Insider Brief
- Quantum computing is moving from theory to strategic planning in the energy sector as rising compute demand, driven by AI, forces companies to evaluate new technologies alongside existing systems.
- Early quantum systems are being tested for applications such as grid optimization, materials discovery and energy system modeling, with most near-term use expected to be hybrid with classical and AI computing.
- Deployment challenges, including specialized infrastructure, workforce gaps and cybersecurity risks, mean large-scale commercial impact is still years away, but preparation is increasingly viewed as urgent.
Quantum computing is shifting from a theoretical pursuit to a strategic priority for the energy sector as rising demand for compute power reshapes infrastructure, policy and investment decisions, according to a new report from S&P Global Energy.
The report, authored by analysts at S&P Global’s 451 Research unit, portrays quantum technologies as entering a phase of “evaluation” rather than speculation, with early deployments, commercial pilots and growing enterprise interest signaling a transition toward practical use.
This emergence comes as energy systems become more dependent on computation, driven largely by artificial intelligence, which is pushing data center power demand sharply higher and exposing the limits of classical computing.
From Lab Concept to Strategic Tool
Quantum computing is no longer confined to academic research or science fiction, according to the report. Systems are now being deployed in data centers, accessed via cloud platforms and tested on real-world problems.
“Quantum computing is not yet a broad commercial platform, but it is no longer theoretical,” Atul Arya, senior vice president and chief energy strategist at S&P Global, writes in the report. “It has emerged as a strategic
imperative for the energy sector.”
Unlike traditional computers that process information as binary bits — 0s and 1s — quantum computers uses the principals of quantum mechanics to explore many possible solutions, theoretically all at once. This power makes them particularly suited for complex problems involving optimization, simulation and modeling.
For the energy sector, those problems are central, the analysts suggest. Classical systems, even at large scale, struggle with tasks such as modeling chemical reactions, optimizing grid operations under uncertainty or simulating complex physical systems.
The report identifies quantum computing as part of a broader “compute continuum” alongside AI and high-performance computing, rather than a replacement. Early use is expected to be targeted and complementary.
Potential applications include advanced materials discovery for batteries and catalysts, optimization of power grids and supply chains, carbon capture chemistry and nuclear system design.
Quantum Momentum Builds
The past year has marked a turning point for the quantum technology industry, with investment accelerating and governments expanding national strategies.
S&P Global estimates that global investment in quantum technologies surpassed $55 billion in 2025, while market revenue is projected to rise from roughly $2.5 billion in 2025 to nearly $9 billion in 2026.
Enterprise expectations are also shifting. According to a 451 Research survey cited in the report, 76% of respondents believe quantum computing will begin delivering material value within five years.
“2025 ignited interest. 2026 is triggering change,” the analysts wrote.
Industry activity is broadening beyond startups to include large technology companies, cloud providers and national laboratories. Vendors now span hardware developers, software firms, cloud platforms and systems integrators, reflecting a maturing ecosystem.
Early use cases are already being tested. The report highlights work by Oak Ridge National Laboratory and IonQ on power grid optimization as an example of how current systems are being applied to energy challenges.
At the same time, the convergence of quantum computing and artificial intelligence is emerging as a focal point. Organizations are exploring quantum-enhanced machine learning and AI acceleration as leading applications.
This year, the analysts suggest industry activity continues to rev up.
“Only a few months into 2026, the quantum computing industry has been catalyzed: M&A activity is surging, investment continues to grow, governments around the world are accelerating their commitment to quantum technology, and deployment and commercial conversations are increasingly supplanting hypotheticals,” the analysts write.
Infrastructure Focus
As quantum systems move toward wider deployment, the report emphasizes that infrastructure — particularly data centers — will need to evolve.
Quantum computers differ fundamentally from classical systems in their physical requirements. Some rely on cryogenic cooling near absolute zero, while others use lasers, photonics or electromagnetic fields. These differences complicate integration into existing facilities.
