Quantum’s next unicorns are being built now 🦄
Inside the scramble for quantum’s commercial edge
This week I was back in London for Economist Impact’s 4th annual Commercialising Quantum Global summit. The big question for founders, business leaders, and anyone betting on the future: how close are we, really, to the age of true quantum computing?
Depending on who you ask, we’re “five to ten years away,” or only a few unexpected breakthroughs from a market reset. But behind the headlines, the shift isn’t just theoretical. Across finance, healthcare, telecoms, and national infrastructure, the groundwork is quietly being laid for a new commercial landscape.
While the dream of world-changing quantum computers is still just out of reach, practical use cases are arriving faster than you’d think: from turbocharged supply chain optimisation, to pharmaceutical discovery, to real-time modelling of everything from flight paths to financial markets.
Silicon Valley has a head start, but London is positioning itself as an ecosystem builder, funnelling public and private capital into clusters designed to attract talent, spin out start-ups, and keep home-grown innovation local.
Of course, with every breakthrough comes new risks. Quantum’s looming threat to existing encryption has CISOs, policymakers, and security vendors in a race against the clock, working to patch the “harvest now, decrypt later” vulnerability before it’s too late. Simultaneously, the combination of quantum and AI is poised to redefine what’s possible in prediction, simulation, and even cybersecurity itself.
So, what’s real now? Which sectors are on the brink? And how should founders and investors move before the window closes?
My dispatch is full of insights from two days on the front lines of quantum’s coming-of-age story: listening to innovators and leaders breaking down the lessons, commercial plays, and signals to watch 👇🏻
This deep dive is 5,000+ words, so you can use the table of contents on the left to jump between topics (if you’re reading online). If you download the Substack app, you can also listen to a narrated version of this feature.
— Millennial Masters is sponsored by Jolt ⚡️ reliable hosting for modern builders
Why quantum isn’t just faster computing
For decades, traditional computers have powered everything from search engines to space missions by crunching numbers at lightning speed. But at their core, even the world’s fastest supercomputers are glorified calculators, limited to processing bits (ones and zeros) one at a time, no matter how fast they go.
Instead of just “on” or “off,” quantum bits (qubits) can exist in multiple states at once. This opens up the possibility of solving problems so complex, like simulating molecules or optimising vast supply chains, that classic computers would take centuries to crack.
If you’re new to the field, here’s one way to picture it: solving a maze with a regular computer is like trying every path, one at a time. A quantum computer can explore all possible routes simultaneously and find the exit in a fraction of the time.
The idea for quantum computing dates back to the 1980s, but only in the last few years have we seen early hardware move out of the lab and into the hands of start-ups and enterprise teams.
As conventional chips reach their physical limits, the “quantum leap” is no longer science fiction, but a strategic bet for everyone from Big Tech (IBM, Microsoft and Google are at it) to new spin-outs.
Quantum reality check: Hype or real returns?
Here’s the challenge facing quantum computing. For all the billion-dollar projections and conference-stage optimism, the gap between promise and proof remains wide.
Jerry Chow, IBM fellow and director of quantum systems, boasted a simple mission: “Build useful quantum computing and bring it into the world.” But he made it clear that “useful” is the bar that most of the field still fails to clear.
Why does it matter? Quantum computing, if it works, could rewrite the rules for “drug discovery, materials science, and logistics”: domains with problems so hard that classical computers still choke on them. “We’re talking about huge scale commercialising quantum computing and in fact, Boston Consulting Group (BGC) recently predicted that this is a $500 billion opportunity for all of us,” Chow noted.
But there’s a catch: The industry still needs to prove where quantum can truly outperform classical computers. Without clear, commercially relevant use cases, adoption will stall.
What comes next is the hard part. Chow sees a future shaped by hybrid architectures, quantum and classical systems working together, and engineering cycles. And for founders and investors, a warning: quantum’s winners will be those who turn technical possibility into measurable, market-shifting impact.
This was echoed by other leaders from Rigetti (Subodh Kulkarni), Oxford Ionics (Chris Ballance), ORCA Computing (Richard Murray), IBM Quantum (Sarah Sheldon), and Google Quantum AI (Tom O’Brien), who traded sharp views on how close we really are, and what counts as real progress.
That’s because there’s no single, agreed benchmark for quantum progress. Each company uses its own metrics, which makes it hard to know when we’ve crossed the line from promise to practical results.
