At Q2B 2025, Matt Langione, a partner at Boston Consulting Group, delivered a talk that challenged conventional thinking about how quantum computing will reach commercial viability. His core argument: the companies that will capture the lion's share of quantum's value aren't waiting for the technology to mature—they're actively shaping it.

For those of us working to bring quantum computing into production environments, his message resonates deeply. Here's what stood out, and why it matters for organizations considering their quantum strategy today.

The Demand-Side Thesis

Langione opened with a striking observation about innovation over the past two decades. The MAG-7 tech giants—companies like Apple, Microsoft, NVIDIA, and Google—have grown from roughly 16% of market cap in 2015 to nearly 50% today. This represents extraordinary supply-side innovation, but it also means the benefits of new technology have concentrated in a remarkably small number of companies.

Quantum computing, Langione argues, offers an opportunity to change that pattern.

"We think quantum is an opportunity to see broader participation," he said. "We're seeing some early signals."

The implications are significant. In industries where classical computational approaches have stalled—drug discovery, materials science, financial modeling—quantum offers a path forward. But capturing that value requires something most enterprises haven't done before: participating directly in technology development rather than waiting for off-the-shelf solutions.

The Tesla-Panasonic Model

Langione illustrated demand-side innovation with a concrete example: Tesla's 2014 partnership with Panasonic on battery development. The two companies invested billions, placed teams side-by-side on production lines, and shared risk at early technology readiness levels.

The result? Battery costs dropped by a factor of 11 over ten years, enabling mass EV adoption.

What made this work wasn't just capital. It was data-rich feedback loops—Tesla had the mission-critical data to specify exactly what battery performance meant for their vehicles—and shared risk at the pre-commercial stage.

Quantum computing, Langione suggests, is ripe for the same approach.

QuEra's perspective: This is precisely why we built our algorithm co-design program. The problems that matter most to enterprises—molecular simulation for drug discovery, logistics optimization, portfolio risk modeling—aren't generic. They require translating domain-specific constraints into quantum-native formulations. That translation happens best when hardware teams and domain experts work side-by-side, not when one delivers a finished product to the other.

Our work with Los Alamos National Laboratory on nuclear dynamics, with Merck and Amgen on small-data drug discovery, and with Cinfo on telecommunications network optimization all follow this model. The algorithms that emerged weren't off-the-shelf. They were purpose-built for the physics of neutral-atom systems and the specifics of each customer's problem.

Moving the Dots, Not Just Improving the Hardware

One of Langione's most useful framings involved IBM's resource estimation visuals. Think of quantum algorithms as dots on a chart, defined by circuit width (how many qubits) and depth (how many operations). A pure supply-side view says hardware improves until all dots are reachable.

But there's another approach: move the dots.

"You also move the dots—by optimizing algorithms and tying them to real business problems," Langione explained.

This is where demand-side engagement becomes essential. Problem specification turns out to be hard. It requires deeply cross-functional teams—what Langione calls a "two-in-a-box" model—where industry domain expertise meets quantum algorithm development.

QuEra's perspective: Neutral-atom systems offer unique advantages for this kind of co-optimization. Our Field-Programmable Qubit Arrays allow the hardware geometry itself to be adapted to problem structure. A graph optimization problem can be mapped directly onto the physical atom layout. This isn't possible with fixed-topology architectures.

When BCG X joined the QuEra Quantum Alliance in September 2025, we framed the partnership around exactly this idea. As Jean-François Bobier, Partner and VP at BCG X's AI Science Institute, put it: "Leaders don't need hype, they need problem-first roadmaps and the means to test them quickly."

Winner-Take-Most Dynamics

Langione delivered a sobering projection: in IP-driven industries, roughly 90% of quantum's value may accrue to the first 10% of adopters.

The reasons are structural. Algorithm talent is scarce. Compute access may be limited. Quantum solutions are custom and take time to develop—the IBM-HSBC collaboration announced in 2025, Langione noted, was the result of at least five years of work.

"That's indicative of what meaningful innovation requires," he said.

This creates urgency for organizations that haven't yet started. The question isn't whether quantum will deliver value—BCG projects $450 to $850 billion across simulation, optimization, machine learning, and cryptography. The question is who will be positioned to capture it.

QuEra's perspective: We've been explicit about this in our messaging: the transition from "one day" to "Day One" requires engagement now, not later. The companies working with us today—through co-design engagements, Premium Cloud Access, or on-premises deployments like AIST Japan—are building institutional knowledge and IP that will compound over time.

The five-year timeline Langione mentioned for IBM-HSBC matches what we see in serious enterprise engagements. That's not a reason to delay. It's a reason to start.

The Market Today: $440 Million and Growing

Langione shared BCG's current market sizing: approximately $440 million at the end of 2024, with enterprise spending exceeding academia and government—rare for deep tech at this stage.

Cloud hardware access is the largest category, but algorithm co-development is growing. BCG identified roughly 150 active quantum proof-of-concepts at year-end 2024, up 50% from 2022, even during a period when AI dominated enterprise attention.

Looking to 2029, Langione projected $2.5 to $5 billion in the most likely scenario, with upside potential to $10 billion or more depending on error correction progress and end-user engagement.

QuEra's perspective: The growth in co-development spending validates what we're seeing in customer conversations. The organizations that have moved past "quantum exploration" into structured engagements are the ones asking the most sophisticated questions—not "what can quantum do?" but "how do we map our specific optimization problem onto your hardware, and what's the path to production?"

That's a fundamentally different conversation, and it's happening more frequently.

What This Means for Your Organization

Langione's talk was a call to action for end users. Bending the curve forward to quantum advantage isn't just the job of hardware providers. It requires capital, time, and data from industry.

For organizations evaluating their quantum strategy, a few questions are worth considering:

Do you have problems that have hit classical computational limits? Drug discovery costs doubling every nine years. 20-year materials translation cycles. Portfolio optimization constraints that force approximations. If your industry has stalled on computationally hard problems, quantum may offer a path forward—but only if you engage early enough to shape the solutions.

Are you prepared for a multi-year commitment? The IBM-HSBC timeline Langione cited isn't an outlier. Meaningful quantum engagements require sustained investment and iteration. The organizations capturing value aren't running one-off experiments; they're building programs.

Can you provide the data-rich feedback loops that make co-development work? The Tesla-Panasonic model succeeded because Tesla knew exactly what battery performance meant for their vehicles. Quantum co-design works the same way. The domain expertise has to come from your side.

The Bottom Line

Matt Langione's message at Q2B was clear: quantum computing's timeline to advantage isn't fixed. It can be bent forward by the enterprises willing to engage in demand-side innovation.

For QuEra, this thesis aligns with everything we've built—from our co-design program to our BCG X partnership to our on-premises deployments that put quantum hardware directly into customer environments.

The question for industry leaders isn't whether quantum will matter. It's whether you'll be among the early adopters who capture 90% of the value, or among those who wait and wonder what happened.

QuEra Computing is a founding member of the QuEra Quantum Alliance, which includes BCG X among its strategic partners. For more information on algorithm co-design engagements, visit quera.com/co-design.

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