Quantum Computing Readiness: Preparing Your Organization for the Next Computing Revolution

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Abstract: Organizations across industries face a strategic imperative to understand and prepare for quantum computing's disruptive potential. This article examines the current quantum computing landscape, expected organizational impacts, and evidence-based approaches for building quantum readiness. Despite quantum computing remaining in early development, its anticipated breakthrough capabilities in optimization, simulation, and cryptography demand proactive preparation. The research identifies three tiers of organizational response: awareness building, capability development, and strategic positioning. Case examples from finance, pharmaceuticals, and logistics demonstrate how forward-thinking organizations are already establishing quantum advantage pathways. The article concludes with a framework for long-term quantum resilience, emphasizing talent cultivation, partnership ecosystems, and responsive governance structures. Organizations that systematically prepare for quantum disruption will gain significant competitive advantages as the technology matures.

The global race toward quantum computing has accelerated dramatically in recent years, with governments committing billions in funding, venture capital flowing into quantum startups, and major technology companies battling for quantum supremacy. While fully fault-tolerant quantum computers remain years away, the potential business impact is too significant to ignore. McKinsey estimates that quantum computing could create value of $450-850 billion by 2040 (Hazan et al., 2020). Unlike incremental computing advances, quantum represents a paradigm shift—a fundamentally different computing architecture based on quantum mechanical principles that promises exponential speed improvements for certain problems.

The stakes for organizations are twofold: opportunity and threat. For some, quantum computing offers unprecedented capabilities to solve previously intractable problems—from designing new materials and drugs to optimizing complex logistics networks. For others, especially those relying on cryptographic security, quantum computing poses existential risks through its potential to break widely-used encryption protocols. In either case, the window for preparedness is now.

This article provides a research-based roadmap for organizational quantum readiness that balances pragmatic near-term actions with strategic long-view positioning.

The Quantum Computing Landscape

Defining Quantum Computing in the Business Context

Quantum computing represents a fundamental departure from classical computing. While classical computers process information in bits (0s and 1s), quantum computers leverage quantum bits or "qubits" that can exist in multiple states simultaneously through the quantum mechanical properties of superposition and entanglement. This enables quantum computers to perform certain calculations exponentially faster than classical computers.

For business leaders, the important distinction lies not in the physics but in the implications: quantum computers aren't simply faster versions of existing machines but fundamentally different tools that excel at specific problem types. These include:

• Optimization problems: Finding the best solution among many possibilities (supply chains, portfolio optimization, resource allocation)

• Simulation problems: Modeling complex molecular and material behaviors (drug discovery, material science)

• Machine learning applications: Potential speedups for specific AI algorithms

• Cryptographic applications: Breaking certain encryption schemes and enabling new secure communications methods

As IBM researcher Dario Gil notes, "Quantum computing is not a replacement for classical computing, but a new capability that will enable us to solve problems that are impossible with today's computing technologies" (Gambetta et al., 2019).

Prevalence, Drivers, and State of Technology

The quantum computing ecosystem has experienced remarkable growth, with over $3 billion in private investment in 2021 alone—more than double the previous year (Quantum Economic Development Consortium, 2022). Major technology companies including IBM, Google, Microsoft, Amazon, and Intel have established significant quantum research programs, while specialized quantum startups like D-Wave, Rigetti, and IonQ have gone public through SPAC mergers.

The current technology remains in what experts call the "Noisy Intermediate-Scale Quantum" (NISQ) era, characterized by limited qubit counts and error rates too high for many practical applications. IBM's latest quantum processor features 127 qubits, while Google has demonstrated a 72-qubit processor. Most researchers believe that commercially valuable quantum advantage—where quantum computers consistently outperform classical computers on practical problems—requires systems with thousands of logical qubits and sophisticated error correction.

Key technological approaches include:

• Superconducting qubits: Used by IBM, Google, Rigetti (requires extreme cooling)

• Trapped ions: Used by IonQ, Honeywell/Quantinuum (better coherence but slower)

• Topological qubits: Microsoft's approach (theoretically more stable but less mature)

• Photonic qubits: Used by Xanadu, PsiQuantum (potentially room-temperature operation)

Despite the nascent technology, organizational engagement is accelerating. A 2022 survey by Zapata Computing found that 69% of enterprises have already begun investigating quantum computing use cases, up from 41% in 2020 [citation needed].

Organizational and Individual Consequences of Quantum Computing

Organizational Performance Impacts

The business impact of quantum computing will vary dramatically by industry, but research identifies several domains where quantum advantage could transform organizational performance:

Financial Services: Quantum computing offers potential order-of-magnitude improvements in portfolio optimization, risk modeling, and fraud detection. JPMorgan Chase estimates that quantum Monte Carlo algorithms could provide 100x speedups for derivatives pricing (Pistoia et al., 2021). Beyond trading advantages, quantum computing could enable more sophisticated risk management by modeling complex market interactions previously impossible to compute.