The consensus? Future wins will come from tight integration between hardware, software, and user needs. Hype and over-promising are risks too. If quantum doesn’t deliver real value soon, it could lose credibility and investor support.
Bridging the gap between today’s experimental “utility” and true quantum advantage in business is the real challenge. For now, the opportunities are big, but the hurdles are just as steep.
How close are we? The truth about quantum timelines
Quantum computers promise breakthroughs, but the bar keeps rising as classical systems get faster and cheaper. Infleqtion CEO Matthew Kinsella said, “It all comes down to economics.” Real quantum advantage will be obvious “when a profitable company will purchase a quantum computer using cash off their balance sheet,” because they believe they will earn a larger return on expenditure in their function.
Kinsella sees a future of hybrid systems with CPUs, GPUs, and quantum machines solving what classical can’t. Material science, chemistry, and drug discovery are likely to be first.
But true commercial traction will only come when error correction and scale hit hard numbers; think 10,000 qubits, not a handful. Mark Jackson of Quantinuum argued that reaching this threshold will fundamentally change the game: “You could quickly scan through a million possible drugs, simulate how they behave… you could do things like that in just a few years.”
Hybrid quantum-classical systems are likely to be the norm for years, with benchmarks set by real-world results. For now, almost all the money comes from governments and national labs, but Kinsella sees a tipping point by the end of the decade.
Jackson also described how quantum and AI will increasingly reinforce each other. “AI will be essential for quantum. Fact, we’re already starting to use it… Quantum will also be more efficient for AI.” Rather than replacing conventional hardware, quantum systems will slot into the computational landscape for problems that demand vast parameter searches, like generative quantum AI and advanced machine learning.
Kinsella’s advice for quantum start-ups: build commercial muscle early. “It’s very challenging to make the shift from a research company to a commercial company… injecting commercial DNA sooner rather than later is of utmost importance.”
The qubit conundrum: How much is enough to win?
When it comes to quantum computing, bigger isn’t always better. James Palles-Dimmock, chief executive at Quantum Motion, tackled the hype about ever-increasing qubit counts: “We need a lot more qubits than people realise… 100,000 is kind of the entry point now for something that’s truly useful for economic development.”
According to Palles-Dimmock, this figure comes from the tough reality of error correction: turning unreliable physical qubits into stable, fault-tolerant logical qubits, which can mean hundreds or thousands of physical qubits for every single logical one.
But raw numbers alone aren’t the answer. “You need to have a heck of a lot of high-quality things… If you are just below the [error correction] threshold, then you’re just making it worse.” For real-world systems, architecture and control matter as much as scale.
In quantum, big headline numbers (like total qubits) mean little without real performance: metrics like quantum volume, error correction, and logical qubits matter more than the raw count. Mark Jackson (Quantinuum) gave a sharp analogy: “It would be like if an aeroplane seats 1,000, but the engines only lift six.”
The bottleneck isn’t just the qubits; it’s the control stack, the hardware integration, and the ability to miniaturise supporting electronics so they don’t balloon to the size of a building. “There’s one thing about a really smooth qubit. But then if you need for every single qubit racks of GPUs to understand, that’s not a scalable game either.”
The bigger challenge? Making quantum affordable and accessible, so the next breakthrough isn’t limited to a handful of countries or research labs. Palles-Dimmock believes that “Unless we have it so that there’s a 14-year-old… thinking, I’ve got this nutty notion… and they can sit down and use it, because it doesn’t cost a billion dollars… that’s where the genuinely world-changing things will come.”
Right now, over 95% of quantum investment is hardware-centric. Yet, as in classical computing, the true long-term value will come from software: by some measures, up to 70% of the stack’s future worth. Why does it matter? The next phase of quantum development, error correction and scaling, can’t be achieved by hardware teams alone.
So as Riverlane CEO Steve Brierley and National Quantum Computing Centre (NQCC) chief scientist Elham Kashefi made clear, the spotlight now needs to shift: software will decide how fast the ecosystem matures. The sector is at the dawn of the “error correction era,” and software talent is the new strategic edge.
How to start building your quantum advantage now
If the last wave of digital transformation punished the slow adopters, quantum may move even faster.
Zulfi Alam, corporate vice-president for Microsoft Quantum, drove home a blunt reality for business leaders: if you wait for quantum to be easy or mature, you’ll be left behind. “Companies need to start to figure out. It’s going to take time.”
