Two years ago, quantum physicist Dolev Bluvstein chose an academic career over the commercial sector, believing practical quantum computers were still too distant to be marketable. Today, as co-founder and CEO of Oratomic, Bluvstein is leading efforts to build a full-scale quantum computer by the end of the decade, following the company’s recent $300 million funding round—reported as the largest initial financing for a quantum start-up. This shift underscores a growing optimism in the quantum computing field, driven by a series of technical advances that suggest the long-held vision of quantum-powered machines is nearing realization.
Quantum computers operate fundamentally differently from classical machines, using "qubits" that can exist simultaneously in multiple states and become entangled, potentially offering vast improvements in computational power. The industry targets problems far beyond the capabilities of current technology, which has attracted significant venture capital investment—over $4 billion this year alone, nearly matching totals for 2025 and preceding years combined. The sector has also seen increased stock market activity, including the first initial public offering by U.S. company Quantinuum and the European debut of Finnish start-up IQM.
Despite this momentum, experts caution that considerable uncertainty remains over when quantum machines will solve meaningful commercial problems and which technologies—or companies—will ultimately prevail. Christophe Jurczak, founder of the French company Pasqal and head of the investment firm Quantonation, describes quantum computing as a “perpetual five-year technology” characterized by breakthroughs that frequently reveal new technical obstacles, delaying broader commercialization.
While many in the field believe that foundational science has been established and that ongoing challenges are mainly engineering-related, key players like Google and IBM continue to explore multiple qubit technologies. For instance, Google has expanded research into neutral atom qubits, a method also pursued by Oratomic, while IBM recently acquired a company developing silicon spin qubits. Although there have been initial claims of "quantum advantage," in which a quantum computer outperforms classical counterparts on specific tasks, these results have not yet translated into practical commercial applications.
Industry leaders emphasize the need to move quantum computing beyond the laboratory and into real-world engineering and application development. James Palles-Dimmock, CEO of Quantum Motion, highlighted the importance of cost-effective approaches to building large-scale quantum machines, cautioning against the notion that quantum computing’s potential justifies unlimited spending.
Current quantum algorithms offer exponential speed-up primarily in two areas: breaking common encryption methods and simulating quantum systems such as subatomic particles. The encryption-breaking capability raises cybersecurity concerns but is acknowledged by some industry executives, including Infleqtion CEO Matthew Kinsella, as unlikely to become a major source of commercial revenue. The second application, simulating natural quantum phenomena, is widely seen as the most promising near-term opportunity, with potential impacts on drug discovery, battery technology, and energy and climate challenges. Steve Brierley, CEO of UK-based Riverlane, stresses that while this is a specialized field, it should not be considered a limited business opportunity.
How much financial benefit quantum hardware providers will derive from advances in simulation and other applications remains uncertain. However, some investors foresee substantial profits through partnerships with pharmaceutical and chemical companies. Peter Barrett of Playground Global projects potential earnings of “hundreds of billions of dollars” over the coming decade via profit-sharing arrangements.
Outside of these areas, the commercial prospects for quantum computing are less clear. While some companies assert the technology will enhance the resolution of complex optimization problems common in industry, Nvidia CEO Jensen Huang and others argue that existing classical methods already adequately address many such challenges. Jurczak notes that heuristics often suffice, reducing the need for quantum precision in practical business contexts.
Nevertheless, many executives maintain that quantum computers will have broad commercial utility, even if they do not always deliver exponential speed-ups. IonQ CEO Niccolo de Masi expects much of the value to come from algorithms offering "quadratic speed-up," which though less dramatic than exponential acceleration, could still yield significant time savings — for example, completing tasks in minutes instead of hours — in sectors like finance. De Masi is optimistic that as more companies explore quantum applications, new use cases will emerge.
Furthermore, the field anticipates that continued development of algorithms and applications will unlock additional potential, reminiscent of the early evolution of semiconductor technology. Jan Goetz, CEO of IQM Quantum Computers, underlines this sense of an unfolding opportunity.
Recent research involving teams from Google and Oratomic has demonstrated a method that might produce exponential improvements in processing large data sets, marking the first evidence of genuine quantum advantage in machine learning. Bluvstein notes that such work points toward future transformative impacts on artificial intelligence.
Though practical quantum computers appear to be approaching feasibility, realizing their full promise, including revolutionizing AI and other fields, remains a distant goal. The industry is poised at a critical juncture, balancing excitement over progress with the recognition of significant technical and commercial challenges ahead.