Tech giants from Microsoft to Google are accelerating bets on quantum computing even as the field remains nascent and error-prone, reviving the question of whether quantum could ultimately outstrip artificial intelligence in impact. Market forecasts underscore the gap: McKinsey pegs quantum’s value at up to $97 billion by 2035, versus trillions for AI. Still, advocates argue quantum could deliver breakthroughs classical machines can’t touch—from rapid molecular modeling for drug discovery to ultra-precise sensors and resilient navigation.
Skeptics point to physics and engineering hurdles, with today’s fragile qubits requiring exotic environments and sophisticated error correction. Yet corporate pilots are multiplying: utilities exploring grid optimization, aerospace groups modeling cargo loading, and labs demonstrating chips that promise orders-of-magnitude speedups on select tasks. The looming security risk is clearer: once capable machines arrive, they could crack widely used encryption, prompting a global pivot to post-quantum cryptography even as adversaries stockpile stolen data. Analysts warn timelines are uncertain, but some place a potential “Q-day” near 2030. For investors and policymakers, the calculus mirrors AI’s: navigate the hype, hedge the downside, and prepare for outsized winners.
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