Among today’s emerging technologies, only agentic AI rivals quantum computing in the hype and promises surrounding its enterprise impact. While significant research on quantum computing continues, there are opportunities to learn about and pilot quantum computing today.

It took 20 years to go from primitive virtual machines bought on credit cards to the over $900 billion cloud computing industry we see today. Experts present a similar timeline for quantum computing and suggest that more enterprises need to invest in developing skills, reviewing business opportunities, and preparing for security challenges. Bain estimates the market potential for quantum computing at between $100 billion and $250 billion, with top applications in machine learning, logistics network optimization, and drug discovery.

Quantum computing infrastructure today

You can experiment with quantum computing today on noisy intermediate-scale quantum (NISQ) hardware. These devices are noisy, with quantum computations that are error-prone, so pilot projects are often hybrid, pairing quantum and classical computation. Their scale is limited to 50–1,000 physical qubits, the basic unit of information used to encode data in quantum computing. The largest quantum computer today is 1,121 qubits.

“While quantum isn’t yet suited for everyday enterprise workloads, organizations can already access quantum systems in the cloud to explore optimization, simulation, and modelling use cases, particularly in sectors such as healthcare, energy, and advanced research,” says Ben McCarthy, lead cybersecurity engineer at Immersive. “These early efforts help teams understand where quantum may eventually deliver value and how it fits into existing operating models.”

There are several options to experiment with quantum computing today.

• Amazon Braket,  Azure Quantum, and IBM Quantum Platform are three broad, multi‑purpose quantum computing-as-a-service (QCaaS) providers. They offer significant optimization capabilities, expose multiple hardware back ends, and blend quantum steps with regular computing.
• Specialists like D‑Wave’s Leap and Zapata Orquestra focus on optimization-heavy workloads, such as computing delivery routes, crew schedules, or a mix of financial investments at massive scale.
• Hardware vendors such as IonQ, Rigetti, and QuEra plug into quantum computing ecosystems to give enterprises practical, cloud-based access to different qubit technologies.
• Hands-on learning opportunities are available from Amazon, Immersive, QuLearnLabs, and The New School. Learning opportunities are also available from CERN, IBM, MIT, Quantum Learning Lab, and other online courses, certifications, and university programs.

“The potential of quantum computing is demonstrated by ongoing progress from top companies and research organizations,” says Dia Ali, global platforms and solutions lead for data intelligence at Hitachi Vantara. “These advancements indicate a slow but significant progression in computational methods, even though quantum computing has not yet achieved widespread use.”

Speakers on the “Coffee With Digital Trailblazers” podcast episode “Demystifying Quantum Computing” offered pragmatic views on opportunities during the next three years, including how companies can commercialize quantum computing. Some will lead to learning pilots, but discovery efforts should also capture the intractable use cases that today’s CPUs and GPUs cannot solve easily.

Use cases for different industries

Although you can try QCaaS inexpensively, a discovery-phase pilot can be costly. One estimate budgeted $150,000 to $450,000, requiring two or three experts working for three to six months, followed by two longer, more expensive development phases. 

These costs shouldn’t scare large enterprises, but it’s important to research the right use cases.

“The right move now is to identify where quantum could eventually create real business impact, understand how those use cases would change existing workflows, and closely track progress from quantum hardware and software providers,” says Kevin Hilscher, senior director of product management, post-quantum cryptography and device trust at DigiCert. “For example, life sciences companies are already exploring how quantum could accelerate molecular modeling and drug discovery, while financial institutions are assessing its potential for risk modeling and optimization. Organizations that start this groundwork now will be far better positioned to move quickly as commercial quantum capabilities emerge.”

Ali of Hitachi Vantara adds, “Molecular research, financial analysis, and optimization issues are just a few of the complex situations that quantum computing can address.” Some examples of quantum computing pilots include:

• HSBC simulated different models to predict bond trading prices and found that quantum computing outperformed classical models by as much as 34%.
• DHL’s pilot of a quantum‑driven vehicle routing algorithm for deliveries in congested cities could reduce driven miles by up to 10%.
• Molecular research examples include predicting whether drug molecules stay stable and bind as intended, mapping 3D shapes of small RNA strands, and modeling how potential cancer drugs interact with their targets.

While quantum technologies have the potential to revolutionize business, these pilots are not straightforward. Jordan Kenyon, senior quantum scientist at Booz Allen, suggests, “A technology’s efficacy has as much to do with its implementation as its intrinsic capacity. Actually delivering mission impact with quantum requires a cadre of technologists and mission experts working together to identify where and when these novel approaches merit further investment.”

Preparing for the security impacts

Security is a major concern, as the same computational capabilities that quantum has for studying molecular interactions are also being applied to data encryption. Transitioning to post-quantum cryptography (PQC) will require significant implementation before Q-Day, when quantum computers will be able to break existing cryptographic algorithms. The transition may be more complex and expensive than fixing the Y2K bugs back in the late 1990s, which was estimated at $300 billion to $600 billion. 

Arjun Kudinoor, quantum security advisor at Protegrity, PhD student, and NSF graduate research fellow at the MIT Center for Theoretical Physics, says, “For enterprises today, the most important step is not adopting quantum hardware, but upgrading public-key infrastructure to PQC. While quantum attacks that can break large-key encryption like RSA-2048 are not yet feasible, data encrypted now may be vulnerable in the future.”

Jimmy Mesta, cofounder and CTO of RAD Security, says attackers are already stealing encrypted data, betting they can decrypt it later with quantum computing. “Enterprises should start identifying long-lived secrets like customer PII, sensitive IP, and authentication keys, and prepare them for PQC. Defenders don’t know when quantum computing will break encryption, but we do need to be prepared for when it does,” says Mesta.

Getting started

The first place leaders, engineers, and developers should start is by learning more about quantum computing opportunities, infrastructure, development approaches, and security risks.

There is a significant talent gap that should concern enterprise leaders, and it is an opportunity for engineers seeking new, highly employable skills. McKinsey’s research found that in 2025, there was only one qualified quantum candidate for every three job openings and predicted that fewer than half of quantum jobs would be filled that year. In the 2025 ISC2 Cybersecurity Workforce Study, quantum computing ranked last among the top needed skills, with only a 17% response rate.

“For most enterprises, quantum computing today is about learning and preparation rather than running meaningful workloads at scale,” says Jon France, CISO at ISC2. “The practical move is to experiment through cloud-based quantum services and start understanding how these systems could eventually integrate with existing IT environments, while building the skills and security mindset needed for the future. Organizations that treat this as a measured, hands-on learning phase now will be far better prepared when quantum capabilities start delivering real business value.”

Organizations are already investing heavily in AI, including AI agents, vibe coding, employee pilots, and leadership learning. IT leaders may need to approach the investment in quantum computing from two perspectives: the urgency around security and the opportunity to invest in research and development. 

“Our understanding of what is possible with quantum computing continues to evolve alongside advances in hardware, error mitigation, and theory,” says Bill Wisotsky, principal quantum systems architect at SAS Research and Development. Organizations can take meaningful action today by developing the intellectual property that will matter when quantum computing technology arrives. By building strong portfolios of patents, publications, and technical expertise now, they will be better positioned once quantum computing reaches maturity.”

Quantum computing is generating significant hype, but it’s not without merit. For engineers, quantum computing offers the opportunity to learn high-demand skills in security, data engineering, and computing areas. For enterprises, the opportunity is to identify where and how solving massive computational challenges paves the way for new business opportunities and efficiencies. And all businesses need to be prepared for Q-Day.