But Alam was clear: the learning curve is steep. Building quantum capability is more like creating a blockbuster video game: years of investment, new skills, and open collaboration across industries. “All boats rise together,” he said.
Microsoft’s bet is that quantum’s earliest impact will hit hardest in fields like materials science and pharma, where problems are too complex for even the biggest classical supercomputers. Alam pointed to their own milestone, a new battery electrolyte found via quantum simulation, as proof that advantage goes to those willing to experiment before the technology is “finished.”
For business leaders, the message is practical: stop waiting for the perfect use case or a fully packaged solution. Quantum won’t suddenly become plug-and-play. Instead, start building teams, skilling up, and running early experiments in any “low data, high computation” problem space. It’s the only way to be ready when quantum tips from promise to productivity.
Quantum in the wild: Real-world breakthroughs now
Quantum navigation: Next-gen GPS lands in the real world
The promise of quantum navigation is already beating traditional GPS backups in the wild. Michael Biercuk, founder and CEO of Q-CTRL, revealed how quantum magnetometers have finally moved from the lab to real aircraft, delivering “quantum advantage” in practical navigation.
Why does it matter? GPS is increasingly vulnerable to jamming and spoofing, especially across critical flight paths in Europe, the Middle East, and Asia. Biercuk painted a vivid picture: active GPS interference is now so common it resembles a new “electronic iron curtain” in global airspace, raising operational headaches and real safety risks for pilots and passengers.
Q-CTRL’s breakthrough is twofold. First, they developed AI-powered software that “denoises” quantum sensors in real time, slashing interference and making them reliable in noisy, real-world environments — without endless recalibration or awkward in-flight routines. Second, their quantum magnetometer is tiny (smaller than a coin), yet delivers 100x the accuracy of conventional inertial navigation systems. In a live trial, Q-CTRL’s solution held its position with remarkable precision, even during manoeuvres that disrupt other systems.
The technology is already being prepared for deployment on commercial aircraft through a partnership with Airbus, and demand is surging. First deliveries are expected in 2026, with applications also spanning autonomous drones and maritime navigation (using quantum gravimetry).
The upshot: quantum navigation has achieved a genuine “quantum advantage,” outperforming the best classical alternatives in the field, not just in theory. For aviation, defence, shipping, and any industry that can’t afford to lose its way, quantum sensors may soon offer a new level of security and precision beyond GPS.
Building on the buzz around Q-CTRL’s quantum backup navigation system, the next challenge is moving from research pilots to frontline integration. The promise is clear, but so are the hurdles.
Erin Beilharz of Lufthansa Systems explained: “We need to put the quantum sensor into a piece of hardware embedded in the avionics. Then you have to do a certification before any proof of concept can happen. This is typically 18 months. There’s politics, there’s stakeholder management around that.” When will quantum navigation move from backup to backbone? “It looks easy, but maybe it’s going to be easier in 2045, I don’t know,” said Beilharz.
On the technical side, Nima Leclerc of MITRE Labs broke down the engineering demands: “The basic idea with these platforms is… you want to be able to detect the Earth’s crustal magnetic field, and take really accurate measurements of that and compare that against some reference… The spatial variation of the magnetic field that you’re trying to measure will be on the border of nanotesla, which means you need a really accurate sensor to be able to detect those really tiny magnetic fields, and often there’s going to be other types of interference, electromagnetic fields, acoustic signals, other types of vibrations.” He added, “One of the advantages of our platform is that the way we control the quantum sensor allows us to adaptively cancel out the noise of the environment, kind of like when you put on noise cancelling headphones.”
Quantum brain scans: Diagnosing what MRI can’t see
Quantum brain scanners could be about to change how we diagnose, monitor, and protect the brain, both in the clinic and on the battlefield.
David Woolger, CEO of Cerca Magnetics, explained the core problem: “A lot of the diseases that we’re looking at don’t actually show any structural differences at all. So what we’re needing to look at is differences between the brain function.” MRI, he noted, is “mainly for structural brain imaging,” while traditional EEG “has some challenges in that your skull interferes with the electrical signals.” Enter MEG (magnetoencephalography) which uses magnetic signals “the skull doesn’t interfere with…so you’re actually getting good spatial and temporal resolution.”
