As AI grabs headlines, another transformative technology — quantum computing — is making a significant impression behind the scenes. Heather Higgins of IBM Quantum underlined the huge potential in a recent interview: “McKinsey actually in a recent report put out that there are use cases that will create value capture for industry up to $2 trillion by 2030.”
So, what are these valuable use cases? Higgins outlined three main categories enterprises should watch:
“We talk about advanced mathematics and working with complex business structures,” she began. “A second category would be working with search and optimization. And the third category would be simulating nature.”
Within those buckets, quantum computing can tackle challenges like AI model training, supply chain optimization, and material design.
“You can think in biotech protein folding,” said Higgins, giving one example of simulating natural processes.
But adopting quantum requires careful strategy.
Higgins advised: “We start with the broad area. We whittle that down to about twelve problem types that we’re focused on today and we start to look at what those time scales are so that they can make purposeful investment decisions.”
The key, she explained, is understanding the incremental or disruptive impact sought, and an organization’s risk appetite.
“It’s not bad to be starting on incremental instead of disruptive,” she noted, as quantum requires rethinking how computations are approached.
With heavyweights like IBM leading the charge, quantum computing’s time is coming for enterprises aiming to gain an innovative edge.
