While quantum computing is still in the early stages of its development, the technology has massive potential because it could be capable of exponentially better performance than even the top supercomputers today. Artificial intelligence (AI) requires immense computing power, making the two technologies a logical pairing.

Together, AI and quantum computing could usher in a golden age of innovation. Research by McKinsey & Company estimates that the broader quantum technology market — including quantum computing, quantum communication, and quantum sensing — could grow to nearly $100 billion by 2035 and then double to almost $200 billion by 2040.

With that in mind, this is an excellent time to look at quantum computing stocks that could be potential winners as this technology matures. These three leading AI stocks could help lead the upcoming quantum revolution. Consider adding them to your portfolio today.

1. Nvidia

You can’t say much about AI before bringing up Nvidia (NVDA 1.10%), the runaway leader in providing parallel processing chips for AI data centers. The company’s expertise in developing high-end graphics processing units (GPUs) and its popular CUDA programming platform, which developers use to help those chips work efficiently on specific types of tasks, were keys to its emergence as an AI sector superpower.

Quantum computing is currently relatively unstable. Today’s machines are prone to errors, and the technology has limited practical use outside of scientific research. Nvidia is developing quantum-accelerated computing, a hybrid technology that combines both quantum and classical computer systems. Its CUDA-Q programming platform helps integrate all these components, allowing developers to build and utilize accelerated quantum for real-world applications.

You could think of it like a car company opting to sell hybrid vehicles instead of pure gas or electric models. It’s a mix of new and old technologies, potentially offering a faster path to market, monetization, and market share in high-end computing applications.

That’s essentially the same playbook that Nvidia used for its AI accelerator chips. Only time will tell whether Nvidia can corner another segment of the computing market, but the company’s ongoing AI momentum makes it a fantastic way for investors to gain exposure to the quantum computing opportunity.

2 Microsoft

Behemoth Microsoft (MSFT -0.20%) operates in a wide array of technology sub-markets, from operating systems to cloud services, and from gaming to enterprise software. Of course, Microsoft has also gotten involved with quantum computing.

Earlier this year, Microsoft announced Majorana 1, the world’s first quantum processing unit (QPU) powered by a topological core. It utilizes an entirely new state of matter (neither solid, liquid, nor gas) and is designed to be scaled up to a million qubits on a single chip.

Beyond innovation, Microsoft has direct pathways to sell quantum technology. The company’s Azure is the world’s second-largest cloud infrastructure platform, and millions of customers worldwide already use its various products and services. Microsoft arguably embodies the technology sector’s version of too big to fail. Plus, the company has a world-class balance sheet and has paid and raised its dividends for 23 consecutive years.

It’s hard to envision the technology giant not having a competitive presence in the quantum revolution, and yet it’s such a diverse and financially sound company that investors don’t need to feel like they’re taking a significant risk on quantum computing when they invest. Microsoft already has a $3.7 trillion market cap, so its further growth won’t make you rich overnight. But if peace of mind is essential to you, it’s hard to go wrong with this stock.

3. International Business Machines (IBM)

Computer infrastructure, AI software, and consulting giant International Business Machines (IBM -0.64%) is no longer the juggernaut it was decades ago. Still, it remains a steady presence in today’s technology landscape and has become one of the leading developers of quantum computers. Its Heron R2 quantum system has achieved some of the highest qubit performance while operating at one of the lowest error rates.

To date, IBM has deployed 13 utility-scale quantum computers and is approaching $1 billion in cumulative bookings for quantum computing. Additionally, IBM has developed Qiskit, a developer platform for building quantum software similar to Nvidia’s CUDA-Q. IBM claims Qiskit has a wide lead in developer support, with nearly 5,000 projects.

IBM is far from a pure play on quantum computing, which means it’s a far safer investment than speculative quantum computing businesses that currently have little to no revenue.

IBM has begun to grow again after transitioning its business away from some legacy offerings, and at current share prices, it offers a 2.3% dividend yield with a healthy payout ratio. Those dividends will help the company provide you with a solid return on your investment while you wait for its long-term quantum computing opportunity to unfold.

As a developer and a human being, you want to push yourself as much as possible to incorporate the intention of things into your practice. By insisting on understanding a project’s intention and uniting it with your own understanding of the particulars of implementation, you become far more valuable. AI then makes it easier to magnify your intentions into automated activity.

We can speculate that AI will get better at this middle ground in the future, but it will never actually have intention. It will only ever move under human direction. Resist becoming just a connector or interpreter of intention to implementation. Keep on working to develop and contribute your own unique understanding. Implementation can be automated, but the unique qualities of understanding cannot.

Why LLMs will not replace higher-level languages

If you follow the hype cycle, it might seem that AI’s ability to mass produce code to meet requirements makes understanding the intention of that code less important. I’d say it makes it less necessary up front. There may even come a time when AI’s natural language interface is something like what fourth-generation languages are today. I can see a possible future where languages like JavaScript and Python are a layer below the AI interface, akin to how C is today. But if that is the analogy we’re using, then it seems clear we will always need people who deeply understand that layer, just as today we still need people who understand C, assembly machine code, and chip wafers.