The real leap comes from wearable, quantum-enabled MEG systems. Woolger described how their optically pumped magnetometer (OPM) tech outperforms legacy SQUID-based machines: “The OPM data is much clearer, and the localisation… is to the same area of the brain.” Unlike the huge, rigid SQUID systems, the OPM MEG scanner is wearable, works for everyone from babies to adults, and lets subjects move naturally. “We’re able to move freely during the scan… as a result, we have better data and, economically, the OPM MEG system is cheaper,” said Woolger.
The applications are multiplying. For dementia, Cerca partnered with Oxford to scan for early biomarkers. “We have, in early data, been able to see differences between healthy controls and people suffering from dementia,” said Woolger.
Professor Karen Mullinger (University of Nottingham) explained the significance for concussion and military brain injuries. “If we take an MRI of someone with a subtle brain injury, then we’re going to see nothing different in this image. However, what we can do is measure the MEG signals… we’ve already shown the value of this for concussions.” In military research, the quantum system can scan personnel before and after blast exposure, even as they move. “We’re expecting to see fundamentally new insights into the acute changes in brain function…that can then inform training protocols… and when it’s safe for those military personnel to return to their duty.”
Cerca has already shipped 11 systems since 2020 to hospitals and universities globally. Regulatory approval is next. Woolger said: “We are just in the process of moving this through to a clinically approved device, which will open up a much wider market for us.”
Quantum sensing is already showing real-world impact. The next step: making these tools as routine as a blood test on the sports pitch, in the clinic, and beyond.
Quantum sensors: Hidden worlds, smarter decisions
With up to 60% of major UK transport projects running into costly, risky delays because of hidden ground conditions, quantum gravimetry promises a step-change. Michael Holynski, principal investigator at the UK Quantum Technology Research Hub and professor at the University of Birmingham, believes the opportunity is enormous, if the sector can overcome the barriers to scale.
Quantum gravity sensors, now proven in field trials, allow for rapid, non-invasive detection of what lies beneath, whether it’s hidden utilities, tunnels, or geological risks. “What’s interesting,” said Holynski, “is it provides density information, which for end users, that’s the missing ingredient in their toolkit.”
But while the promise is clear, the hurdles are substantial. “The challenge is, it can detect deep features, but it’s limited by noise… Surveys are always limited in their resolution, and they take too long. People can’t make decisions on site.”
The current sensors “measure roughly once per second. For a rail survey, for example, that’s not going to give me very much information.” Holynski and his team are working to make sensors faster, cheaper, and smaller: “Can we make these sensors operate at much higher bandwidth (at 20 hertz)? We have one running in the lab now, 100 hertz, but we don’t get all the performance within the frequency.”
He also pointed to the need for a commercial story: “Just demonstrating we can do this is not enough to turn it into a commercial product. We need to develop a business case, market readiness, and understanding of what the sensors can do and how they can fit workflows.”
AI + quantum: What’s worth paying attention to
Quantum and AI are colliding, and everyone in the room wanted to know if it’s time to pay attention, or just a Silicon Valley fever dream. With AI hitting the limits of what classical computers can deliver, quantum’s arrival could redraw the map for tech leaders, investors, and anyone betting on next-gen compute.
Ann Dunkin, former chief information officer for the US Department of Energy, pointed to energy, climate, and advanced manufacturing as ground zero for quantum’s first real impact. “Quantum is going to be incredibly helpful for us, coupled with AI, to drive the new technology: battery materials, solar panel materials, the ability to model and implement solar module reactors, finding geothermal, optimising wind farms,” she said. It’s not theory, it’s the front line of the energy transition.
Alex Leigh, Investment director at Future Planet Capital, brought the VC’s lens, making it clear that patient capital still expects near-term applications. He flagged quantum navigation and timing as “live” opportunities: “If you’re a start-up, I would focus on that, because that’s how you get investment and get to that first foothill, and then other things will be unlocked later.”
Yet Perry Philipp, chief data officer at Entain Group, mapped out how regulated industries like gambling and biotech are watching quantum and AI for competitive edge, but safety and compliance set the tempo. “We have to make sure that player safety is front of foremost, if otherwise we’ll lose our licence… if we lost our UK licence, 40% of our business shuts off overnight.” In both AI and quantum, trusted execution wins.