“Quantum systems can vary substantially in size, weight, form factor, energy use, cooling requirements, environmental conditions, connection and port locations, and network connectivity requirements,” the analysts write. “There is no set standard for quantum system construction, making every quantum computing deployment an exercise in custom construction.”
Deployment environments vary widely, as well. Systems are currently located in universities, national labs and cloud-accessible facilities, with some on-premises installations emerging. Different hardware approaches — including superconducting, trapped-ion, photonic and neutral atom systems — each come with distinct requirements for power, cooling and connectivity.
This lack of standardization presents a barrier to scaling because, as the report notes, widespread adoption will depend not only on advances in hardware performance, but also on the ability to package and deploy systems at scale in quantum-ready data centers.
Quantum “hubs” are forming in locations with strong research ecosystems, talent pipelines and infrastructure, including cities such as Chicago, Boston and Santa Barbara. Over time, the report suggests, quantum infrastructure may need to move closer to data generation sites, particularly as hybrid quantum-classical workflows become more common.
Energy Demand and Compute Collide
The rise of quantum computing is occurring alongside a broader surge in computing demand driven by AI.
The growth of AI has led to projections that global data center power demand will nearly double between 2024 and 2030, the analysts write.
This creates a feedback loop between compute and energy. More powerful computing systems require more electricity, while energy systems themselves increasingly rely on advanced computing to operate efficiently.
Quantum computing enters this dynamic in two ways, according to the report.
First, it may help address some of the computational bottlenecks associated with energy systems, enabling more efficient modeling, optimization and decision-making.
Second, it introduces new infrastructure requirements that must be integrated into energy planning, including specialized cooling systems and potentially higher power densities.
In other words, quantum computing can be seen as both a contributor to and a potential solution for rising energy demand.
The growing importance of quantum technologies is also raising concerns about cybersecurity and national competitiveness.
Powerful quantum computers could eventually break widely used encryption methods, creating urgency around the development of quantum-resistant security standards. The report explains that this risk has elevated quantum computing from a technical issue to a national security priority.
Government investment is currently reflecting this upgrade in prioritization. Countries across North America, Europe, Asia and emerging markets are expanding funding and policy initiatives, often linking quantum development to broader goals in economic competitiveness and infrastructure resilience.
At the same time, workforce constraints pose a challenge. Quantum computing currently requires highly specialized expertise, often at the doctoral level, creating concerns about talent shortages as the industry scales.
Efforts are underway to broaden access through education programs, partnerships and tools that allow classically trained engineers to work with quantum systems without deep expertise in quantum physics.
A Hybrid Future
Despite rapid progress, the report emphasizes that quantum computing’s near-term impact will be limited to specific use cases rather than broad adoption.
Commercially useful, fault-tolerant systems — capable of correcting errors and operating at scale — are expected to emerge between 2028 and 2030. Until then, most applications will rely on hybrid approaches that combine quantum and classical computing.
This hybrid model is already shaping strategy. Companies are exploring how quantum systems can act as accelerators within existing workflows, rather than standalone replacements.
The report outlines several priority areas for energy companies, including optimization of grid operations, development of advanced materials and improvements in climate modeling.
Quantum approaches could, for example, help balance renewable energy sources in real time, reduce inefficiencies in energy distribution or simulate complex climate systems with greater accuracy.
However, the analysts caution that expectations must be managed. Many applications remain in early stages, and significant technical and operational challenges remain.
The analysts indicate that quantum computing will not transform the energy sector immediately, but that preparation must begin now.
“Quantum’s impact will unfold over years, not quarters — but preparation must happen today,” the analysts write.
Energy companies are advised to begin exploring hybrid computing environments, engage with vendors and research institutions, invest in talent development and integrate quantum considerations into cybersecurity planning.
The report also stresses the need for alignment between quantum strategies and energy infrastructure, warning that mismatches between technological progress and grid or data center capacity could create bottlenecks.
“Energy leaders who understand quantum’s trajectory, limitations and opportunities will be best positioned to balance risk and reward in an increasingly computing-driven energy era,” the analysts conclude.
