Imagine designing a better battery, discovering a new medicine, or developing a material that can withstand extreme temperatures. Even the world’s most powerful supercomputers can struggle to simulate the behavior of complex molecules and materials accurately. Quantum computers could eventually help with some of these problems, potentially opening doors to discoveries that are difficult or prohibitively expensive today.But don’t expect a quantum computer to replace your laptop or suddenly solve every problem that conventional computers cannot. Its potential is much more specialized. And while companies are racing to build increasingly powerful machines, the most important applications are still taking shape. So, what could quantum computers actually solve, and how long might we have to wait?First, what makes quantum computers different?Traditional computers process information using bits, which represent either a 0 or a 1. Quantum computers use quantum bits, or qubits, which can exploit phenomena such as superposition and entanglement to perform certain calculations in fundamentally different ways.This does not mean they try every possible answer simultaneously. As the US National Institute of Standards and Technology (NIST) explains in its quantum computing guide, extracting useful information from a quantum calculation requires carefully designed algorithms.Their advantage comes from the ability to manipulate complex quantum states, making certain problems potentially much easier to tackle than with conventional computing.The catch? Qubits are extremely fragile. Small disturbances can introduce errors, and researchers need increasingly sophisticated error-correction systems before quantum computers can reliably perform lengthy calculations.1. Designing better medicines and chemicalsOne of the most promising applications is quantum chemistry. Molecules behave according to quantum mechanics, which makes quantum computers a potentially natural tool for simulating them.Even powerful classical computers struggle to accurately model certain complex chemical interactions, particularly in systems involving strongly correlated electrons. Quantum computers could eventually simulate these interactions more directly, helping researchers understand how molecules behave and react.That could have implications for drug discovery, chemical manufacturing, and the development of more efficient catalysts. For example, researchers could investigate molecular structures and reaction pathways to identify promising compounds or chemical processes.A particularly interesting possibility is developing better catalysts for producing ammonia, a key ingredient in fertilizer manufacturing. More efficient chemical reactions could also help reduce the energy required for industrial production.A 2025 research perspective published in the Journal of Chemical Theory and Computation, involving researchers from several national laboratories and universities, identified potential applications in photochemistry and materials design using early fault-tolerant systems with approximately 25 to 100 logical qubits.When? Early, scientifically meaningful demonstrations could emerge as fault-tolerant systems become available over the next few years. Broader applications in pharmaceutical development and industrial chemistry will likely take longer, potentially extending into the 2030s.2. Discovering better batteries and materialsWhat if researchers could simulate a material’s properties before spending years developing and testing it in a laboratory? Quantum computers could help investigate the behavior of electrons in complex materials, potentially improving the search for better battery components, superconductors, solar cells, and industrial materials.This is closely related to the chemistry problem, but the implications extend into energy and manufacturing. Better simulations could help researchers understand why certain materials conduct electricity, store energy, or exhibit unusual magnetic properties.The US Department of Energy’s Quantum Genesis initiative specifically identifies chemistry, materials science, plasma physics, and high-energy physics as potential application areas. Research applications could begin gaining traction in the late 2020s, with more substantial materials-discovery applications potentially emerging during the 2030s. These are estimates, not guaranteed delivery dates.3. Breaking today’s encryptionNot every potential quantum application is something to look forward to. Many widely used encryption systems rely on mathematical problems that are extremely difficult for conventional computers to solve. One example is the factorization of very large numbers, which underpins the security of RSA encryption.In 1994, mathematician Peter Shor developed a quantum algorithm that could theoretically solve this problem efficiently. A sufficiently powerful quantum computer running this algorithm could threaten RSA and other public-key cryptographic systems.That does not mean today’s quantum computers can crack bank accounts or unlock encrypted internet traffic. They are nowhere near the required capabilities.However, the threat is serious enough that governments and technology companies are already preparing alternatives. NIST has published post-quantum cryptography standards designed to withstand attacks from both conventional and future quantum computers.The US Government Accountability Office reported in October 2026 that experts believe a cryptographically relevant quantum computer could emerge as soon as the 2030s, although estimates vary. The threat is a 2030s concern, not an established capability today. The transition to quantum-resistant encryption is already underway because sensitive information collected now could remain valuable for decades.4. Tackling complicated optimization problemsQuantum computers could also help with problems involving enormous numbers of possible combinations. Consider organizing airline schedules, optimizing industrial supply chains, managing electricity grids, or coordinating complex manufacturing operations. Finding the best solution among countless possibilities can become computationally expensive.Quantum algorithms may eventually help explore certain optimization problems more efficiently, particularly when combined with conventional computers. However, this is one area where expectations need to be tempered. There is no established evidence that quantum computers will routinely outperform the best classical methods across everyday business optimization problems.When? Experimental applications are already being explored, but commercially meaningful advantages remain uncertain. Some optimization problems may benefit during the late 2020s or 2030s, while others may never offer a worthwhile quantum advantage.So, when does the quantum era actually begin?There is no single arrival date. IBM’s current quantum roadmap targets a large-scale fault-tolerant system for 2029, while the US Department of Energy’s Quantum Genesis initiative aims to demonstrate scientifically relevant fault-tolerant systems by 2028.These are ambitious development targets, not guarantees that commercially useful breakthroughs will follow immediately. The likely future is not quantum computers replacing conventional machines. Instead, they will work alongside classical supercomputers and AI systems, handling specialized calculations that are particularly difficult for traditional hardware.The first big breakthroughs may not come as a flashy new consumer gadget. Instead, they could show up as a better battery, a more efficient industrial chemical process, or a new understanding of how a complex molecule behaves.