Like the hapless tramps in Samuel Beckett’s play Waiting for Godot, the world has been waiting – not for the mysterious Godot, but for quantum computing, which is much anticipated but has yet to arrive. But while the ghostly Godot never does show up, quantum is beginning to materialize.

It’s about time. Global powers, led by China, have invested more than $55 billion in the promising technology and we are closer than ever to realizing the $500 million to $1 billion in gains that quantum promises to deliver to businesses over the next fifteen years. The quantum market is already estimated to be worth more than $1 billion this year, even though quantum computers are not yet very useful.

In Europe, Germany has launched an investment plan of more than $3 billion by 2026, and France has announced an investment of nearly $2 billion, aiming to train 5,000 quantum-ready engineers and create 30,000 jobs. In the United States, the National Quantum Initiative Act has authorized $1.2 billion in funding over five years for quantum computing research and development.

What are we talking about? Computers that could be a billion times faster than conventional computers for solving certain complex problems.

Classical computers, such as the one you’re likely reading this article on now, rely on binary bits to store and process information as strings of zeros and ones. But quantum computers use quantum bits, or qubits, which can exist in a superposition of states, allowing for an exponential number of simultaneous combinations of zeros and ones. Don’t bother trying to visualize this – no one has ever seen a qubit. It’s all math.

Nonetheless, this superposition can be measured, enabling quantum computers to perform complex computations at an exponential speed.

Several technologies at the boundaries of current physics are being tried to make this work: superconductivity, neutral atoms, trapped ions, and photonics.

Are they used in businesses? Not yet. At this stage, quantum supremacy, meaning that a quantum computer is more efficient than a conventional computer, has only been established for algorithms without truly useful applications, such as verifying that a die is not loaded (Google, 2019).

But progress in developing quantum computing has been steady, and many people believe quantum computers will be a practical reality within a few years. IBM, the leader in quantum computing hardware, predicts that quantum computers will outperform classical computers in specific tasks by 2027.

Quantum supremacy is expected to first materialize for “native” quantum problems, which lend themselves particularly well to quantum modeling. They fall into four categories: modeling physicochemical reactions to discover innovative materials, new proteins, and future drugs; optimizing complex systems to improve flow management or the design and engineering of complex systems; generating synthetic data to train AI models; and finally, cryptography.

So, is it too early for businesses to be building their quantum muscle? Absolutely not. It takes time to build a team that understands how to use the burgeoning technology, and the future will belong to those who can harness the power of quantum computing early.

Banks, hedge funds, and car manufacturers are recruiting specialized quantum teams. They are tackling the construction of algorithms coded in qubits for their strategic applications. They are forming partnerships with quantum computer manufacturers – IBM, Atos, Pasqal – and academic research centers. These companies will be ready for the day when manufacturers offer sufficiently powerful machines. The aim is to increase the number of high-quality qubits and reduce error rates, eventually multiplying the power of the best current prototypes by a thousand.

The first challenge will be cybersecurity: with quantum supremacy, many of our security devices will become instantly obsolete. Businesses should start now to shift to quantum-hardened encryption technologies. The American National Institute of Standardization and Technology (NIST) is working on developing and standardizing post-quantum cryptographic algorithms and plans to impose a schedule for using encryption solutions capable of resisting quantum attacks.

But quantum computing has the potential to help mankind solve some of its biggest problems – mitigating climate change, for example, by accelerating the development of new materials for carbon capture, more efficient catalysts for hydrogen production, better batteries for electric vehicles, and optimized power grids that can handle renewable energy sources.

Quantum computing is also expected to accelerate drug discovery, enabling the development of personalized medicines and more effective treatments for diseases. And quantum algorithms could be used to optimize logistics and supply chain management, reducing fuel consumption and increasing efficiency. The list goes on.

AI can complement and enhance quantum computing, helping to develop error correction techniques for quantum hardware, for example, one of the main barriers to practical quantum computers. Quantum computers, meanwhile, can simulate complex natural processes, like the behavior of molecules or weather systems, much more accurately than regular computers.

Scientists collect relatively small amounts of data from experiments with such natural processes, but this isn’t always enough to train AI models effectively. Quantum computing is expected to be able to generate additional, high-quality data to fill in the gaps, making the simulations more accurate and reliable. This, in turn, can help AI make more precise predictions about natural phenomena.

And quantum computing can generate synthetic data to train generative AI models when real-world data is scarce or difficult to obtain. While GenAI does not directly use quantum algorithms, hybrid algorithms that combine classical and quantum computing can leverage the strengths of both computing paradigms, potentially leading to more powerful and efficient AI models.

And if quantum doesn’t come? In Beckett’s play, when Estragon asks this question to Vladimir, the wise vagabond replies: “We’ll come back tomorrow.” Businesses will do the same and remain busy with generative AIs.

Here Are Five Steps That Business Leaders Can Start Implementing Today

Build Quantum Expertise:

Working with quantum computing requires deep expertise, including quantum software developers and quantum hardware engineers who can design and optimize quantum circuits and algorithms for specific business applications. Quantum computing will initially augment rather than replace classical computing, so quantum teams will also need traditional software developers who can integrate quantum solutions with existing classical systems. And companies will need people who can translate complex business problems into quantum algorithms.

Since quantum computing is still an emerging field, companies will need to collaborate with academic institutions, technology providers, and quantum research organizations to keep up with the latest advancements and integrate cutting-edge solutions. Building a multidisciplinary team with these areas of expertise takes planning and time. While this may not be something smaller companies can undertake, large companies should start now. Because quantum computing is a new computing paradigm, hiring and developing talent capable of harnessing it in conjunction with company domain expertise will be the winning combination. But quantum scientists and engineers will be in short supply when quantum advantage will trigger interest, not dissimilar to what happened in AI in 2015 and GenAI now.

Develop Quantum Use Cases:

Companies need to identify and develop specific quantum use cases that align with their business goals. This involves exploring how quantum computing can solve industry-specific problems, such as molecular modeling in pharmaceuticals or portfolio optimization in finance. Conducting proof-of-concept projects and pilot studies ahead of time will help refine these use cases and demonstrate their potential value.

Harden Security Protocols:

Companies will need to implement post-quantum cryptographic algorithms (PQC) to secure data and communications. The National Institute of Standards and Technology has been developing these algorithms designed to withstand quantum threats. Companies large and small should track these developments and start integrating PQC algorithms into their security frameworks to ensure their encryption is hardened against quantum computer attacks.

Foster Strategic Partnerships:

Companies should begin forging strategic partnerships with quantum technology providers, research institutions, and other industry players. These alliances will facilitate knowledge sharing, accelerate innovation, and ensure access to the latest advancements.

Monitor Regulatory Developments:

Navigating the regulatory landscape is crucial for the successful adoption of quantum computing. Quantum computing is considered by governments as “dual-use” technology and critical for national security and competitiveness. Transitioning away from RSA to PQC protocols will a massive undertaking on a scale larger than the Y2K bug. Business leaders should stay informed about emerging regulations, mandates and standards.

Preparing for quantum computing is not a one-time effort but an ongoing commitment. It requires vision, strategic foresight, and a willingness to invest in the future. The rewards, however, will be immense for those who are prepared.

Leave a Reply

Your email address will not be published. Required fields are marked *