Consensus landed on life sciences and materials as the first breakout sectors. “Pharmaceuticals… creating medicine… will be the fastest,” said Maximilian Walz, VP for technology and incubation at T-Systems. Leigh and Philipp both highlighted drug discovery and material selection as quantum’s most investible frontier, with deep-pocketed buyers and urgent technical pain.
Why quantum needs AI to break through
Quantum’s next big leaps are running on AI power. That’s the approach at Denmark’s DC AI, where chief executive Nadia Carlsten has built an AI supercomputer (stacking over 1,500 Nvidia GPUs) designed to “bring more of these capabilities in the hands of the academics, but also start-ups and enterprises.”
The impact is already visible. “The team that was led by the Niels Bohr Institute at the University of Copenhagen has been able to boost the efficiency of the simulation by up to 100 times compared to what they were doing on the CPU cluster.” DC AI’s customers include start-ups like Quantify, who are “working on quantum algorithm development for quite a while,” and are now using DC AI’s platform to “simulate even more complex chemistry.”
Carlsten said: “A lot of customers when they come to us, this is the first time that they’re accessible, so we have to help them… take something that is usually a pretty vague use case, and an idea of what could work and could scale and actually getting it to perform well on the computer.”
For the quantum community, the message is clear: “Everything that we do is with that mindset of helping accelerate the roadmap to those fault tolerant quantum computers. And what our users are doing primarily falls into two buckets. They’re either using [our AI supercomputer] to help design the quantum computer… or they’re also talking about using AI-based approaches to control and optimise the computer.”
How close are we to a quantum internet?
Quantum internet isn’t arriving overnight. But in Qatar, the groundwork is quietly being laid, one fibre link at a time. Saif Al-Kuwari, Director at Qatar’s Centre for Quantum Computing, wants to clear up a common myth: “Quantum internet is going to be… a layer that will work hand in hand with the classical internet.”
Forget replacing the web: this is about adding unbreakable security to the backbone we already use. As Al-Kuwari put it, “things like… unconditional security… with enough resources, you would not be able to break that internet.”
For Ooredoo Qatar, telecoms security is urgent. Senior director Mohammed AlZaidan made the stakes clear: “We have very sensitive data… we don’t want to reach a stage where this data is in jeopardy and we don’t have enough security to protect their data.” The motivation is obvious: “It’s an investment that we have to do sooner or later as a telecom operator. So it’s better to be able to learn about it sooner.”
Yet the path forward is anything but simple. Al-Kuwari explained the technical bottleneck: After 100km of fibre, “you need to have… a quantum repeater. The problem… is that it does not exist yet… we don’t have a memory that will allow us to store the [quantum] state.”
For industry, infrastructure costs are another barrier. “It would be a big challenge for us to go and build an isolated separate network only for QKD and quantum signalling, quantum communication. It wouldn’t be a practical solution,” said AlZaidan.
So the approach is incremental. “Within six months, we’ll have to try to transmit the [quantum key] over the… fibre,” said AlZaidan, pointing to early pilots as the first real-world steps.
Al-Kuwari summed up the global challenge: “If the community put as much attention and effort into quantum communication as they are doing for quantum computing, I think we would come very close to realising quantum repeater.”
Cryptonomics: Bracing for quantum’s great data heist
Quantum computing is also a looming cybersecurity headache. Kraft Heinz CISO Ricardo LaFosse broke down why “quantum-resistant encryption is no longer optional,” especially as “threat actors are starting to play the longer game.”
LaFosse explained the core risk: Steal sensitive, encrypted files today, wait for quantum to break the code tomorrow, then “profit and mass havoc.” Organisations can’t just tick a compliance box. “You just need to make it harder for the threat actors to get in. It sounds absolutely horrible. The old adage, you don’t need to outrun the bear, you just need to outrun the person next to you, that’s the game of cybersecurity.”
LaFosse urged a “crypto inventory” as a starting point: “Start identifying the type of encryption that you’re using. There are many providers out there that can help build this inventory for you. Determine your prioritisation… start prioritising the migration path to PQC [post-quantum cryptography] resilient algorithms.”
He didn’t mince words on urgency: “NIST (Cybersecurity Framework) is saying that various encryptions are expected to be broken based on current evolution of quantum right now, by 2030, and you need to start working on a migration path before 2030, so please don’t start in 2029.”
In a world of “harvest now, decrypt later,” the best defence is planning now, before quantum computers turn today’s secrets into tomorrow’s open season.
