the measurement and standards environment that allows innovation to grow safely and sustainably. Why measurement sits at the heart of quantum standards Quantum technologies are built on exquisitely sensitive physical effects. In many cases, the use of the end-product of quantum technology isnt the hard part. The hard part is making and manufacturing it consistently, and proving how it behaves, across devices, environments, suppliers, and time.

Thats why metrology (the science of measurement) is so central. It provides the tools to test, verify and benchmark performance, and it creates the evidence base that standards require.

This is also why National Metrology Institutes are so deeply involved. Many
SI units already have strong links to quantum principles: precision timing is fundamentally quantum, and modern electrical standards are quantum-based. The UK has decades of heritage here in work that stretches back to landmark achievements like the first atomic clock in 1955. Collaboration is non-negotiable in a field this complex Theres another reason quantum needs early standardization: no single organization, and no single country, can do everything. Quantum computing, networking , sensing and quantum-enabled position, navigation and timing span multiple technologies, multiple engineering challenges and multiple supply chains. Fragmented approaches dont just slow progress but can also create incompatible ecosystems that limit market access and reduce investor confidence.

Thats why international cooperation is so important, and why the standards conversation has become more strategic. The recently announced NMI-Q initiative brings together National Metrology Institutes from G7 countries
and Australia to accelerate pre-standardization research and develop best measurement practices that can shape global standards for quantum technologies.

In the UK, initiatives like the UK Quantum Standards Network Pilot provide a way for industry, academia and government to feed into standards development and represent UK interests within European and international standards
bodies, helping ensure UK quantum companies can access global markets and supply chains as the sector matures. Standards de-risk investment by making performance comparable For startups and scale-ups, standardization is often framed as a nice to have. In reality, its increasingly a commercial
necessity.

Investors and end-users dont primarily want a physics lecture. They want confidence. Questions come up repeatedly: Does it work? How does it compare with existing technologies? Is it reliable? What does it cost to run? Is
there a robust supply chain? Can it scale? Are there relevant standards or regulation?

Standards help answer these questions because they make performance
measurable in a way that is credible across the ecosystem, thereby reducing the risk of vendor lock-in, improving interoperability, and creating minimum quality expectations that buyers can trust. Over time, that enables economies of scale and multi-vendor supply chains, which in turn helps drive adoption.

Crucially, the old model of build the product first, then standardize it doesnt fit quantum. As industry has told us, standards now often need to emerge before technology is fully mature, because without shared approaches you risk building something that is locked out of the wider stack, or you end up with fragmented standards shaped by whoever moved first rather than by
what works best. A practical call to action for quantum innovators If youre building quantum technologies today, its important not the view early engagement with standards as giving away IP or slowing down your roadmap, but as a way of shaping the market you want to enter.

Get involved early so youre not excluded later. Contribute to the shared terminology and measurement practices that will define good in your segment. Use independent benchmarks to validate performance, strengthen credibility with investors, and build trust with partners across your supply chain.

Quantum computing will open new possibilities, and quantum sensing and timing technologies can deliver powerful capabilities in sectors that depend on precision and reliability.

But those opportunities will only translate at scale if the ecosystem can compare approaches fairly, integrate them reliably and prove value with confidence. By building the measurement and standards foundations now, innovation can scale when the market is ready. Check out list of the best product information management software .



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