Why should you care about quantum computing?

Right now, criminal and state-sponsored hackers are intercepting and storing encrypted data they cannot yet decode. Likely targets include everything from corporate secrets and medical records to legal agreements and military communications. Why would these actors bother to steal data they can’t read? Because they are betting on developments in quantum computing that will eventually let them crack this encrypted data wide open.

This isn’t a fringe theory. The NSA (National Security Agency), NIST (National Institute of Standards and Technology), and ENISA (European Agency for Cybersecurity) are all treating this “harvest now, decrypt later” scenario as a live threat that is serious enough to demand immediate action. The NSA has mandated that all U.S. national security systems must transition to quantum-resistant cryptography by 2035—with new acquisitions required to be compliant by 2027. In Europe, ENISA issued updated guidance in April 2025 warning that the threat is “sufficient to warrant caution, and to warrant mitigating actions to be taken,” and recommending that organizations begin deploying post-quantum cryptography immediately. NIST has launched a parallel global effort to develop the new cryptographic standards on which these transitions will depend.

The message from all three bodies is the same: organizations are running a grave risk if they wait until quantum computers can break current encryption standards to begin upgrading. That is the reason business leaders need to pay attention to quantum computing now—not because the technology is ready, but because the risk is grave, and the cost of preparation is trivial compared to the cost of being caught flat-footed.

Quantum Computing 101

Classical computers store and process information as “bits,” where each bit is either a 0 or a 1. Quantum computers, by contrast, exploit the properties of quantum mechanics, working instead with qubits, which can exist in multiple states simultaneously. Tapping into the unusual features of quantum states in this way allows quantum computers to explore vast numbers of possibilities in parallel rather than working through them one by one.

This doesn’t mean that quantum computers are generally better than, or a replacement for, classical computers. Rather, quantum computers are a specialist tool for handling a specific class of problems that involve enormous combinatorial complexity—the kind of problems where the number of possible solutions explodes so fast that even the most powerful classical supercomputers can’t meaningfully explore them. In areas like these, quantum computers have the potential to offer not just incremental improvements on classical computing, but to redefine what is computationally possible in whole fields.

Logistics optimization, financial modeling, drug discovery, and cryptography are all examples of fields that involve exactly the kind of combinatorial complexity that quantum computers are built to handle. Of these, it is cryptography that demands the most immediate attention.

Hype and Reality

Disentangling the reality from the hype about quantum computing is genuinely difficult—and not just for casual observers. In January 2025, Nvidia CEO Jensen Huang suggested that useful quantum computers could be decades away, sending stocks in quantum-related companies into freefall. By mid-2025, he was far more bullish, describing the field as being on the cusp of an inflection point. If one of the most technically informed CEOs on the planet can shift his assessment that dramatically in six months, the rest of us should be humble about our ability to call the timing.

As is often the case with new technologies, there is real momentum on both sides. On the bullish side, Google announced in late 2024 that its Willow quantum chip solved a problem in five minutes that they claimed would have taken a classical supercomputer ten septillion years. In February 2025, Microsoft unveiled its Majorana 1 chip, claiming that they had implemented a new approach to building qubits that could scale faster than competing designs. IBM continues to publish ambitious roadmaps.

Credible researchers such as Nathalie de Leon, an experimental quantum physicist at Princeton, say that there has recently been a “vibe shift“ in the field—a growing sense that useful quantum machines could arrive within ten years rather than thirty. “I am much more certain that quantum computation will be realized, and that the timeline is much shorter than people thought,” Dorit Aharonov, a computer scientist at Hebrew University in Jerusalem, told Nature. Capital markets are paying attention too.

But the bear case is also serious. Quantum computing stocks like Rigetti and D-Wave have traded at more than 500 times estimated sales—with almost no real-world revenue and few practical applications. The machines remain fragile, error-prone, and require operating temperatures near absolute zero. There is a persistent and uncomfortable pattern in the research: researchers working on quantum computing announce a speedup, and classical computing researchers almost immediately find ways to match it. Quantum computing could be the next big thing—or it could be the next hot air balloon.

The point isn’t to resolve this debate. The point is that smart, informed people disagree sharply about when—or whether—quantum computing will deliver on its promise. And that disagreement should sound uncomfortably familiar.

We’ve Been Here Before

When ChatGPT launched in November 2022, it became the fastest-growing consumer application in history. Within two months, it had 100 million users. Enterprises scrambled to adapt. Boards demanded AI strategies overnight. It felt like a bolt from the blue.

But it wasn’t. Machine learning as a discipline dates back to the 1950s. Neural networks were being explored seriously in the 1980s. Even looking at the more recent past, the technology had been visibly advancing for over a decade. In 2016, AlphaGo defeated world champion Lee Sedol 4–1. In 2017, transformer architecture was introduced, which became the foundation for modern large language models.

This is not a story about AI. Rather, it’s a long-running, frequently recurring story about institutional blindness to technological disruption. With AI, the technology was visibly coming, and still most companies were caught without a plan, a team, or any institutional understanding of what was happening. Quantum computing is following a similar pattern: once again we see real scientific progress, genuine uncertainty about timescales, sharp disagreement among experts, and a business community that is mostly not paying attention.

“Those who cannot remember the past are doomed to repeat it,” said the philosopher George Santayana. So let us remember the general state of unpreparedness around AI, and try to do better with quantum computing.

What Businesses Should Do Today

The whole point of learning from the AI experience is that preparation doesn’t have to be expensive—it just has to start early.

1. Develop organizational literacy. You don’t need to hire quantum physicists. You need a small number of people—in strategy, technology, and risk management—who can follow developments, read past the hype, and flag when something becomes relevant to your business. The goal is to ensure that when a headline lands about a qubit milestone or a new standard, someone in your organization can tell you whether it matters and why.

2. Identify your exposed workflows. The potential impact of quantum computing on your business extends well beyond cryptography. Which of your core operations involve the kind of complex optimization, simulation, or modeling processes that could be disrupted—or where a competitor with quantum capabilities could leapfrog you? You don’t need to solve for this today. You need to know where to look when the time comes.

3. Define your trigger conditions. What specific developments—a demonstrated commercial application in your sector, a regulatory mandate, a breakthrough in error correction—would move you from monitoring to investing? Set these thresholds now, so that when news breaks, you’re executing a plan rather than reacting to a headline.

4. Get your cryptographic house in order. This is the most concrete and most urgent action. The NSA, ENISA, and NIST are all moving toward post-quantum cryptographic standards, but those standards are still evolving. That means you need two things. First, you need an understanding of where encryption actually sits in your organization—which of your systems depend on which cryptographic standards and where does encrypted data flow to third parties whose security posture you don’t control? Second, you need architecture that lets you swap cryptographic components independently when the standards settle, without forcing a rebuild of everything around them. Engineers call this crypto-agility. Think of it as future-proofing your security not against a specific threat, but against the certainty that the regulatory and threat landscape will keep shifting.

None of this is to say that quantum computing is certain to become practically relevant to your organization in the near future – or even in any future. Experts themselves disagree over this question. The point is that businesses cannot afford to wait for the experts to reach consensus. If quantum computing becomes practically useful within the next decade, the implications could be enormous. The cost of paying attention is low; the cost of being caught flat-footed could be devastating.