In the shadow of the current artificial intelligence boom, the promise of quantum technology is quietly building momentum. The article from BBC News, titled “Will Quantum Be Bigger Than AI?”, raises an important question: Could quantum computing and its associated technologies outpace or even surpass AI in impact and scale? In this newsletter, we analyze that question by looking at the state of play, the key differences between the technologies, and the implications for industry, society, and strategy.
The Current Landscape: AI’s Dominance And Quantum’s Quiet Progress
AI today is ubiquitous, from chatbots and recommendation engines to image generation and business automation. It is software driven, relying on data, models, and computing power. Quantum technology, by contrast, revolves around hardware based on the peculiar rules of quantum mechanics, and its applications are still nascent. As the BBC piece notes, quantum has “ended up with a lower profile than tech’s current rock star, artificial intelligence”.
Yet behind the scenes, investment and research are growing. Recent reports estimate that quantum technologies, including computing, sensing, and communication, could generate tens of billions of dollars in revenue by the early 2030s. The contrast is clear: AI is mature, pervasive, and fast moving, while quantum is early stage, complex, and promising a fundamentally different kind of capability.
Key Differences And What They Mean
A crucial difference lies in the nature of the problems each technology addresses. AI excels at pattern recognition, prediction, and automation using classical hardware. Quantum computing promises exponential speedups for very specific hard problems, such as molecular simulation, optimization, and cryptography. According to the analysis referenced by the BBC, quantum may unlock “weird activity” in the microscopic world that allows a “whole new world of scientific super power”.
However, that promise comes with formidable hurdles. Quantum systems are highly sensitive, require extreme environments such as near absolute zero temperatures, and face significant scalability and error correction challenges. These practical constraints mean that quantum remains much farther from everyday use than AI. The implication here is that quantum may not simply follow the path AI has taken but will require a different timeline and different business models.
Implications For Industry And Society
If quantum technology fulfills its promise, the implications across industry could be profound. In healthcare, it could accelerate drug discovery by simulating complex molecules far beyond classical capabilities. In materials science, it could enable new compounds and manufacturing processes. In cybersecurity, quantum communication could reset the foundations of secure data exchange. In each case, the impact could rival large scale AI deployments.
Yet the fact that quantum is limited to specific problem domains means its effect may differ from AI’s broad impact. AI touches many aspects of daily life, business operations, creative work, and even culture. Quantum may instead become a critical infrastructure technology that augments other fields rather than dominating them visibly. The implication for strategy is that organizations may need to treat quantum not as a replacement for AI, but as a complementary force that amplifies capabilities in certain niches.
Strategic And Policy Takeaways
From a strategic viewpoint, the question of whether quantum will be bigger than AI is less useful than asking how quantum and AI will interact. AI may continue to grow rapidly in breadth and application, while quantum may grow more slowly in breadth but offer depth and breakthrough capability in particular sectors. Organizations and nations that invest early in quantum infrastructure, talent, and partnerships could secure disproportionate advantage when the technology reaches commercial viability. Governments around the world are already signaling this by identifying quantum as a strategic priority.
Additionally, since quantum faces a different risk profile characterized by hardware fragility, long timelines, and high capital intensity, investors and executives must be patient and realistic. The hype cycle around quantum may mirror earlier waves of AI, but the timeframe may be longer and the applications more specialized.
A Final Note
In summary, will quantum be bigger than AI? Not necessarily in the same way. AI has a head start, broad application areas, and an ecosystem already in motion. Quantum may not replicate that exact path or scale of impact, but it has the potential to be transformative in its own domain. The more relevant question is how quantum and AI will converge and together reshape sectors such as healthcare, materials, and security. For businesses and policymakers, the prudent approach is to view quantum as a strategic complement to AI rather than a simple successor.
