The Case Against Quantum Computing as a Technology Insurance Policy
The Case Against Quantum Computing as a Technology Insurance Policy
The potential and exciting use cases of quantum computing garner the lion’s share of attention, as they should. Drug discovery, financial portfolio optimization, predictive environmental modeling for climate change, transportation routing optimization…it’s a long list that spans many industries.
There is, however, one particular use case where quantum computing should never be used: as a technology insurance policy.
Allow me to explain.
My role at Zapata puts me in contact with enterprise decision-makers on an almost daily basis. So, I not only hear their questions, skepticism, concerns and enthusiasm for quantum computing, but also their ways of internally positioning it from a business planning perspective.
What I find is that many enterprises are focused on incorporating quantum into their IT architecture and readying themselves for more powerful devices in the hardware pipeline – inclusive of organizations we are presently working with on pilots and building production-ready assets. However, there are other enterprises that see quantum’s key benefit as a “technology insurance policy.” In other words, quantum computing as an investment hedge if they’re late to the competition’s leverage of quantum advantage.
This mindset of “We’re going to be disrupted by quantum, so we have to get ahead of it” is helpful to an extent, but in practice finding quantum talent and building capabilities is not accomplished rapidly. Specifically, enterprises don’t fully benefit from a cursory review of quantum with a single proof of concept (POC), some high-level education, and rolling out a “Mission Accomplished” banner. That’s playing a defensive game instead of trying to win. And, as any organization that adopted AI (i.e., pretty much every enterprise, everywhere) can attest, this will be a long game requiring a multi-season strategy.
That said, I understand the reasoning behind the “insurance policy” approach. With cutting-edge, exotic compute technology in general – and this goes double for quantum – there is certainly an element of playing the part, so to speak. We liken it to “quantum theater” (this goes for vendors and customers) and it is directly correlated to the hype that surrounds our industry. Enterprises, especially those without quantum Ph.Ds focused on just this area, have a difficult time effectively evaluating the latest research, products and (purported) innovations.
From my vantage point as someone whose focus is partnering with enterprises and helping them navigate away from the hype and toward the real, science-backed innovations to build quantum solutions, two things are clear:
If your company is just beginning its quantum journey, or even off to the races but possibly in need of a course correction, I suggest four key questions to deliberate internally:
In my experience, the best way forward is to consider quantum computing as an integral part of digital transformation, alongside current classical AI/ML strategies and workstreams — including data science and machine learning (DSML) — while building internal and partnership infrastructures now. In other words, build to win, and leave the insurance policies to insurance companies.