Quantum computing invites leaders to revisit ambitious challenges in optimization, discovery, artificial intelligence and security with a broader computational horizon. Patent activity is accelerating, hybrid quantum–classical approaches are running on real hardware, and their performance can increasingly be expressed through measures that shape enterprise decisions: accuracy, time, energy, reliability and outcome value. 

This creates a practical opportunity. Organizations can connect quantum progress to consequential business problems, learn alongside specialist partners, and build the product and operating capabilities that convert emerging technology into industrial advantage. 

Quantum readiness is the bridge. It connects scientific progress with enterprise outcomes through focused problem portfolios, credible benchmarks, accountable ownership, and disciplined investment decisions.
 

/ Quantum Momentum Gains Industrial Direction 

The joint OECD–EPO study Mapping the Global Quantum Ecosystem reports that international patent families in quantum grew at approximately 20% annually from 2014, compared with about 2% across all technologies. Quantum-computing patent activity expanded nearly twentyfold over the last decade, making it the most dynamic of the major quantum fields. The study points to a sector progressing from rapid expansion towards focused development and commercialization. (OECD–EPO, 2025) 

Europe brings substantial foundations to this next phase. The European Commission’s Joint Research Centre reports that the EU hosts 32% of the world’s quantum-technology companies and accounts for 6% of global quantum patenting. The distance between ecosystem participation and patent ownership creates a significant opportunity to convert scientific depth, entrepreneurial activity and public investment into more defensible intellectual property, scalable products and industrial outcomes. (European Commission JRC, 2025) 

For enterprises, these developments sharpen the strategic agenda. Relevant problem domains can be mapped to the product and innovation portfolio. Relationships can be built across the quantum ecosystem. Evidence thresholds can be defined for moving an opportunity from exploration into experiment and integration.

/ Real Hardware Makes the Opportunity Measurable 

A study co-authored by our friends at QuantumBasel and IonQ shows how quantum value can emerge as a focused component within a hybrid architecture, working alongside conventional AI. 

In the experiment, a pre-trained language model processed text while an IonQ quantum processor performed the final positive-or-negative classification. This division of work offers a practical pattern for adoption: retain proven classical capabilities and apply a quantum component to the computational step where it can contribute distinctive value. 

Across 250 samples, the best calibrated quantum-hardware result achieved 91.20% accuracy, compared with 89.56% for the strongest classical baseline used in the study. The 1.64-percentage-point difference represents approximately 15.7% fewer classification errors. 

Energy adds a second dimension. For circuits ranging from 10 to 28 qubits, quantum energy consumption grew approximately linearly, while GPU simulation of the same circuits grew much faster. Extending those measured trends indicated a potential energy break-even point around 34 qubits for this experimental configuration. (Knitter et al., 2026) 

The conditions of the result preserve its decision value. The accuracy benchmark covers one sentiment-classification workload and 250 samples. The energy crossover is projected from the measured 10–28-qubit range. GPU statevector simulation provides the classical comparison for executing the same quantum circuits. The paper’s approximately 24% error-reduction figure comes from an ideal quantum simulation; the calibrated real-hardware comparison yields approximately 15.7%. 

For leaders, the signal extends beyond this individual experiment. Hybrid architectures make selective adoption possible, while measurable accuracy and energy profiles allow technical progress to be connected to product performance and business economics. Organizations that recognize where those performance curves can compound into material value can build the partnerships, expertise, intellectual property and product capability that shape the next wave of adoption.

/ This Lens Connects Evidence to Enterprise Value 

The QuantumBasel–IonQ research offers a model for translating technical evidence into enterprise action. Enterprise value emerges through translation: deciding where the signal matters, what outcome it could improve and how the organization would absorb the capability. 

At bluegain, we view quantum readiness as an enterprise transformation capability spanning product strategy, business value, operating-model design and investment governance. A technically successful experiment creates industrial value when it improves a consequential outcome and can enter the organisation’s data, workflows, decision rights and delivery model. 

The strongest starting point is therefore a portfolio of two or three workloads where computational performance constrains a material result—for example production yield, logistics cost, development time, portfolio performance, resilience or product quality. Each opportunity needs a business owner, a credible comparison with the strongest current solution and an explicit value threshold. That keeps scientific learning connected to products, value streams and strategic capabilities from the beginning. 

