3 Quantum-AI Stocks That Could Outperform Traditional Tech Giants in 2025
Quantum computing meets artificial intelligence—and Wall Street hasn't even priced in the disruption.
Forget FAANG. These three quantum-AI plays are positioning to eat legacy tech's lunch while analysts are still busy downgrading crypto ETFs.
QuantumScape's solid-state batteries are solving energy density puzzles that stumped Tesla for years—imagine AI models running for months, not hours.
IonQ's trapped-ion systems already outperform classical computers on optimization tasks that make hedge fund algorithms look like abacuses.
Rigetti Computing just scored a DARPA contract that could make cloud quantum access as commonplace as AWS—if Big Tech doesn't regulatory-capture them first.
These aren't science projects. They're revenue-generating companies solving real problems while traditional tech giants are busy announcing stock buybacks instead of innovation.
Image source: Getty Images.
IonQ and D-Wave Quantum
(IONQ 5.63%) and(QBTS 12.01%) are two of my favorite quantum computing pure plays to follow. Each is taking a unique approach to the quantum computing industry, potentially giving them a leg up if their novel solutions work.
IonQ utilizes a trapped-ion approach, which has a few key advantages over the more popular superconducting approach. Instead of needing to cool a particle to nearly absolute zero, a trapped-ion computer can perform its tasks at room temperature. This reduces input costs, making it easier to deploy. Additionally, a trapped ion calculation is far more accurate than a superconducting one at this time. IonQ holds multiple world records for the most accurate quantum computers, and this could make it a top pick by potential clients.
D-Wave Quantum uses a quantum annealing approach, which isn't intended for broad use like a trapped ion or superconducting quantum computer might be. Instead, it works by finding the lowest energy state in a system, which represents the optimal solution. This makes it ideal for tasks like statistics or logistics networks, which represent a massive use case for quantum computing.
Each company is also looking at deploying its solutions for AI. IonQ's researchers have utilized several existing large language models and improved them by incorporating quantum computing. This cut down on energy cost and provided better-performing models. D-Wave Quantum is also involved with integrating quantum computing applications with AI, specifically focusing on applications where pre-trained AI could assist businesses and researchers.
Both companies are approaching integration with quantum computing in a hybrid approach, which involves using quantum computers to enhance what traditional computers are already doing. Currently, the king of traditional AI computing is(NVDA 0.34%), and it's also dabbling in the AI realm.
Nvidia
Nvidia isn't developing a quantum processing unit to replace its graphics processing units (GPUs). Instead, it's evolving its popular CUDA software to include quantum computing plug-ins, morphing the platform into CUDA-Q.
This is a smart approach by Nvidia, as it allows it to continue focusing on the AI arms race while capturing the upside of quantum computing. This approach will ensure that Nvidia's GPUs are needed in a hybrid computing application, which will continue to be the vast majority of use cases that deploy quantum computing.
While some may argue that Nvidia could be classified as a "traditional" tech company, I don't think it falls under this classification, as it's only a computing hardware provider that just happens to be the largest company in the world due to extreme demand. Nvidia is making a ton of money from its GPU sales to traditional big tech companies, and I think it's well-positioned to outperform in the current environment as well as in the future, when quantum computing potentially becomes a commercially viable technology.
