What To Do While Pursuing The Promise Of Quantum Computing

Bonisiwe Shabane

-Jan 2, 2026, 11:35 AM

what to do while pursuing the promise of quantum computing

Brahima Sangafowa Coulibaly, Marcela Escobari, Homi Kharas, Pierre Nguimkeu, Jennifer L. O’Donoghue, Zia Qureshi, Landry Signé, Rebecca Winthrop Imagine a computer that could solve incredibly complex problems at a speed we can't yet fathom and bring about breakthroughs in fields like drug development or clean energy. That is widely considered the promise of quantum computing. In 2025, tech companies poured money into this field. The Trump administration also named quantum computing as a priority.

But when will this technology actually deliver something useful for regular people? NPR's Katia Riddle reports on the difference between quantum hype and quantum reality. KATIA RIDDLE, BYLINE: Tech companies like Google and Microsoft, as well as the U.S. government, bet big on quantum computing in 2025. UNIDENTIFIED PERSON #1: Google Quantum AI is unveiling the first demonstration of verifiable quantum advantage. PRESIDENT DONALD TRUMP: Joining forces on quantum computing.

UNIDENTIFIED PERSON #2: Creating an entirely new architecture for quantum computing. Quantum computing has long been technology’s white whale. But in recent months, new developments suggest practical applications for this elusive technology could finally be within reach. “Quantum has been five to ten years away from fruition for many, many decades,” says McKinsey Partner Michael Bogobowicz. “Now it feels three to five years away.” In this episode of The McKinsey Podcast, Bogobowicz joins McKinsey Global Editorial Director Lucia Rahilly to discuss how quantum differs from conventional computing, what its potential... In our second segment we ask, what’s the most important factor in having a successful transformation?

McKinsey Senior Partner Michael Bucy says it’s the CEO. The McKinsey Podcast is cohosted by Lucia Rahilly and Roberta Fusaro. The following transcript has been edited for clarity and length. Lucia Rahilly: Let’s talk about what’s new on mckinsey.com. More on tariffs. We just published an article about the importance of establishing a nerve center that can help companies respond comprehensively and in real time.

Quantum computing represents one of the most exciting and revolutionary frontiers in technology. While classical computers rely on bits to process information as either 0 or 1, quantum computers use quantum bits, or qubits, which can exist in multiple states simultaneously. This property of quantum superposition, combined with other quantum phenomena like entanglement, holds the potential to solve problems that are currently intractable for traditional computers. As quantum computing moves from theoretical research to practical application, businesses, governments, and individuals alike must start thinking about how to prepare for its impact. In this article, we’ll explore the current state of quantum computing, the challenges and opportunities it presents, and how to begin preparing for a quantum-powered future. Quantum computing is still in its early stages, but significant progress is being made.

Major tech companies like IBM, Google, Microsoft, and Intel are investing heavily in quantum research, and governments worldwide are funding quantum initiatives. These efforts are leading to notable breakthroughs in quantum hardware, software, and algorithms. One of the most famous milestones in quantum computing came in 2019 when Google announced it had achieved quantum supremacy—a point where a quantum computer solved a specific problem faster than the world’s most... While the problem solved by Google’s quantum computer was not practically useful, it marked a significant leap forward in proving that quantum computing could, in principle, outperform classical computing. However, large-scale, practical quantum computers that can address real-world problems are still a long way off. Today’s quantum systems are still relatively small, noisy, and error-prone, meaning they cannot yet solve problems of real-world complexity.

The field faces challenges in scaling up the number of qubits, improving error correction techniques, and developing algorithms that can harness the full power of quantum computation. The report states directly, “The convergence of artificial intelligence (AI) and quantum computing (QC) holds transformational potential across the economy.” QED-C argues that classical machine learning can accelerate quantum R&D (termed AI-for-QC), while quantum... The third leg is hybrid QC+AI, in which classical and quantum processors share a workflow to “reduce algorithmic complexity” long before fault-tolerant quantum machines arrive. The full report is available via https://quantumconsortium.org/quantum-computing-and-artificial-intelligence-use-cases/ The consortium is an industry-driven group managed by SRI International and backed financially by NIST. With corporate, academic and federal members, QED-C sees itself as a key facilitator for a nascent supply chain that spans dilution refrigerators, cryo-CMOS chips, error-correction software and now AI toolkits.

The report emphasizes the need for collaboration between the quantum and AI communities to accelerate progress and realize potential benefits sooner. Chemistry and materials science top the list of near-term opportunities. The report notes that quantum computers “hold the promise of achieving highly accurate approximations of molecular quantum states,” which could “enable the precise modeling of complex chemical reactions, streamline the design of new materials,... The report suggests “Al-enabled quantum simulation in chemistry could be one of the highest-value use cases in the quantum field.” Second is large-scale optimization in logistics and energy grids. The report states that “Approaches using QC + Al may be well suited to solving complex optimization problems such as supply chain scheduling, route planning, and energy distribution.” These problems challenge classical solvers as...

