Key takeaways

• Quantum computing capability is advancing at a pace that makes early engagement essential
• Enterprises should treat quantum as an accelerator for specific problems, not a replacement stack
• Early value will emerge in chemistry, materials, energy and life sciences
• Cultural readiness and continuous learning matter more than hardware access
• Quantum opportunity and post-quantum security risk must be addressed together

As enterprises grapple with the computational limits of today’s systems, limits increasingly exposed by advanced AI workloads, the question is no longer whether quantum computing matters, but how and when organizations should begin preparing for it.

In this fireside chat, as part of HCLTech’s Davos Dialogues series, Abhay Chaturvedi, Corporate Vice President, Tech Industries at HCLTech, sat down with Nathan Baker, Partner for Quantum Applications at Microsoft, who underscored a central reality: quantum is not a distant abstraction. The pace of progress is accelerating, and the window for thoughtful preparation is already open.

The pace of change is no longer theoretical

The speed at which quantum computing is advancing has increased dramatically. “It used to be you would check in on the literature and find out what the latest was in quantum, and you'd be okay if you did that every month or so,” said Baker. “Now if you don't do it once or twice a week, you miss out.”

That acceleration is visible in the progress of logical qubits (error-corrected units of quantum computation, designed to be stable and reliable enough to run meaningful calculations, unlike raw physical qubits, which are highly prone to noise). A few years ago, there were none capable of detecting and correcting errors. Then came four. Then twelve. Then twenty-eight. “Now,” said Baker, “we're working with Denmark and QuNorth, and we'll be launching a machine with 50 logical qubits.”

For enterprises, the implication is significant. Progress is no longer following a slow, linear research curve. Capability is compounding and organizations waiting for a single arrival moment risk missing the learning curve entirely.

Quantum is not a replacement: It’s an accelerator

A recurring clarification throughout the discussion concerned what quantum computing is not. It is neither a wholesale replacement for classical systems nor a general-purpose computer waiting in the wings.

“Quantum’s an accelerator,” said Baker. “[In the same way as you] bring in a GPU, you bring in quantum for specific kinds of calculations.”

In practice, quantum computing will sit alongside existing stacks, like AI, high-performance computing and classical simulation, and plugged into workflows where it adds unique value. The challenge for enterprises lies in learning which problems fall into that category.

This is why preparation matters more than near-term deployment. “The time to start thinking about it is absolutely now,” said Baker, pointing to governments already investing in quantum education and workforce development. “It’s not too soon to start that journey.”

Where quantum will matter first and why

Some industries are naturally positioned to benefit earlier than others. “I’m a chemist, so I am biased towards chemistry,” said Baker, before referencing Richard Feynman’s observation that nature itself operates on quantum principles.

Problems rooted in quantum mechanics, including electrons, molecular bonds and material behavior, remain difficult for classical systems to model with precision.

“Chemistry, material science, the way drugs interact with proteins, the way proteins influence metabolism and processes in the body…all of those are fundamentally quantum mechanical problems,” said Baker. Current approaches rely on approximations. Quantum computing adds “that extra layer of accuracy.”

In practical terms, this enables more reliable predictions: how a drug will behave in the body, how a material will perform in a battery or how molecular interactions influence disease. “Quantum computing gives businesses the ability to look, perform a calculation and have a first-time right type of prediction,” he said.

While pharmaceuticals, energy and materials may see earlier impact, these capabilities are not confined to a single sector as the technology matures.

Culture, not hardware, is the real constraint

Technological progress alone is not enough. Transformational tools require organizations to change how they learn and adapt.

A growth mindset remains central. Constant learning and ongoing education as the field evolves is important.

The challenge is the speed of change. “The things you knew last week may be different this week,” he noted. Capabilities once thought to be years away are becoming viable in much shorter timeframes.

To be ready for quantum, organizations need to remain agile and continuously reassess which problems quantum can address, where it fits into existing workflows and when it is ready to be applied.

Opportunity and risk arrive together

Quantum computing presents both upside and exposure.

“The pace of growth in quantum computing capabilities is so rapid,” said Baker. “It is time for every business to be thinking about how this relates to the problems I care about and to the value I deliver to customers.”

At the same time, those advances affect security. “Quantum computing’s capabilities for cryptanalysis [the process of analyzing information systems in order to understand hidden aspects of the systems], for breaking public key encryption, are also becoming increasingly real,” he said.

In this context, preparation is not optional. Enterprises must pursue quantum-enabled opportunities while also planning for a post-quantum security environment. “It is time for everyone to start to make the transition to quantum-safe technologies,” said Baker.

Skills, literacy and cutting through the hype

As the discussion turned to talent and education, the emphasis shifted away from deep specialization toward practical understanding.

“I’m not telling anyone to go out and make sure they have a PhD in physics,” said Baker. “It’s not required.”

What matters instead is literacy, including understanding what quantum can and cannot do, and judgment. “With any new technology, there tends to be a lot of hype,” he said. “Having the literacy and the judgment skills to cut through the hype…is really important.”

Quantum computing will reward informed curiosity and disciplined integration, not blind enthusiasm.

FAQs

Is quantum computing ready for enterprise use today?
Not broadly, but progress is rapid enough that enterprises should begin learning, mapping use cases and building readiness now rather than waiting for full maturity.

Will quantum replace classical computing or AI?
No. Quantum will act as a specialized co-processor, used alongside classical systems and AI for specific, high-value calculations.

Which industries should pay attention first?
Industries rooted in chemistry and materials, such as pharma, energy and advanced manufacturing, are likely to see earlier impact.

Why is culture so important for quantum adoption?
As capabilities evolve quickly, organizations need a learning mindset to continuously reassess where quantum fits and when it is ready to use.

What skills matter most for the quantum future?
Literacy and judgment. Understanding realistic capabilities and cutting through hype matters more than deep physics expertise for most roles.