By Krishan Gopal Sharma
The age of quantum AI is no longer a futuristic concept. It’s here—emerging in labs, seeping into cloud platforms, and shaping quiet government strategies. What once sounded like science fiction is now becoming a reality in real-world pilots, patents, and policy briefings. The speed is breathtaking. The lack of clarity is alarming.
This year alone, global tech giants have rolled out early-stage deployments of quantum-assisted AI. These models aren’t just faster; they’re smarter in ways we can’t fully define. Supply chains are being optimized. Drug discovery is accelerating. Material science is opening new frontiers. India’s National Quantum Mission is advancing steadily, while the U.S. and China push to extend their lead. The arms race of the 21st century is less about missiles, more about algorithms.
But capability comes at a cost. Transparency is collapsing. AI was already a black box; quantum AI is a black hole. When these systems start making decisions—who gets a loan, which medicine is prescribed, which political content trends—what happens if no one can explain why?
The red flags are real. A financial institution shelved a quantum risk engine after it churned out unexplainable outputs that regulators couldn’t accept. In healthcare, a patient was flagged “high risk” by a model that had latched onto a phantom variable buried deep in its training data. These aren’t bugs. They’re warnings.
Governance is lagging. The UN has floated a global AI watchdog. The Global Partnership on AI has produced roadmaps. But consensus remains fractured. Innovation trumps restraint, and private players scale new heights with little appetite for collective guardrails.
Quantum AI also creates a sharp asymmetry. A handful of states or corporations could soon hold predictive power so precise it could tilt trade, defense, or diplomacy. If encrypted communications can be cracked in real time or economic moves forecast with surgical accuracy, trust among nations shatters. Negotiations could give way to anticipatory modeling—and whoever owns the models controls the field.
India is walking this tightrope with unusual clarity. It advocates ethical guardrails, fairness in algorithms, and data sovereignty. But clarity must evolve into leadership. India cannot afford to be a passive consumer of someone else’s future. Institutions must be prepared to question, to shape, and, when needed, to say no.
It’s tempting to view quantum AI as another technological leap, like the internet or smartphones. That would be a mistake. This isn’t about speed. It’s about control. And unless nations, regulators, and societies draw firm boundaries, we may soon cede control to systems we barely understand, designed by actors we don’t trust, for purposes we can’t predict.
For now, the machines still require our input. That may not last forever.
