Scenario 2: Quandary
An undeveloped talent and operating environment, combined with later-than-expected scalable quantum computing, leads to slow progress.
Quantum progress has been continuous, but slow. Organizations continue to learn about the transformative potential that quantum computers can deliver, but innovation budgets are limited, and enterprise leaders are focused on other technology, mainly AI. Given underinvestment from venture firms that made bets on AI and classical computing, quantum computing hasn’t passed the technical threshold to meet commercial needs by 2030.
While it always has felt like there’s a light at the end of the tunnel with new scientific breakthroughs, the tunnel keeps getting longer in unexpected ways. Organizations’ investments move elsewhere, timelines extend, and business investment continues to shift. Only a few public universities and government institutions persist in investing at meaningful levels.
Stagnant talent operating in an academic environment has led to fewer vendors and options for organizations to experiment. Although most organizations have invested in AI talent, these teams have lacked any practical exposure to and experience with quantum algorithms and systems. Those that have continued to experiment in quantum computing have cornered the market on limited available talent.
While AI has driven revenue growth, shortsighted tech planning has left many organizations vulnerable when quantum utility does arrive, post 2030. Businesses have lost a decade of knowledge and infrastructure development. For example, when a seismic breakthrough in quantum molecular simulation occurs in pharma, leaders across all industries scramble to assemble boards and react. Chief information and technical officers must jump back into the quantum fray (or enter the quantum computing arena for the first time).
Most company leaders have written off quantum computing, except for a few stalwarts that continue to gain incremental, short-term advantages, such as enhanced classical computing capabilities, while they wait for scalable quantum computing to arrive (while filing patents to protect IP in the future). Some of these companies are also benefiting from experiments with quantum-inspired approaches, developing, for example, new optimization techniques that are generating enhanced performance relative to classical computers. By continuing to invest in maintaining their institutional knowledge from ongoing experimentation, they have secured a talent advantage and sustained a vision through C-suite role changes and commitment to multiyear quantum innovation agendas.
Impacts: Emerging opportunities and risks
While this may seem like a familiar future market scenario—quantum technical breakthroughs and the talent market taking a long time to evolve—many organizations that are making decisions based on this assumed future may have failed to fully think through the long-term implications on their businesses. Their assumption may be that if the market takes a decade to mature, the organization doesn’t need to act today because the opportunities and risks are also far off and can be addressed closer to a technical inflection point.
However, if the market experiences a “quantum winter” and technical progress takes longer than expected, that might not mean that they can and should delay investment for another decade. What’s worked in the past won’t necessarily work in this moment, given the pace of technological change and the sheer complexity it will require to get quantum infrastructure and talent scaled to the organization. Implementation of quantum computing will likely be significantly complex, taking longer to manage the risks, seize the opportunities, and compete relative to those who are investing in the quantum ecosystem now.
In the quantum quandary future (figure 5), we envision leading companies would concentrate expert quantum knowledge in the business, and it would be the responsibility of this small group to educate the broader organization.