IBM CEO Sees ‘Something Remarkable’ Happening in Quantum Over Next Three to Five Years

Insider Brief

• IBM is betting that quantum computing will be a foundational technology, with CEO Arvind Krishna predicting significant advances in error correction and coherence times by the end of the decade.

• The company is focused on engineering improvements to quantum hardware, aiming to extend qubit coherence times to a full millisecond to enable complex computations.

• IBM’s AI strategy prioritizes smaller, specialized models over massive general-purpose systems, contrasting with competitors like OpenAI and Google DeepMind.

• Image: IBM

As debates about quantum’s timeline continue to rage, IBM is betting that quantum computing will be a cornerstone of future technology, with chief executive Arvind Krishna telling Time Magazine the company is on track to achieve significant advances in error correction and coherence times by the end of the decade.

IBM has spent over a decade developing quantum hardware, a technology Krishna describes as more of an engineering problem than a scientific one. The challenge, he explains, comes down to two key issues: high error rates and coherence loss. While all computers experience errors, classical computing systems have built-in mechanisms that make them nearly invisible to users. Quantum computers, by contrast, are far more sensitive to disruptions, as tiny amounts of energy can interfere with their calculations.

Krishna said IBM has made steady progress in managing these challenges, improving coherence times—how long a quantum bit, or qubit, maintains its quantum state—to about a tenth of a millisecond. The goal is to extend this to a full millisecond, which he believes will enable quantum computers to perform calculations impossible for today’s classical machines.

“We feel over the next three, four, five years — I give myself till the end of the decade — we will see something remarkable happen on that front and I’m really happy where our team is,” Krishna told Time.

Translating Hardware Advances to Practical Benefits

IBM’s long-term strategy hinges on translating these hardware advances into practical applications for clients. Krishna envisions industries such as materials science, pharmaceuticals, and energy benefiting from quantum-powered discoveries.

“They will get the value, whether it’s material discovery or better batteries or better fertilizers or better drugs, that value will be accrued by our clients,” Krishna told the magazing.

IBM’s role, he argues, is to be the dominant provider of working quantum systems. Krisha added that this would gives IBM a tremendous position and the first-mover advantage.

IBM’s commitment to quantum comes as other major players, including Google and startups such as IonQ and Rigetti, push forward with their own efforts. While Google’s approach focuses on demonstrating “quantum supremacy” — a point where quantum computers surpass classical computers in a specific task—IBM has taken a more incremental approach, focusing on improving hardware performance and reducing error rates before scaling up.

Quantum computing is still in its early stages, but Krishna believes it will eventually be as integral to computing as the smartphone was to personal technology.

Krishna said: “Technology has always been additive. The smartphone didn’t remove the laptop. I think quantum will be additive. But much like we helped invent mainframes in the PC, maybe on quantum we’ll occupy that same position for quite a while.”

IBM’s AI Strategy

IBM’s strategy for artificial intelligence diverges sharply from companies like OpenAI and Google DeepMind, which have focused on scaling up large general-purpose AI models. Krishna argues that bigger isn’t always better. Instead of developing massive AI models that require billions of dollars in compute resources, IBM is betting on smaller, specialized models tailored for specific business applications.

“So if I have a 10 billion parameter model and I have a 1 trillion parameter model, it’s going to be 10,000 times more expensive to run the very big model,” Krishna said. “Then you turn around and ask the question, if it’s only 1% better, do I really want to pay 10,000 times more? And that answer in the business world is almost always no. But if it can be 10 times smaller, hey, that’s well worth it, because that drops more than 90% of the cost of running it. That is what drove our decision.”

IBM’s AI approach stems from lessons learned from its early AI ventures. In the 1990s, IBM’s Deep Blue became the first chess computer to defeat a human world champion, and in 2011, Watson won the game show Jeopardy! But subsequent efforts to apply AI broadly, such as in medical diagnostics, ran into challenges. Krishna said IBM underestimated the complexities of industries like healthcare, including regulatory requirements and operational workflows.

That experience led IBM to rethink its AI strategy. Rather than trying to create monolithic models that attempt to solve broad problems, the company has focused on developing fit-for-purpose models that optimize for specific tasks. Krishna disagrees with the idea that AI’s greatest potential lies in generalist systems.

“If you’re willing to have an answer that’s only 90% accurate, maybe,” Krishna told Time. “But if I’d like to control a blast furnace, it needs to be correct 100% of the time. That model better have some idea of time-series analysis baked into it. “

Krishna sees AI’s economic benefits being distributed between large companies that train foundational models and smaller businesses that apply them to specific use cases. He compares AI’s development to the early days of the internet, where both large platforms and small businesses thrived.

“If I’m going to build a video streaming business, the more content you have, the more people you can serve,” he said. “You get a network effect, you get an economy of scale. On the other hand, you have a shopfront like Etsy. Suddenly the person who’s an artisan who makes two items a year can still have a presence because the cost of distribution is extremely low.”

TIME spoke with Krishna ahead of a ceremony in early February when he was awarded a TIME100 AI Impact Award.