Quantum computing is a technology that could radically change the world. It’s also one that, despite decades of development, has so far failed to achieve anything resembling radical real-world change because practical quantum solutions that are usable at scale have failed to materialize.

Thus, for quantum skeptics, it’s easy to look at the history of quantum so far and be dismissive of the technology’s potential. Quantum may feel like a never-ending experiment that is unlikely ever to bear real fruit.

The history of AI, however, suggests a different trajectory for quantum computing. After all, AI is another technology that seemed to have limited potential for decades, but then exploded into a dramatically disruptive type of solution. The same story could well play out with quantum.

To prove the point, let’s explore the history of AI, assess the current state of quantum computing and consider what it will take for quantum to achieve the same type of transformational moment that AI underwent when genAI models became practical in 2022.

AI has been in development since the 1950s, when programmers built AI systems capable of doing things like playing checkers or (in the 1960s) conducting therapy sessions. These applications, however, were very niche and experimental. No one saw them as solutions that businesses would adopt on a large scale.

Even in the first decades of this century, when AI-powered analytics systems entered into widespread use to do things like generate product recommendations on shopping websites or identify anomalies in IT monitoring platforms, the applicability of AI technology seemed limited. AI at this point could help solve certain real-world problems, but it still didn’t feel like a fundamental game-changer.

Meanwhile, in the later 2010s, AI researchers quietly began making significant advancements in the realm of generative AI by creating more sophisticated large language models (LLMS) using the transformer architecture, a largely novel idea at the time. But outside of the rarefied world of AI engineering, few paid much attention. The models still felt very experimental and far too unreliable to solve real problems.

That suddenly changed when OpenAI debuted ChatGPT, powered by version 3.5 of the OpenAI GPT model, in November 2022. Seemingly overnight, a generative AI system had appeared featuring a host of impactful capabilities that once seemed unthinkable.

There remained a lot of room for improvement following the initial ChatGPT release and genAI and agentic AI continue to evolve. But the point is that in late 2022, a technology that had long seemed like it would never move beyond niche roles suddenly gained the potential to transform businesses entirely.

Quantum computing is also a technology that has been decades in the making, but for which engineers have yet to solve all of the technical challenges necessary to make the technology reliable enough for real-world use. If quantum’s history turns out to resemble that of AI, however, there is good reason to believe that quantum’s “ChatGPT moment” – meaning the point at which quantum computers become practical enough to solve real business problems – is on the horizon.

After all, quantum researchers have quietly achieved some important feats in recent years, such as exponential improvements in quantum error correction and the introduction of neural atom arrays as a way of creating more flexible and nimble quantum computers. These advances haven’t received much attention outside of the quantum research community, but they are perhaps not unlike the under-the-radar achievements that AI researchers made in the years leading up to the release of ChatGPT in 2022.

Admittedly, these innovations, on their own, don’t mean that Q-Day (the point at which quantum devices become practical for real-world use) is imminent. But they do bring that juncture a step closer.

It’s worth noting, too, that just as there was no real indication ahead of time that production-ready genAI technology was about to be unveiled in 2022, Q-Day is likely to arrive with no advance warning. That means that the businesses best positioned to take advantage of quantum computing will be those that assess quantum use cases and implementation requirements now. Early quantum adopters stand to gain tremendous advantages, and the most effective quantum transformation strategies are those that begin before Q-Day.

To be clear, this doesn’t mean that every business should drop everything and begin pivoting toward quantum today. But it is to say that companies that remain skeptical of quantum practicality do so at their peril in the same way those that believed AI would never really take off were caught unawares in 2022, slowing down their ability to achieve AI transformation. Smart businesses should be factoring quantum into their medium and long-term technology strategies now, because no one can say when the quantum equivalent of ChatGPT will go live.