For instance, “quantum annealing – a type of QC that is especially well suited for optimization problems – may be useful to address combinatorial problems,” potentially combined with AI models to improve efficiency. Another area is “smart grid optimization, including energy unit commitment, and the integration of diverse energy sources.” Quantum computing promises unprecedented speed, but in practice, it’s proven remarkably difficult to find important questions that quantum machines can solve faster than classical ones. One of the most notable demonstrations of this came from Ewin Tang, who rose to prominence in the field as a teenager. When quantum algorithms had in principle cracked the so-called recommendation problem, Tang designed classical algorithms that could match them. So began the approach of “dequantizing,” in which computer scientists look at quantum algorithms and try to achieve the same speeds with classical counterparts.

To understand the ongoing contest between classical and quantum computing, co-host Janna Levin spoke to Tang on The Joy of Why podcast. The wide-ranging conversation covered what it was like for Tang to challenge the prevailing wisdom at such a young age, the role of failure in scientific progress, and whether quantum computing will ultimately fulfill... LEVIN: I’m looking forward to talking to you about my interview with Ewin Tang, a computer scientist at UC Berkeley. I realized, talking to her, that I don’t know anything about computer science. LEVIN: Do you feel like you’ve got a handle on quantum computing, classical computing? STROGATZ: Not really.

I mean, I can say the words. I’ve heard of Turing machines. I’ve heard of qubits. I’m puzzled by it. I can’t wait to hear your episode. Nature Computational Science volume 5, pages 1093–1094 (2025)Cite this article

As quantum mechanics marks its centennial, this issue of Nature Computational Science features a Focus that outlines the impact of quantum mechanics in advancing computing technologies, while discussing the challenges and opportunities that lie... Quantum mechanics emerged in the early twentieth century when scientists sought to explain phenomena that classical physics could not elucidate, such as the discrete energy levels of the hydrogen atom. In 1900, Max Planck introduced the concept of energy quantization to explain blackbody radiation1, which is considered the birth of quantum theory. Later, Niels Bohr’s atomic model2,3, Werner Heisenberg’s matrix mechanics4, and Erwin Schrödinger’s wave equation5 collectively established a comprehensive framework for quantum mechanics that explained why electrons occupy discrete energy levels and exhibit wave–particle duality,... These breakthroughs also paved the way for modern computing technologies. This year marks the centennial of quantum mechanics, honoring Heisenberg and his contemporaries’ works on laying the foundation for modern quantum theory.

To celebrate the anniversary, this issue of Nature Computational Science presents a Focus that explores the profound impact of quantum mechanics on advancing computational capabilities. The first notable impact of quantum mechanics on computing was its provision of a theoretical framework to understand electron behavior in solids, which is essential for semiconductor design. By explaining how electrons move through crystal lattices and interact with impurities, quantum mechanics enabled precise doping strategies that control conductivity in materials. Between the 1940s and 1950s, this understanding led to the creation of p–n junctions, the building block of the transistor, a tiny electronic switch that serves as the physical basis for modern digital computing,... This fueled the later exponential growth of computing power, such as the spread of supercomputers. For centuries, humanity has pushed the boundaries of knowledge by exploring the very nature of reality—diving into the mysteries of the universe, from galaxies to atoms.

Along the way, we created technologies that transformed our world: steam engines, electricity, the internet, and, more recently, the smartphone in your pocket. But now, we stand at the threshold of a new revolution—one that promises to upend the rules of computation, challenge our notions of physics, and unlock a power unlike anything seen before. Welcome to the age of quantum computing. Quantum computing isn’t just the next step in faster processors—it represents a fundamental shift in how we understand and manipulate information. Built on the principles of quantum mechanics, it defies the classical logic that has defined computers since the 1940s. With quantum computers, we aren’t just flipping bits of 1s and 0s; we’re sculpting waves of probability, entangling particles, and peering into alternate dimensions of calculation.

The implications are staggering. From solving problems in minutes that would take today’s supercomputers billions of years, to breaking current cryptographic systems, designing new drugs, and simulating the universe itself, quantum computing has the potential to reshape science,... But what exactly is quantum computing? How does it work, and why is it such a game-changer? In this in-depth journey, we’ll explore the fascinating rise of quantum computing, demystify its underlying principles, and understand its potential to revolutionize our digital future. In a world where digital transformation is the norm, quantum computing emerges as a paradigm-shifting technology that promises to redefine problem-solving and ignite innovation.

Even as headlines trumpet breakthrough after breakthrough, the journey from laboratory marvel to real-world application remains fraught with challenges. Drawing on authoritative sources and research studies, this article combines in-depth insights with simple language, concrete examples, numerical data, and meticulously referenced evidence to help you understand quantum computing’s potential—and to prove it. Quantum computing operates on principles that challenge our everyday intuition. Unlike classical computers that rely on bits (ones and zeros), quantum computers utilize qubits, which can exist in multiple states simultaneously thanks to superposition. When paired with quantum entanglement, these qubits allow systems to perform complex simulations and cryptographic tasks at speeds unachievable by traditional means. Recent advancements—such as innovative qubit designs and enhanced error correction methods—are signaling a shift toward more robust, scalable quantum architectures.

However, despite these breakthroughs, issues like noise and system instability continue to hamper widespread practical deployment. Several key developments are propelling quantum research forward: These breakthroughs are invigorating debates among experts regarding realistic timelines and the scope of quantum advancements, even as many caution that overcoming systemic scaling challenges remains a formidable task. Despite notable progress, several practical hurdles must yet be surmounted:

What To Do While Pursuing The Promise Of Quantum Computing

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