Quantum economy: Beyond the hype and reality


By Dr. Tim Sandle
DIGITAL JOURNAL
May 21, 2025


Despite their volatility and concerns over the huge quantities of electricity involved in trading them, cryptocurrencies like Bitcoin and Ethereum have soared in popularity in recent years - Copyright AFP -

Amazon has joined the quantum-computing race alongside Microsoft and Google, CNBC reported this week. However, many analysts think that the biggest opportunities in AI and quantum will not come from the usual tech giants alone. This includes Anders Indset—a thought leader and deep-tech investor.

According to Indset, the race between Microsoft (Majorana 1), Google (Willow) and Amazon (Ocelot) in early 2025 is only the beginning of a series of breakthroughs that will now switch from scientific to economical impact. Startups building software, applications and enabling ‘full stack’ like SandboxAQ, IonQ, Rigetti Computing, PsiQuantum and Swiss based Terra Quantum are already showing today how breakthroughs will have massive implications on security, energy, and business optimization.

The race is on – AI-driven biotech, materials science, and quantum security will create massive disruptions in the next 5 – 10 years.

Indset is the Founder and Chairman of Njordis Group, a driving force behind initiatives like the Quantum Economy, and a sought-after international speaker on exponential technologies and the future of humanity. along with renowned physicist Dr. Florian Neukart, Anders is also co-author of the new book Ex Machina: The God Experiment, which bring together philosophy and quantum physics to explore the hypothesis that our universe may be part of a chain of simulations.

Recently featured in InformationWeek and Observer on the future of quantum, Indset tells Digital Journal:

“Quantum computing’s commercial readiness is still in a nascent phase. Investors should calibrate expectations based on the technology’s genuine maturity rather than hype alone. While quantum computing might profoundly disrupt everything from AI to materials science, patience and a long-term perspective are crucial. Much like AI, we expect incremental progress until a major inflection point arrives. Until then, overreacting to either positive or negative headlines can lead to significant market swings that don’t necessarily reflect the underlying technology’s steady advance.”

In terms of the pace of change, Indset adds: “Historically, whenever we see a technology appear “decades away,” major discoveries sometimes emerge unexpectedly and accelerate the timeline—AI scaling over the last few years (notably with the GPT-Moment) is a prime example and so are the many examples along the “Gartner Hypecycle”. So, while 15 to 30 years might be a conservative estimate, there’s a high likelihood we will see meaningful applications much sooner.”

However, a measured approach is required to filter out some of the wilder claims. Indset cautions: “That said, balancing hype and reality is essential. The field of quantum computing tackles fundamental physics problems that don’t always conform to Moore’s Law. We can expect incremental progress and “quantum surprises,” but we still face significant scientific and engineering barriers—things like high error rates, short coherence times, and the need for specialized algorithms. It’s smart to plan for a long horizon while remaining open to the possibility that a single big discovery—whether in materials science, error correction, or new qubit technologies—could substantially speed up development. So if there are answers to some of the challenges or even if other approaches could be taken, most likely the timeline for breakthrough will be much shorter.”

Some of the caution relates to technological realities. According to Indset: “One of the biggest challenges is scaling. Even though crossing key error thresholds (like Google’s recent milestone) proves that quantum computing can “scale” in principle, the journey has only just begun. The community needs to add many more qubits to build complex quantum circuits that do practical tasks, further reduce and manage errors so logical qubits can run computations as long as needed, and develop entirely new software tools and programming models compatible with quantum mechanics—rather than the classic paradigms we use today.”

Following this, Indset clarifies: “This underscores why real-world applications are still a ways off. We can do certain tasks in the lab under carefully controlled conditions, but bridging that to consistent, large-scale production systems is where the real engineering mountain lies. Part of that bridge involves near-term, “bridge” technologies—specifically hybrid quantum-classical systems—that let smaller quantum processors tackle sub-problems while leveraging powerful classical HPC for the bulk of computation. It’s a giant step in the right direction, but we still have a long way to go before quantum computers become practical, everyday machines that solve real problems. It is also important to understand that quantum computers are as of now special purpose machines.”

Yet the development curve will deliver, Indset foresees: “Over time, as quantum hardware matures, we may see broader quantum-first approaches. But for the foreseeable future – in particular in 2025 – hybrid systems are the pragmatic way to deliver incremental value and learning while fully fault-tolerant quantum computers remain on the distant horizon.”

In terms of the future state: “Quantum algorithms are crucial because they tap into phenomena like superposition and entanglement, tackling problems classical computing can’t easily handle. For AI, quantum-enhanced techniques could dramatically speed up model training or uncover new patterns. For materials science, quantum simulations might optimize molecular design or accelerate drug discovery. And for cybersecurity—including cryptocurrencies—quantum could be both a blessing and a threat.”