Quantum operations at the chip core can be simultaneously applied across multiple fields, such as molecular structure analysis (left), large-scale data optimization (center), and network security (right). However, it is currently in an early, special-purpose commercialization stage, and significant technical challenges remain before general-purpose quantum computers can be realized.
What if computers used a language other than '0 and 1'?
The computers, smartphones, and servers we use every day all operate on the same language: '0' and '1'. Electricity flowing is 1, and no electricity flowing is 0. With this simple combination of binary, we write documents, play videos, and run artificial intelligence models. This is the world of classical computers.
Quantum computing fundamentally overturns this premise.
It processes the minimum unit of information using Qubits (Quantum Bits) instead of bits, and a qubit can simultaneously exist in a state of both 0 and 1. This is Superposition, one of the core principles of quantum mechanics.
To put it in perspective: if a classical computer tries one path at a time when escaping a maze, a quantum computer explores all paths simultaneously. For certain types of problems, this difference can create a speed gap of billions of times.
Three Core Principles
To understand quantum computing, one must know three physical phenomena. All are concepts originating from a branch of physics called Quantum Mechanics.
① Superposition
Qubits maintain states of 0 and 1 simultaneously until they are measured. This is similar to tossing a coin in the air, where it is both heads and tails at the same time until it hits the ground. Thanks to this, quantum computers can process countless numbers of cases simultaneously.
② Entanglement
This is a phenomenon where two or more qubits are linked together so that when the state of one is determined, the state of the other is determined instantly. It is a counterintuitive phenomenon that Einstein called "spooky action at a distance," but thanks to this principle, quantum computers can compute information among qubits with extreme efficiency.
③ Interference
Quantum states act like waves, amplifying the probability of paths leading to the correct answer while canceling out the probabilities of incorrect paths. This works on the same principle as noise-canceling earphones, which create out-of-phase waves to surrounding noise waves to cancel out the sound. Thanks to this, quantum algorithms can 'guide' computations toward the right answer.
Why It Is Attracting Attention Now: The Decisive Turning Point of 2025–2026
Quantum computing has been studied theoretically for decades. So why now?
As of 2026, evaluations are mounting that the field has moved beyond mere research stages and entered the threshold of demonstration and commercialization.
A paper co-authored by major research institutions such as the University of Chicago, Stanford, MIT, and Delft University of Technology and published in the journal Science (January 2026) assessed that quantum technology has reached a tipping point similar to the early transistor era that reshaped modern computing. However, the paper also specified that "while functional quantum systems already exist, major further advances in engineering and manufacturing are needed to scale them into truly powerful machines."
The most symbolic event is Google's move. Google officially unveiled its Willow chip equipped with 105 qubits in November 2024, followed by its announcement in October 2025 that it had demonstrated verifiable quantum advantage for the first time in history using the Quantum Echoes algorithm powered by the Willow chip (Google Official Blog, October 22, 2025). According to Google, this algorithm performed molecular structure-related computations at a speed about 13,000 times faster than the world's fastest classical supercomputer at the time.
In addition, according to the Quantum Computing Report (dated April 16, 2026), Voyager Space and IBM successfully demonstrated the first quantum secure communication link between the International Space Station (ISS) and Earth, and Google Quantum AI began accepting external researcher proposals for the Willow processor that same month.
Around 2026, evaluations are growing that quantum computing has entered a transition period moving from a 'pure R&D subject' to an 'early practical product,' at least for certain special purposes (quantum simulation, optimization, quantum key distribution, etc.). At the same time, cautious outlooks coexist that realizing large-scale general-purpose quantum computers still requires years to decades of additional development.
Current Limitations: Neither Hype Nor Underestimation
To accurately understand the current status of quantum computing, its present limitations must also be faced directly.
Yuval Boger, Chief Commercial Officer of quantum computing startup QuEra, stated at the Q+AI conference held in New York in October 2025, "If anyone tells you that quantum computers are commercially useful today, I want to know what they're drinking."
The industry's goal is to build powerful, practical machines capable of solving large-scale problems that classical computers cannot solve, but the common perspective among a majority of experts is that this goal has not yet been reached at this point in time.
A core technical hurdle is Error Correction. Qubits are extremely unstable and their states are easily disturbed by minute vibrations in the surrounding environment, temperature changes, and electromagnetic interference. This is called Decoherence. Current qubits are noisy and have high error rates, and scaling to a scale of millions of reliable qubits has not yet been achieved.
There are also limitations in physical infrastructure. Superconducting quantum computers must maintain cryogenic environments close to absolute zero (−273.15°C), and the scale and cost of cooling equipment and control systems for this are substantial.
Research on error correction is increasing rapidly. According to data compiled by StartUs Insights, 120 related peer-reviewed papers were published in the first half of 2025 alone, a pace exceeding triple the 36 papers published in the entirety of 2024.
