What’s Next After Google’s Quantum Supremacy Claim?

In 2019, Google made global headlines by declaring that it had achieved “quantum supremacy.” The announcement, based on a lab experiment in which its quantum processor completed a specific task in 200 seconds that would take a classical supercomputer 10,000 years, sparked both celebration and skepticism. While some hailed it as a breakthrough, others questioned its real-world significance. Nearly five years later, one question remains:
what’s next?

Quantum computing is no longer confined to physics labs or science fiction. It is transitioning from theoretical promise to practical application. Leading technology firms, academic institutions, and governments are now investing billions into what they believe could become the defining computational infrastructure of the 21st century. But understanding its potential, and its limitations, requires going beyond the headlines.

At its core, quantum computing relies on the principles of quantum mechanics to process information. Instead of using binary bits like traditional computers, which are either 0 or 1, quantum computers use qubits, which can be both 0 and 1 simultaneously. This feature, called superposition, combined with entanglement and quantum interference, allows quantum machines to solve certain types of problems much faster than classical computers.

For now, quantum computing is not positioned to replace conventional computers. It is designed to complement them by handling complex tasks such as molecular simulation, cryptographic analysis, and optimization problems that are beyond the reach of even the most powerful supercomputers. In chemistry and pharmaceuticals, for example, quantum algorithms could one day simulate the exact behaviour of molecules, paving the way for precision drug development or new materials with targeted properties.

In finance, quantum computing could significantly enhance portfolio optimization, risk analysis, and fraud detection. In logistics and manufacturing, it could transform supply chain planning and production scheduling. In the energy sector, it may help model subsurface geological formations or improve battery design by simulating quantum systems. These are not just technical goals. They are strategic ambitions with multi-billion-dollar implications.

Yet, real-world deployment remains elusive. Today’s quantum computers are fragile, error-prone, and require cryogenic environments to function. They are mostly experimental, limited in scale and accuracy. The challenge is not just building more qubits but stabilizing them.

Researchers refer to this stage as “Noisy Intermediate-Scale Quantum” (NISQ), a transitional phase in which machines are not yet powerful enough for fault-tolerant quantum computing, but too promising to ignore.

In response, a global race is underway to develop error correction, hybrid algorithms, and scalable architectures. Companies like IBM, Google, and Intel are building larger and more stable quantum systems. China has declared quantum technology a national priority. The European Union and the United States have launched dedicated quantum initiatives. India has
announced a National Quantum Mission. The competition is not just for technological leadership but for future economic and national security dominance.

Sri Lanka and other emerging economies must now ask how they fit into this new equation.
Waiting for the technology to mature and arrive ready-made is no longer a viable strategy. By investing early in quantum education, collaborative research, and pilot applications, even smaller countries can carve out a niche. Whether through partnerships with global quantum labs, contributions to open-source quantum software, or participation in policy forums, there
are ways to gain relevance without building quantum machines from scratch.

Local universities should begin by introducing interdisciplinary quantum curricula that bring together physics, computer science, mathematics, and engineering. Research institutes can collaborate on simulation studies or develop quantum-inspired algorithms that run on classical machines. Meanwhile, the private sector should watch closely. Companies in
logistics, finance, and healthcare that are data-intensive should monitor how quantum computing could reshape their industries over the next decade.

While public understanding remains limited, the real significance of quantum computing may lie not in the machines themselves but in the mindset they demand. Quantum thinking is probabilistic, relational, and deeply interconnected. It challenges the linear, deterministic logic of classical computing. This shift in perspective could influence not only how we solve
problems, but how we perceive uncertainty, risk, and opportunity.

Google’s claim of quantum supremacy may have been more symbolic than practical. But it marked a turning point in the global narrative. It signaled that the era of quantum experimentation is giving way to the era of quantum engineering. The future will not be built by those who wait, but by those who begin preparing now for a world where computation is no longer binary, but quantum.