Quantum computers remain several years away from full-scale production, but early adopters such as the Cleveland Clinic and Mitsubishi Chemical are already reaping benefits—especially when quantum technology is paired with artificial intelligence and high-performance computing. This hybrid approach is accelerating the timeline for real-world applications that were once considered years off.
Real progress in simulation
Dr. Lara Jehi, chief research information officer at Cleveland Clinic, highlighted dramatic improvements at a recent industry conference. In 2024, the largest quantum simulation achieved just ten atoms. Industry roadmaps predicted it would take five to seven years to surpass 10,000 atoms. Yet by mid-2025, the Cleveland Clinic had simulated protein complexes of up to 12,635 atoms—a feat impossible with classical methods alone.
“We would not have been able to do the same analysis classically,” Jehi noted. However, she cautioned that for clinically relevant applications, simulations need to reach around one million atoms. She expressed confidence that this milestone is one to two years away.
Hybrid AI-quantum approach
The breakthrough lies in combining quantum processors with AI running on classical computers. Simulating how a compound binds to a protein in real time is too complex for either AI or quantum alone. AI excels at identifying critical regions within large molecules, and quantum provides the extra accuracy needed for those fragments.
“We use classical computing up front to identify these highest tier fragments and then zoom in to those fragments with the higher resolution that quantum can provide,” Jehi explained.
Industry use cases emerge
Mitsubishi Chemical has been experimenting with quantum computing since 2018 for quantum chemical calculations and optimization problems. Dr. Qi Gao, a distinguished scientist at Mitsubishi Chemical, said the technology is ready for production. “We want to try to have it in production use by the end of this year, or maybe the beginning of next year,” he said. The first use cases involve designing advanced semiconductor materials for two-nanometer chips, which require energy resolution unattainable with classical computers.
Similarly, SoftBank Corp. is integrating quantum computers into its AI data center. The company connects customers to IBM and Quantinuum machines through its Riken-based facility, with 21 pilot projects underway. Nobushige Oguri, director of quantum business planning at SoftBank, emphasized that quantum will act as a new accelerator “to enhance current AI capability,” not replace it.
The growing quantum ecosystem
The transition from lab to market is supported by a maturing ecosystem. According to the Quantum Economic Development Consortium, there are now 556 pure-play quantum companies and over 7,000 quantum-engaged organizations. Revenue reached $1.9 billion in 2025 (up 30% from 2024), with $12.7 billion in new government funding commitments (up over 300%) and $4.9 billion in private venture capital (up nearly 200%).
Celia Merzbacher, executive director of the consortium, said, “We’re shifting from very fundamental and exploratory … to making things that are scalable.” The number of people actively advancing quantum hardware and software is growing rapidly.
Startups are filling specialized roles. Marta Estarellas, CEO of Qilimanjaro Quantum Tech, noted that quantum companies no longer need to build every component from scratch. “Players like ours don’t have to think about building the full stack and can delegate to third parties—and that really helps push forward the technology,” she said.
At the Quantum Tech World conference, over 1,300 attendees and more than 100 sponsors showcased the breadth of the field. Quantum Computing Inc. demonstrated a fraud detection algorithm that outperformed classical methods and scaled linearly rather than quadratically. Classiq, an orchestration software company, reported surging interest from non-scientists building quantum applications.
Looking ahead
Experts agree on a timeline: 2028 and 2029 will be pivotal years for quantum computing. “Every company is looking at 2028, 2029, or 2030,” said Gao. SoftBank’s Oguri echoed that sentiment, noting that hybrid AI-quantum use will drive adoption.
Quantum processors are specialized devices, good only for certain tasks. “They’re really bad at doing basic math,” said Juliette Peyronnet, U.S. general manager at Alice & Bob. Instead, they will complement CPUs and GPUs, handling challenges traditional computers cannot solve.
This pragmatic perspective underpins the current optimism. Rather than waiting for a standalone quantum revolution, enterprises are integrating quantum into existing workflows—and seeing results sooner than anticipated.
Source: Network World News