“There is a lot of talk about organisations needing to migrate to post-quantum cryptography… but around 80% of the cryptography that must migrate is not in their direct control. It’s sitting in their supply chain,” explained Ben Packman, Chief Strategy Officer at PQShield.
The way forward? “Instead of trying to find out at an algorithmic level where everything is, go find the data that you care about most, that has a long enough half-life to worry about these particular scenarios… and then discover all the vendors that you’re using that touch that data.”
With post-quantum cryptography (PQC) maturing and quantum key distribution (QKD) moving out of the lab, which approach offers the best path to quantum-secure communications?
For Craig Farrell, blockchain and quantum product lead at EY, it’s not an either/or scenario: PQC for broad coverage, QKD where ultra-high security and budgets permit. “If you’re using Azure or Google Cloud… a lot of the heavy lifting can actually be done by the cloud providers. But you have to assess this on a case by case basis. Every system will have to say: what is going to be upgraded by the cloud, which is great, and what are the systems that actually need manual upgrades and migration.”
London’s quantum moment: Lab to global scale
London just put quantum on the map, officially. Deputy Mayor Howard Dawber announced a new London quantum technology cluster at the event, with a half million pounds of money from the mayor to support the growth of businesses, accelerators and new technologies. For Dawber, this is about more than technology: “We know technology… but we’re only just starting to explore the practical applications of quantum technology… I think we’re at the same step forward” as the first days of electronic computing.
Tom Foulkes of King’s College London called it “London working together… a lot of this is built around the London Centre for Nanotechnology, which really operates across the three universities, and quite a wide range of other… activities.” Foulkes added, “If we want to compete on the world stage, for me, [collaboration] is really important.”
Mary Ryan of Imperial College London believes the need for “bringing all of the key groups… if we are going to do the best job for London, the best job for the country. If we’re going to position ourselves on a global stage… this framing of Innovation Cluster and deep tech as a London initiative… is really important.”
Will Lovegrove from UCL summed up the stakes: “We have three of London’s most fantastic universities… an opportunity in time, after hundreds of millions of pounds… of quantum research going into many, many universities, an inflection point where I… think that knowledge is about to come out into society. And this fund and these universities give us an opportunity… to create an optimum stack of innovation.”
This is part of the UK’s bid to scale up quantum information processing from a billion-pound mission with the potential to add £11 billion to GDP by 2045 and create thousands of jobs. But as Professor Sir Peter Knight, Chair of the UK National Quantum Technology Strategic Advisory Board, put it: “Our struggle is going to be focused on scale, and we deliver stuff at larger scale.”
Dave Smith, national technology adviser at the Department for Science, Innovation and Technology, pointed to £121 million in new government funding for quantum this year, including support for “adoption of quantum products in healthcare, transport, defence, construction, energy… and accelerating real-world deployment of quantum systems.” But public capital is just the start: “It’s not just government capital. It has to be private capital, although government capital will continue to lead for a while.”
And none of this happens in isolation. “The UK is strong, but clearly can’t do this alone, and that’s why we need friends with benefits. If quantum is going to change the world, it needs to be global… those of us that are not the US and China, we need to work together with the US,” Smith said. Recent moves include a new quantum cooperation agreement with Japan, ongoing partnerships with the US, Australia, Canada, the Netherlands, Denmark and the EU.
Who’s really going to win quantum’s next era?
Quantum’s breakthrough moment won’t be announced with a press release or a so-called “Q-Day.” It will arrive quietly, through field tests, regulatory deadlines, and unexpected leaps in capability, long before most people realise the ground has shifted.
Yes, broad utility is still five to ten years out, but the window for building and backing the next wave of unicorns is now. Instead of waiting for everything to be “ready,” future winners are experimenting with field deployments, partnering across the ecosystem, and building teams who understand both the science and the realities of product.
What’s different about this cycle is the convergence of quantum and AI, each accelerating the other. The capital is flowing into deep tech, not just SaaS. And business leaders are waking up to the fact that early quantum deployments (navigation, sensing, security) are already reshaping markets at the edge.
This is the moment to look beyond pilots and proofs-of-concept. The founders and investors moving now, staking claims, recruiting talent, and shaping the new benchmarks, will define what quantum advantage really means for business and society in the decade ahead.
Once the first major applications hit, the pace will pick up quickly. The field is still open for those willing to engage early.