In the long run, that is from 2030 onward, quantum- computing applications will build on at-scale access to universal quantum computers, the experts estimate. Prime factorization algorithms to break common encryption keys will therefore be universally available. The focus will likely move toward digital security and risk mitigation as players try to prevent the quantum hacking of communications in autonomous vehicles, on-board electronics, and the Industrial IoT. Cloud-hosted navigation systems of shared-mobility fleets will improve their coverage algorithms through regular training enabled by quantum computing. Other promising fields of application include investigating and optimizing crash behaviour, cabin soundproofing or training for AI-based autonomous driving algorithms.
Such applications require a steep maturing process for the QC industry. The McKinsey experts admit that today it is unclear how the QC hardware industry will be able to reach this degree of maturity, but they see a number of possible ways. For instance, existing QC approaches will evolve over time. QC will establish itself as a cloud service, which will relieve users of the need to acquire and run their own hardware. Similarly, the market researchers expect that the QC software will evolve – with the difference that in contrast to hardware where almost all competencies are concentrated in the US, European players will also become relevant.
While many uncertainties persist, the analysts express optimism that most of the problems ahead will be solved within the time frame specified. For 2030, they expect an economic impact of these technologies in the automotive industry alone of some $2 billion to $3 billion by 2030.
The full study can be found here: https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/will-quantum-computing-drive-the-automotive-future