Executives from the biggest tech giants in the world have recently claimed that quantum computers will have commercial value in the next several years.

The CEO of IBM says that the company will show the real-world commercial impact of quantum by 2029, and the VP of quantum at Microsoft is “confident” that the company will have quantum machines in data centers that have commercial value by the end of the decade.

What’s more, McKinsey predicts that quantum technology will reach $2 trillion in economic value by 2035 in industries across finance, global energy and materials science, travel and transportation, logistics, pharmaceuticals, and aerospace and defense.

These are certainly exciting claims, but what does this mean for business leaders – whose expertise is not in quantum physics – that are trying to prepare their organizations for the impending impact of quantum technology?

As enterprises explore the opportunities in quantum computing, many find themselves stalled at the proof-of-concept (PoC) stage: unsure which applications to pursue, how far to take them, or how to implement them across each layer of the quantum computing stack.

Application discovery, algorithms, error correction, resource estimation, hardware execution, and classical components are all critical parts of the quantum computing stack, and leaders cannot evaluate a quantum use case at just one layer.

Why organizations need quantum application intelligence

While potentially useful for demonstrating quantum capabilities, select PoCs will not be enough to create meaningful business value, nor will vendor briefings or exploratory pilots give a leader an actionable plan for quantum adoption.

Quantum computing is a multilayer ecosystem evolving alongside hardware modalities, algorithm design, and application development frameworks, not a singular technology with a linear adoption curve. This requires organizations to become quantum application intelligent to enable informed decision-making that prepares employees and their workflows to apply quantum computing strategically.

This quantum application intelligence requires business leaders to have a dynamic and data-driven understanding of which quantum applications to build, when they’ll be valuable, and how to implement them. Such awareness helps enterprises decide where to start and allows them to model advancements and changes in the quantum stack over time, providing a systematic, reliable way to evaluate whether – and how – to build applications.

However, the quality of strategic readiness depends greatly on the quality of intelligence that is provided. For business leaders to make decisions that are not disadvantaged, the intelligence they use to make their decisions must cover the whole stack and maintain the following five principles.

1. The intelligence must be dynamic: A quantum strategy is only as good as the information that feeds it. Because of the rapid and constant evolution of quantum technologies across the stack, the intelligence that informs their decisions should be updated in real-time. Quantum industry reports updated even quarterly can become obsolete before the next decision cycle. If intelligence is not refreshed at least as often as decisions are made, organizations risk moving confidently in the wrong direction, investing resources, setting priorities, and making “progress” in areas that are already outdated. In a field where hardware advances, new algorithms emerge, and competitors’ research and development efforts can rapidly shift the viability of an application, static intelligence leaves businesses behind before they realize the landscape has changed.
2. The intelligence should be translatable across applications, capturing advances in one area that might impact another area relevant to your business model. For example, a breakthrough in quantum error correction for chemistry simulation may have direct implications for financial risk modeling, or an advance in optimization for logistics might reshape what is possible in drug discovery. Intelligence that does not translate across domains will fail to take advantage of knowledge that is already out there, leading to slower progress in the field that it is trying to track, along with giving competitors an opportunity to get ahead simply by being more aware of the latest developments.
3. Business leaders must have intelligence that is rigorous, meaning that it is not only accurate, but explainable, transparent, and verifiable. Critical elements like resource estimates and time to value must be well documented to justify continued investment or redirect valuable resources. These conditions can help quantum initiatives earn trust from boards, risk committees and executive leadership that might be wary of such nascent technology.
4. The intelligence must be holistic and complete across the entire stack and ecosystem. The scope of information that informs quantum application intelligence should draw from the global body of quantum research across all hardware modalities and algorithmic approaches. This also includes examining all possible applications, not just use cases that generate internal excitement. The most strategically valuable quantum application for an organization may not be the most glamorous or apparent one. Without this holistic view of both the ecosystem and potential use cases, organizations might miss key developments or use cases that could provide value.
5. Finally, the intelligence should reflect an agnostic view of the industry. The quantum hardware and software landscape is crowded and competitive, with many compelling yet unsure paths forward. To make reliable decisions, the intelligence that business leaders use must be objective and data-driven, without favoring a particular architecture or implementation model.

A plan based on the advantages of a superconducting quantum system may flounder when a better path to success for a particular application arises on an ion-trap quantum computer. Removing modality and methodology bias allows leaders to find the best avenue for their strategic goals.

The strategic implication of being quantum applications intelligent

The impact of quantum computing is inevitable, and business leaders must be thinking now about how their organizations are positioned to create commercial value.

The enterprises that will reap real value will not be the ones who spent the most on quantum exploration and PoCs, but rather those who built a disciplined approach to understand which quantum applications would most benefit their organizations, and an equally disciplined approach on how best to architect those applications in complex quantum implementations.

These organizations will have dynamic, translatable, rigorous, holistic, and agnostic intelligence on a portfolio of quantum applications that can drive business value and compete with, or even own, the market.

There are AI-powered quantum industry solutions available now that enable such intelligence by providing a deep, dynamic assessment of which applications to build, and when and how to build them, for non-quantum savvy business leaders and technology experts alike.

With quantum technology, disciplined intelligence is a strategic imperative for commercial success in this new era.