Introduction
Quantum computing is moving from the realm of theory into the realm of practical impact. For many years, it has been framed as the “next big thing” in computing. Now, in 2025, we are witnessing tangible shifts: hardware, algorithms, investment, and business ecosystems are aligning. At TechSurge.ai, we focus on emerging tech that changes how organisations operate and compete, quantum computing is firmly in that category. In this blog, we will explore what quantum computing is, why it matters, where things stand in 2025, what remains to be solved, and how technology leaders should prepare.

What is quantum computing?

At its core, quantum computing uses the laws of quantum mechanics to process information very differently from classical computers. In classical computing, the basic unit is the bit, representing either 0 or 1. Quantum computing uses the quantum bit (qubit) which can, by virtue of superposition, be 0, 1, or both simultaneously. Further, qubits can be entangled so that the state of one is correlated with another, even if separated in space. 
These phenomena allow quantum machines to explore multiple computational paths in parallel, which enables them — in principle — to solve certain classes of problems far more efficiently than classical systems. 
It is important to note that quantum computers are not simply “faster computers” in the traditional sense. They excel at specific workloads — e.g., simulation of quantum systems, optimisation, cryptography-relevant problems — rather than replacing classical computers across the board.

Why it matters now

Several drivers make quantum computing relevant today rather than “some time in the future”.

1. Business and industry appetite: According to recent research, the market for quantum technologies (computing + communication + sensing) could approach US$ 100 billion by 2035. This signals that quantum technology is gaining commercial traction, not just research hype.

2. Technological inflection: Reports indicate that the field is shifting from growing qubit counts to stabilising qubit performance (fidelity, error rates) — meaning that hardware is becoming more credible.

3. Strategic urgency: With implications for security, materials, logistics and energy, organisations that wait too long risk being left behind. For example, quantum-safe cryptography is already being discussed as a risk mitigation imperative.

4. Hybrid computing: The emerging paradigm is one where classical and quantum computing co-exist. Organisations that begin exploring now will gain strategic advantage when full-scale quantum systems come online.

What does 2025 look like?

Here’s a snapshot of where things stand this year.

• Increased investment and global attention: The year 2025 has even been designated by the International Year of Quantum Science and Technology under the auspices of the United Nations, recognising the significance of quantum science and technology globally.

• Roadmaps become visible: Major players have publicly outlined quantum hardware and software plans. For example, IBM’s roadmap outlines modular quantum processors, fault-tolerant systems, and scaling to thousands of qubits.

• Quality over quantity: The focus is shifting toward improving fidelity, coherence times, and error correction rather than only increasing qubit counts.

• Business readiness: Studies show organisations shifting from “quantum curiosity” to “quantum readiness” — looking at pilot uses, strategic assessment and partner ecosystems.

Key sectors and use-cases

Quantum computing is poised to have major impact in several domains:

• Chemistry and materials science: Simulating molecular interactions and new materials more accurately. Because quantum computers mimic quantum systems naturally, they hold promise for breakthroughs in batteries, catalysts, pharmaceuticals.

• Finance and risk modelling: Problems such as portfolio optimisation, fraud detection, derivative pricing involve massive combinatorial complexity, which quantum algorithms may address more efficiently.

• Supply-chain, logistics and optimisation: Optimising routes, networks, flows under many constraints is a classic quantum-friendly problem. Analysing logistics, manufacturing, energy grids may benefit from quantum-enabled optimisers.

• Cryptography and security: Quantum computing threatens current encryption methods (e.g., factoring large numbers) and simultaneously enables quantum-secure communications and key-distribution systems. Organisations must plan for “post-quantum” security.

• AI and machine learning: Quantum computing may accelerate certain machine-learning tasks, enable new types of neural networks, and reduce energy consumption for large models.

What challenges remain

Despite the optimism, there remain significant hurdles to full commercialisation:

• Error correction and decoherence: Qubits are fragile, losing coherence quickly and subject to noise. Achieving fault tolerance remains a major technical barrier.

• Scalability: Going from tens or hundreds of qubits to thousands or millions is not simply a matter of adding more, but of maintaining coherence, connectivity, error control.

• Software, algorithms and integration: The quantum ecosystem is still nascent. Developing algorithms that make quantum hardware useful, integrating quantum into classical workflows, and building developer tooling are still major tasks.

• Cost and access: Quantum hardware is expensive and specialised; access remains limited to large players or via cloud-services. Broad accessibility is still in early stages.

• Use-case maturity: Although many promising use-cases have been identified, many are still experimental. Mid-term business value is emerging but not yet mainstream.

Action steps for technology leaders

Given this context, what should technology decision-makers be doing now?

1. Educate and upskill: Understand quantum fundamentals (qubits, superposition, entanglement, error‐correction) and identify internal champions or labs to explore proof-of-concepts.

2. Scan for quantum-relevant use-cases: Evaluate your business for tasks that involve large combinatorial complexity, optimisation, simulation of materials, or cryptographic risk.

3. Build hybrid thinking: Recognise that quantum will complement, not replace, classical computing. Model workflows that integrate quantum + classical systems.

4. Engage ecosystem partners: Consider alliances with quantum hardware vendors, algorithm firms, cloud quantum services, academic labs.

5. Monitor maturity and readiness: Track vendor roadmaps, fidelity improvements, commercial pilots. Prepare pilot budgets, but avoid “quantum hype” traps.

6. Plan security posture: Begin quantum-risk assessment (especially for encryption and key lifetimes). Consider quantum-safe cryptography.

7. Develop a strategic roadmap: Frame quantum as part of your future-tech roadmap (3-5 years), rather than a speculative experiment only.

8. Consider early experimentation: Use quantum cloud services (available today) to test small quantum algorithms, build familiarity for when hardware scales.

Conclusion

Quantum computing is no longer strictly “a technology of the future”, 2025 is a milestone year where the promise starts to materialise. For technology leaders, this is not the time to wait and watch; it is the time to begin exploring, planning and positioning for quantum-enabled change. At TechSurge.ai we are committed to bringing you insights on how such emerging technologies can reshape strategy, operations and competitive advantage. The quantum journey is just beginning — now is the time to get ready.