Product-centric organizations are well positioned for this approach. Their existing ownership of products and value streams provides a natural home for the outcome, the experiment and the capability that develops around it. Learning remains connected to customer and business value from the beginning. 

/ Readiness Builds Strategic Position 

The problem portfolio creates the starting point. Quantum readiness turns each experiment into compounding enterprise capability. 

An accountable executive sponsor connects the work to strategic priorities and brings together the relevant business, product, technology and risk perspectives. Specialist partnerships provide access to quantum expertise and hardware. Data and workflow preparation make experiments representative of operating reality. Post-quantum security planning protects information whose value and confidentiality extend across long time horizons. 

Stage gates connect learning to investment. Opportunities progress through exploration, experiment, validation and integration as their outcomes, reliability and economics become clearer. Evidence from one workload strengthens future problem selection, partner choices, technical architecture and commercial judgement. 

This is strategic option value in practice: the capacity to recognize a valuable shift early, evaluate it with discipline and act with confidence as applications mature. The assets created through the journey—expertise, relationships, data readiness, intellectual property and product knowledge—strengthen the organization across future quantum opportunities. 

/ Four Moves from Evidence to Value 

1. Start with the consequential business problem. Identify where customers, employees, products or core operations encounter a constraint whose removal would create measurable value. Build the opportunity portfolio from these outcomes rather than from the technology. 

1. Apply a technology-fit test. Determine which approach is best suited to the problem: agentic AI, classical computing, optimization, quantum computing or a hybrid combination. Compare each option against the same outcome, performance and economic measures. 

1. Build one advanced-computing portfolio. Connect AI, classical computing and quantum within a shared investment view. This makes complementary architectures visible and directs resources towards the combination with the strongest enterprise potential. 

1. Build the quantum foundation in proportion to business value. Align investment with the organization’s opportunity, exposure and evidence. Develop the skills, partnerships, architecture, data readiness and security foundations that support the next credible move. 

The central principle is straightforward: begin with a consequential outcome, quantify its value and select the computational approach that can improve it. Each experiment should strengthen both the immediate business case and the organization’s capacity to capture future quantum opportunities. 

/ The Next Move Begins in Basel 

This is the purpose behind the joint bluegain × QuantumBasel CxO Workshop on 27 October 2026 at QuantumBasel in Arlesheim, near Basel. 

QuantumBasel brings deep quantum-computing expertise. bluegain brings AI, product strategy, industrial transformation and operating-model design. Together, we will connect emerging capability to the decisions that shape enterprise value: where to focus, how to compare alternatives, what to prepare, and how to move from experiment to impact. 

Enterprise cases and collaborative working sessions will explore optimization, materials science, logistics, post-quantum cybersecurity and hybrid AI–quantum opportunities. The selected-group format is designed for leaders to test assumptions, identify relevant problem domains, and leave with practical next moves for their organizations. 

Quantum AI is moving from theoretical promise towards measurable performance in accuracy and energy-to-solution. The opportunity now is to turn that progress into products, capabilities, and industrial value. 

Register for the bluegain × QuantumBasel CxO Workshop. 

Quantum AI is moving from theoretical promise toward measurable performance in accuracy and energy-to-solution. That does not prove universal quantum advantage, but it is enough to make quantum readiness a leadership decision today.

/ About the Author

• Arjun Aditya is a Digital Marketing Associate at bluegain, where he focuses on digital branding and communications. Before joining bluegain, Arjun worked at Adidas AG on a global transformation project, leading user-centric change initiatives that impacted over 1,000 employees. He also gained experience at Pollup Data Services and A2A Digital Transformation Consulting. Arjun holds a Master’s degree in Digital Business Innovation from Politecnico di Milano.
• Natasha Fernandes is a Sustainability Transformation Associate at bluegain, where she works on bridging the gap between business impact and sustainability initiatives. She is particularly passionate about circular business models and climate risk mitigation strategies that help companies create long-term value. Her previous experiences span risk advisory with Deloitte, operations consulting for the government, and co-founding a SaaS startup where she drove strategy and growth. She holds a Master’s in Management degree with a specialization in Sustainability from Nova School of Business and Economics, Portugal, where she was a 100% scholarship holder and received the Active Citizenship Award for her role in ESG initiatives.