Fields Where Practical Application is Anticipated
Quantum computers will not transform every field. They possess overwhelming superiority over classical computers only in specific types of computations. Fields that experts are focusing on most currently include the following:
In the financial sector, some banks and asset managers are running pilot operations of quantum tools for risk modeling, option pricing, and portfolio optimization. In the pharmaceutical and materials sectors, quantum simulations exploring molecular structures and reactions are being utilized at the research stage, while in logistics and manufacturing, quantum optimization techniques are being test-applied to route optimization, scheduling, and supply chain efficiency.
The cybersecurity sector is cited as a particularly urgent area. According to research jointly announced by Google Quantum AI and quantum computing startup Oratomic in late March 2026 (reported by TIME on April 7, 2026), a warning was raised that the emergence of quantum computers capable of decrypting internet encryption protocols could happen faster than previously expected. Cloudflare cybersecurity researcher Bas Westerbaan described this as "a real shock," stating, "We need to significantly accelerate our efforts."
In response, Cloudflare announced that it has moved up its target date for quantum-safe transition to 2029. Underlying the setting of transition targets around 2029 by both Google and Cloudflare is the judgment that at least several years of transition preparation time are required before actual threats arrive.
Major Competitors and Technical Approaches
There is not just one way to implement quantum computers. Currently, major companies are adopting different qubit implementation methods, each with different strengths and weaknesses. IBM and Google have adopted the Superconducting method, while IonQ and Quantinuum use the Trapped Ion method.
PsiQuantum and Xanadu pursue the Photonic method, and Microsoft is investing in the Topological Qubit method. QuEra and Atom Computing, which pursue the Neutral Atom method, are also gaining attention.
Regarding market size, based on estimates from various market research firms such as Precedence Research and Fortune Business Insights, the global quantum computing market for 2025–2026 is estimated to be around $1.5 billion to $2 billion. Numerous reports forecast that this market will grow to over $10 billion in the early 2030s, though this is a scenario prediction based on the current point in time and may vary depending on the pace of technological development and the investment environment. In the case of IBM, it has formalized the development of the Kookaburra processor equipped with logical qubits and quantum memory as its 2026 roadmap target.
Notable announcements continue regarding individual corporate achievements as well.
According to the Quantum Computing Report (dated March 25, 2026), Indian startup QpiAI announced that it applied a dedicated hardware decoder to its 64-qubit Kaveri processor, reducing error correction latency from 60 microseconds to 1.5 microseconds.
The same outlet (dated April 14, 2026) reported that IonQ was selected for DARPA's HARQ program and demonstrated the world's first remote photonic interconnect between two independent ion trap systems. In addition, startup Sygaldry Technologies, led by Chad Rigetti, announced that it secured $139 million in investment with the goal of developing quantum-accelerated AI servers to reduce AI energy consumption.
Convergence of Quantum Computing and AI: New Acceleration
One of the notable changes in 2026 is the convergence of AI and quantum computing.
The Oratomic research team stated that AI played a pivotal role in the process of developing this algorithm, and co-author Dolev Bluvstein said in an interview with TIME, "There is no doubt that we accelerated this development by leveraging AI."
Experts evaluate that AI has already established itself as an essential tool across quantum research, including error correction, noise modeling, and pulse-level calibration.
According to industry expert forecasts compiled by The Quantum Insider (December 30, 2025), recent breakthroughs in AI-based quantum error correction and noise mitigation support the validity of this direction, and starting in 2026, quantum software engineering is rapidly emerging as an independent specialized field.
In the Korean Context
South Korea has also designated quantum computing as a national strategic technology and is expanding investment.
Quantum technology R&D investments led by the Ministry of Science and ICT, qubit research by the Electronics and Telecommunications Research Institute (ETRI), and the operation of quantum information science research centers at major universities are continuing.
While long-term investments are underway to build an independent foundation in global competition, the reality is that a significant technological gap still exists in the hardware sector between South Korea and leading companies such as Google, IBM, and IonQ.
Outlook: Distance Remaining Until 'Practical Quantum Computing'
Expert opinions are sharply divided regarding the timeline for the emergence of quantum devices capable of actually decrypting RSA-2048.
While resource estimation studies by Google Quantum AI and some security industry analyses raise the possibility of a threat-level device emerging around 2030 (±2 years) under an optimistic scenario, a more conservative perspective expects it to be in the mid-to-late 2030s or later.
Timeline predictions like this are in the realm of scenarios that vary depending on the speed of technological development, error correction efficiency, and investment scale. A common message among experts is singular: regardless of when the actual threat materializes, preparation for transition to Post-Quantum Cryptography must begin now.
Quantum computing is not a technology that replaces classical computers, but a complementary technology that solves specific types of problems that classical computers cannot solve.
Expectations are growing that solutions to some of humanity's most complex problems—such as drug discovery, climate modeling, financial optimization, and the reorganization of cryptographic systems—could come from this technology. However, the timing and scope depend on the results of ongoing research and investment, and it is more accurate to understand quantum computing not as a technology that changes the world all at once, but as a civilization-level transition process proceeding at a slow pace.