Quantum computers remain two to five years away from full-scale production, but early adopters such as the Cleveland Clinic and Mitsubishi Chemical are already demonstrating real-world benefits, particularly when quantum technology is used in tandem with artificial intelligence (AI) and high-performance computing (HPC). This hybrid approach is accelerating the path to practical quantum advantage, as experts discussed at the recent Quantum Tech World conference in Boston.
Quantum and AI: A powerful partnership
“We are starting to see real applications of it,” said Lara Jehi, chief research information officer at Cleveland Clinic and a keynote speaker at the conference. The technology is moving faster than many anticipated. In fall 2024, the largest simulation quantum computers could handle was just ten atoms. Industry roadmaps predicted it would take five to seven years to break the 10,000-atom barrier. Yet this year, Cleveland Clinic successfully simulated protein complexes comprising up to 12,635 atoms. “We would not have been able to do the same analysis classically,” Jehi noted.
While that scale is still too small for clinical relevance—a million atoms would be needed for truly impactful drug discovery—Jehi is confident that milestone is only one or two years away. Even today, combining quantum computing with AI running on classical hardware enables tasks that neither could handle alone. For example, simulating a compound’s binding affinity to a protein in real time is too complex for either system. But AI can first identify critical regions of a molecule where higher precision is necessary, then quantum computers zoom in on those fragments for more accurate simulations. This division of labor maximizes the strengths of each technology.
Industrial applications on the horizon
Mitsubishi Chemical has been experimenting with quantum computing since 2018, focusing on quantum chemical calculations and optimization problems. The company now plans to deploy the technology in production by end of 2026 or early 2027. “We want to try to have it in production use by the end of this year, or maybe the beginning of next year,” said Qi Gao, distinguished scientist at the Mitsubishi Chemical Corporation Science and Innovation Center. The first use cases involve designing advanced semiconductor materials for two-nanometer chips, where classical simulations cannot achieve the required energy resolution. “So we have to use quantum computers,” Gao explained. The simulation of metal oxide—a photo-resistant material used in chip etching—will take a couple of years to develop fully, but the industry is moving steadily toward practical business use. “Every company is looking at 2028, 2029, or 2030. We think 2028 and 2029 will be very important years in quantum computing,” he added.
SoftBank Corp. is targeting a similar commercialization timeline. The company connects customers to IBM and Quantinuum quantum machines through its AI data center, currently hosting 21 pilot projects. “Within our AI data center, we have already built the supercomputer level,” said Nobushige Oguri, director of the quantum business planning department. “It's a world-class supercomputer, but it's just set up for processing AI. The quantum computer will be the new accelerator to enhance current AI capability.” This hybrid approach—quantum as a specialized accelerator—is expected to drive adoption without replacing existing infrastructure.
The maturing quantum ecosystem
Another sign of quantum computing’s transition from research labs to real-world deployment is the emergence of a full-fledged ecosystem. Hardware makers, software providers, consulting firms, and component suppliers are filling gaps that previously forced quantum companies to build everything from scratch. “I've been 15 years in this field, as a researcher and now as a CEO, and it's been changing dramatically and accelerating very fast,” said Marta Estarellas, CEO of Qilimanjaro Quantum Tech, a Spanish superconducting qubit company. “Now what you see are a lot of spinoffs and startups starting to build different layers of the supply chain. That really helps push forward the technology.”
The Quantum Tech World conference itself showcased this ecosystem. Over 1,300 attendees and more than 100 sponsors were present, including multiple quantum computer makers. Quantum Computing Inc., a maker of room-temperature photonic computers, ran a live demo of a fraud detection algorithm that outperformed classical approaches and scaled linearly with dataset size rather than quadratically. Also present were software companies like Classiq, which provides an abstraction layer that simplifies quantum application development for non-scientists. “Our booth has been packed,” said Jason Silbergleit, head of Americas at Classiq. “Even in the past six months—three months—the amount of acceleration and interest is growing.”
Investment and government support surge
The momentum is apparent in investment and policy. According to a report released in April by the Quantum Economic Development Consortium, there are now 556 pure-play quantum companies and over 7,000 “quantum-engaged” organizations. The quantum industry generated $1.9 billion in revenues in 2025, up 30% from the previous year. New government funding commitments reached $12.7 billion in 2025, a more than 300% increase from 2024, while private venture capital investments hit $4.9 billion, up nearly 200% year over year. “And the number of people who are really rolling up their sleeves and doing the work that needs to be done to advance the hardware and the software—I think there's just a momentum that is quite visible,” said Celia Merzbacher, executive director of the consortium.
This influx of capital and talent is driving improvements in quantum hardware, error correction, and software tooling. While fault-tolerant quantum computers are still years away, current noisy intermediate-scale quantum (NISQ) devices are already proving useful when combined with classical resources. The hybrid AI-quantum paradigm is becoming the standard approach for early adopters, as it leverages the strengths of both technologies without demanding full-scale quantum advantage.
Practical uses today and tomorrow
In healthcare, Cleveland Clinic’s protein simulations are paving the way for more accurate drug design. In materials science, Mitsubishi Chemical is tackling problems that classical computers cannot solve, such as simulating the electronic structure of advanced chip materials. In finance, quantum algorithms for fraud detection and portfolio optimization are being tested. SoftBank’s pilot projects span logistics, cryptography, and molecular discovery. The key insight from these early users is that quantum processors are not general-purpose machines; they are specialized accelerators best suited for specific high-complexity tasks.
Juliette Peyronnet, U.S. general manager at Alice & Bob, emphasized this point: “Quantum processing units are very specialized devices. They can't solve your everyday problems. They're really bad at doing basic math.” Just as CPUs handle general computing and GPUs excel at AI workloads, quantum processors will be reserved for the most intractable challenges. “We know that quantum computers are not going to work in isolation,” she said.
As the ecosystem matures and investment continues to flow, the convergence of AI and quantum computing is accelerating the timeline to practical usefulness. Early adopters are already reaping benefits, and the next few years promise to bring scalable, commercially viable quantum solutions into industries ranging from pharmaceuticals to semiconductors.
Source:Network World News