The next frontier in tech: AI and quantum convergence

In late 2022, artificial intelligence became a household term as chatbots burst onto the scene. According to PitchBook, AI accounted for 3.6% of global investment dollars in 2024 and 8.5% of all technology investment dollars in 2024—not a bad showing for a notoriously capital-intensive innovation. While AI is still new and many companies are navigating the build-versus-buy decision regarding AI and the integration of the technology into their offerings, investors are already starting to look for the next technology revolution.

In December 2024, Google made headlines by announcing that its quantum chip, Willow, could perform a “computation in under five minutes that would take one of today’s fastest supercomputers 1025 or 10 septillion (that is, 10²⁵) years.” This significant increase in computing power could supercharge AI, allowing faster training of models and quicker analyses, with examination of multiple possible solutions at once and enhanced pattern recognition.

As with AI, it is likely that a few early investors will corner the market.

What differentiates quantum computing?

Quantum computing differs from traditional computers by using parallel processing and quantum processing bits (qubits). Parallel processing allows the chip to simultaneously process many calculations, whereas traditional computers process calculations one at a time (linear processing). Processing bits, the smallest data unit, utilized in traditional calculations were noted as either a 0 or a 1. However, qubits can represent both 0 and 1 simultaneously, mimicking quantum mechanics—thus the name quantum computing. Further, quantum computing can use a property called entanglement, where two qubits are linked so that the state of one qubit is dependent on the state of the other. Entanglement can be used regardless of the distance between the two qubits. The result is significantly enhanced speed.

What’s the catch?

Currently, quantum chips require an operating environment of about negative 459 degrees Fahrenheit to maintain the state of their qubits and thus their processing superiority. Considering the strain on the electrical grid and power supply, to commercialize quantum computing will require technological breakthroughs and innovative power conservation measures. A recent innovation from the Massachusetts Institute of Technology aimed at power conservation involved a method of wireless communication utilizing mirrors that reduced power consumption by up to 10 times.

Private funding has been sporadic for quantum computing, as the technology is still emerging. However, significant public funding has been aimed at further breakthroughs. According to an April 2024 McKinsey report, $42 billion of public funds were announced for quantum technology globally as of the end of 2023, of which the U.S. accounted for $3.8 billion. Additionally, a bill is under review in the U.S. Senate to release another $2.7 billion of funds over five years to boost quantum research and development domestically.

AI and quantum convergence

The predicted benefits of AI and quantum convergence are vast—ranging from expected breakthroughs in drug therapies to new ways to combat the climate crisis. As with AI, quantum AI holds significant upside potential for early movers in the market. A few key players will likely corner most of the market share for the early stages of its development and commercialization. However, opportunity is not limited to the developers or big players. Rather, it extends to the entire ecosystem supporting quantum AI—from chip development to energy optimization to scalability solutions.

Additionally, the cybersecurity sector will benefit, as it is anticipated quantum computing will be able to breach current encryption methods within minutes. New advancements in encryption and quantum-proof security will fuel an already booming sector.

Quantum AI comes with business risks similar to those of AI. Businesses need to evaluate whether building or buying is the right choice for them. Further, companies will need to assess the social and environmental impacts of quantum AI.