Guest Post by Dr. Kristin Milchanowski, Chief AI and Data Officer, BMO Financial Group
Quantum Advantage: A Milestone to Celebrate and Strategically Interpret
Quantum advantage, the moment when quantum and classical methods combined surpass classical-only approaches on practical tasks, has recently been claimed. Google’s Quantum Echoes experiment demonstrated a verifiable quantum speedup for a specific, narrowly defined problem, calculating Out-of-Time-Order Correlators (OTOC) on a 105-qubit device, achieving results 13,000× faster than the best classical supercomputers. Unlike Google’s previous claims, this result is both repeatable and stable, and a clear indicator of hardware and software progress.
However, no single experiment has yet demonstrated quantum advantage at both scale and industrial relevance. So how should we think about this?
Beyond the Breakthrough: An Industry Perspective on Quantum Advantage
Transformative technologies often show their true impact only in hindsight, once deeply rooted in industry workflows. In other words, we may not fully comprehend the significance of quantum advantage as it happens, but only through what it ultimately enables as we look back.
As Google’s result illustrates, early demonstrations will likely focus on problems that are computationally challenging yet structurally manageable, ideal for showcasing progress but not yet representative of the complexity found in workflows at production scale. Scaling quantum solutions will require more than clever problem selection, especially in regulated sectors like finance. It will demand fault-tolerant hardware, robust algorithms, and orchestration layers that integrate quantum capabilities into compliance-bound workflows.
We suggest a boardroom definition of quantum advantage that is twofold: (1) a quantum algorithm delivers end-to-end utility and relevance for a business outcome at scale, and (2) it outperforms the best classical algorithms available for the same task. Meeting these criteria would be a truly monumental achievement in quantum computing, signaling distinct business value and clear market relevance. Yet, quantum advantage should not be seen as a singular event. The real opportunity lies in a series of evolving milestones, each expanding what quantum computers can achieve. Ultimately, true validation will come as industries and research ecosystems integrate quantum computing to deliver high-value outcomes for real-world challenges.
These breakthroughs are signals, not endpoints, to build capacity, talent, and strategic clarity. The time to prepare is not when quantum advantage becomes mainstream, it is now.
From Signal to Strategy: Cultivating Internal Fluency and Strategic Alignment
The journey toward quantum readiness begins not with hardware or code, but with shared understanding of the technology, its limitations and its opportunities.
Emerging technologies often outpace institutional readiness; quantum computing will be no exception. As new breakthroughs emerge, organizations must discern their relevance, calibrate responses, and identify promising early investments.
This is why fluency in quantum concepts must be prioritized.
Leaders across business, technology, risk, compliance, and strategy functions need to cultivate a unified language and conceptual framework to grasp quantum computing’s potential and align their efforts effectively. Without this foundation, experimentation risks becoming fragmented, producing activity without driving cohesive progress.
This is not about turning every executive into a quantum physicist; it is about nurturing quantum literacy across the organization.
Strategic communication must foster clarity, alignment, and cross-functional momentum. Dialogue should center around key questions: what problem are we solving? Where can quantum computing provide a meaningful advantage? How does this initiative align with broader organizational goals?
Framing discussions around these questions ensures focus, relevance, and responsible innovation.
For example, at BMO we are exploring quantum enhanced innovations to optimize investment portfolios and deepen risk management insights. These efforts go beyond isolated pilots; they are part of a broader initiative to integrate quantum computing into the core of our innovation strategy.
Ultimately, before quantum capabilities can be fully operationalized, organizations must cultivate the fluency to think strategically about what quantum computing truly means for their business.
From Concept to Capability: Strategic Experimentation as a Long-Term Imperative
This is where quantum computing becomes operationally relevant.
History shows that breakthroughs do not become transformational in isolation. They gain momentum through convergence with other technologies. Just as graphics processing units (GPUs) evolved from visual rendering tools into accelerators of artificial intelligence (AI), quantum processors will likely gain value through integration with classical systems. This will include architectures where quantum processing units, GPUs, and central processing units (CPUs) each contribute to solving different parts of a problem.
Strategic experimentation allows institutions to begin exploring that future today. Well designed pilots can answer meaningful questions, such as: Can quantum-classical algorithms improve portfolio optimization under complex constraints? Can quantum methods help simulate non-linear financial risk in ways that classical models cannot?
These experiments are not about immediate payoff. They are learning milestones that reveal where quantum fits in a workflow, what it takes to implement, and how to scale solutions when fault-tolerant hardware arrives. Early experimentation helps organizations separate signal from noise and act decisively as the quantum ecosystem matures.
Readiness in Practice: A Playbook for Enterprise Adoption
Strategic experimentation generates insight. However, readiness requires deliberate execution. Organizations can take clear, practical steps today to prepare for quantum computing’s evolving role, without waiting for a specific tipping point or regulatory requirement.
A practical playbook might include:
- Starting strategic conversations at the top: Engage boards, executives, and technical leaders to clarify why quantum matters, identify potential applications, and define success metrics.
- Understanding quantum’s strengths and limitations: Examine workflows, focusing quantum on the steps it can realistically address and could be implemented in infrastructure. For example, consider applications that don’t need real-time answers.
- Identifying research projects that address real-world challenges: Prioritize research that adds incremental value and can be benchmarked against existing solutions. Think of this as your “pilot light” guiding steady progress.
- Designing experiments for learning and building internal fluency: Keep pilot projects focused and inclusive, while building cross-functional learning programs that equip your organization to transform experimentation into operational capability.
- Engaging with current platforms and evolving technology roadmaps: Use cloud-based quantum access to build prototypes and gain experience, well ahead of fault-tolerant hardware. In parallel, update roadmaps to support hybrid quantum–classical architectures.
None of these actions require moonshot investments. Readiness is a deliberate process of cultivating capability through experimentation, aligned with strategic priorities.
Institutions that build foundational capacity today will be well positioned to lead when scalable applications emerge. Furthermore, lessons learned now may be what set leaders apart when the next breakthrough arrives.
Leading the Shift Before More Headlines Arrive
As more claims of quantum advantage increasingly become headlines, quantum computing’s most significant applications will likely already be underway.
This dynamic is familiar.
The rapid emergence of generative AI caught many off guard. Although foundational research spanned years, the sudden breakthroughs triggered a scramble to find use cases, often in organizational silos and without the fluency to deploy effectively. The result was a patchwork of underwhelming initiatives that did not scale across organizations. As an MIT study recently reported, 95% of generative AI pilots are failing.
Quantum computing may follow a familiar arc. As with previous waves of innovation, those waiting for external clarity risk becoming reactive participants in a momentum they didn’t help shape. In contrast, those who engage early are positioned to influence how the technology evolves and how it’s adopted across sectors. This is not just a technical decision, it’s a strategic one. The opportunity cost of inaction is real, and the potential rewards for early investment in fluency, experimentation, and alignment may be substantial.
Call to Action:
This is not an invitation to speculative gambles but a call to deliberate intention:
- Identify high-value challenges worth exploring.
- Build fluency across stakeholders and business units.
- Connect domain experts and technologists.
- Foster a culture of purposeful experimentation.
Quantum advantage is not a destination but a waypoint, an early signal of a broader transformation underway. Institutions that begin their journey today will not only benefit from quantum computing’s arrival, but they will also help define what strategic advantage looks like in a post-quantum world.
The time to prepare isn’t tomorrow, it’s today. Those who begin now will shape the path others will inevitably follow.
Dr. Kristin Milchanowski is Chief AI and Data Officer at BMO Financial Group.
The views expressed in this article are the writer’s own.
