Quantum Computing Edges Closer to Real-World Impact

Simulations, optimization, and cybersecurity emerge as key application areas.

Quantum computing is steadily transitioning from theoretical promise to practical relevance, with global hardware investments expected to exceed $21 billion over the next two decades. As systems capable of high-fidelity operations with hundreds of qubits become more common, attention is shifting to which industries will first benefit from commercially viable quantum machines. The search for a “killer application” — a breakthrough use case akin to ChatGPT’s rise in AI — remains a central focus for researchers and investors. IDTechEx’s latest report explores this landscape, drawing insights from conferences and interviews across the quantum ecosystem.

Chemistry Simulations Lead Early Use Cases

Among the most frequently cited near-term applications is quantum chemistry, where quantum computers could simulate molecular interactions beyond the reach of classical systems. Companies like Google Quantum AI and Quantinuum have already demonstrated early proofs of concept using real quantum hardware. One foundational problem, the Ising model, illustrates the challenge of modeling magnetic materials, which becomes exponentially complex for traditional computers. Quantum systems offer a path to accelerate discoveries in magnetism, battery chemistry, industrial compounds, and pharmaceuticals.

Momentum in this area has attracted sustained interest from chemical, pharmaceutical, and automotive sectors. Over the past decade, collaborations between these industries and quantum developers have grown steadily. The potential to unlock new materials and drugs has positioned quantum chemistry as a leading candidate for the first commercially impactful application. Continued progress in hardware and algorithm design will be critical to realizing this potential.

Optimization Across Industries

Another promising domain is optimization, where quantum computing could improve resource allocation, logistics, and financial modeling. Applications range from factory scheduling and energy grid management to delivery routing and portfolio balancing. D-Wave has championed this approach, using quantum annealers to demonstrate early-stage solutions in sectors including telecommunications, food services, and industrial research. These systems differ from gate-based quantum computers, offering a distinct path to practical deployment.

Despite the enthusiasm, theoretical support for quantum speedup in optimization remains limited. Classical methods continue to improve, narrowing the gap and raising questions about where quantum advantage will emerge. Nonetheless, the breadth of potential use cases makes optimization a compelling area for exploration. Commercial interest is likely to persist as companies seek efficiency gains in increasingly complex systems.

Cybersecurity Risks and National Strategy

Perhaps the most widely discussed — and feared — application of quantum computing is its ability to break existing encryption standards. RSA, a cornerstone of secure internet communications, is particularly vulnerable to quantum attacks. A recent study by Google Quantum AI suggested that RSA-2048 could be compromised in under a week using fewer than one million noisy qubits, a sharp reduction from earlier estimates. This shift reflects algorithmic improvements rather than hardware breakthroughs, highlighting the interplay between software and physical systems.

Most quantum hardware roadmaps project reaching the one million qubit threshold in the early 2030s. While immediate threats are unlikely, the possibility of a “Q-Day” — when quantum systems can reliably break encryption — is growing. Governments and corporations are beginning to adopt quantum-safe cryptography in anticipation. The urgency of this issue continues to drive national quantum initiatives and long-term investment strategies.