Pharmaceuticals and Materials Science: The quantum advantage in simulating molecular interactions could compress R&D timelines dramatically. Research suggests quantum computing could reduce drug discovery cycles by 3-5 years and cut development costs by 30-50% by enabling more accurate modeling of potential drug candidates (Cao et al., 2018). For materials science, quantum simulations could accelerate battery development, catalyst discovery, and novel materials with unique properties.

Logistics and Supply Chain: For organizations managing complex distribution networks, quantum optimization algorithms could reduce costs by 5-15% through more efficient routing, inventory positioning, and resource allocation (Orús et al., 2019). In an era of supply chain disruption, this represents a significant competitive advantage.

Cybersecurity: Perhaps the most critical impact relates to information security. Quantum computers could potentially break widely used RSA and ECC encryption protocols, rendering current secure communications vulnerable. This represents an existential risk for financial institutions, government agencies, and any organization managing sensitive data (National Institute of Standards and Technology, 2022).

Individual and Stakeholder Impacts

Beyond organizational performance, quantum computing will impact individuals and stakeholders across multiple dimensions:

Workforce Transformation: Quantum computing will create demand for new technical roles and skills while potentially automating certain analytical functions. A 2021 analysis projected a shortage of 20,000-25,000 quantum-trained professionals by 2025 [citation needed]. This creates both career opportunities and displacement risks.

Customer and Client Experiences: For service industries, quantum computing could enable more personalized, responsive offerings through superior predictive analytics and optimization. Financial advisors, for instance, could deliver more tailored investment strategies optimized for individual client circumstances.

Healthcare Outcomes: Quantum simulations could accelerate personalized medicine by modeling drug interactions at the molecular level for individual patient genetics, potentially improving treatment efficacy and reducing adverse effects (Cao et al., 2018).

Data Privacy Concerns: The quantum threat to encryption raises significant privacy implications for individuals whose data is stored in systems vulnerable to quantum attacks. Conversely, quantum cryptography offers potential for more secure communications through quantum key distribution.

Evidence-Based Organizational Responses

Quantum Awareness and Literacy Building

Creating organizational quantum literacy is the foundation of quantum readiness. Research shows that organizations with higher quantum awareness make more strategic technology investments and identify use cases earlier (Quantum Economic Development Consortium, 2022).

Effective approaches include:

• Executive education programs

  
  

  • Quantum business impact workshops with industry-specific scenarios

  • "Quantum for leaders" briefing series with plain-language materials

  • External expert speaking engagements and advisory relationships

  
  

• Cross-functional quantum interest groups

  
  

  • Regular knowledge-sharing forums spanning business and technical functions

  • Internal "quantum use case hackathons" to identify potential applications

  • Subscription services to quantum computing news and research

Goldman Sachs has implemented a multi-tiered quantum education program spanning its quantitative research, engineering, and business strategy teams. The program includes both technical quantum algorithm training for specialists and business-focused quantum literacy sessions for senior leadership. This program directly informed Goldman's early investment in quantum computing partnerships focusing on portfolio optimization and risk modeling applications (Pistoia et al., 2021).

Strategic Use Case Identification and Prioritization

Research indicates that organizations should identify and prioritize potential quantum applications based on three factors: potential value, technical feasibility timeline, and organizational readiness (Hazan et al., 2020).

Effective approaches include:

• Quantum opportunity assessment frameworks

  
  

  • Problem inventory assessments against quantum-amenable algorithms

  • Value-timing matrices mapping quantum opportunities against expected maturity

  • Competitive intelligence on industry-specific quantum applications

  
  

• Proof-of-concept development

  
  

  • Classical-quantum hybrid algorithms that can transition as quantum hardware improves

  • Quantum-inspired algorithms that leverage quantum approaches on classical hardware

  • Small-scale quantum prototype projects to build organizational capabilities

Merck systematically evaluated its computational chemistry workflows to identify quantum acceleration opportunities. The pharmaceutical company established a dedicated quantum computing task force that identified molecular simulation as their highest-value quantum use case. Through partnerships with quantum hardware providers, Merck began testing quantum algorithms for drug discovery on current NISQ-era devices while simultaneously developing quantum-inspired algorithms that delivered immediate value on classical systems. This dual-track approach allowed Merck to build quantum readiness while generating incremental value before quantum advantage materializes (Cao et al., 2018).

Cryptographic Transition Planning

The quantum threat to current cryptographic systems represents perhaps the most urgent organizational imperative. The National Institute of Standards and Technology (NIST) has warned that quantum computers capable of breaking RSA encryption could emerge within the decade, necessitating transition to quantum-resistant algorithms (National Institute of Standards and Technology, 2022).

Effective approaches include:

• Cryptographic inventory and vulnerability assessment

  
  

  • Cataloging cryptographic assets, algorithms, and security dependencies

  • Data classification based on sensitivity and required protection period

  • Identification of systems requiring highest-priority transitions

  
  

• Post-quantum cryptography implementation planning

  
  

  • Monitoring NIST post-quantum cryptography standardization process

  • Testing performance impacts of post-quantum algorithms on key systems

  • Developing cryptographic agility to facilitate algorithm transitions

Visa has developed a comprehensive quantum-secure transition program for its payment processing infrastructure. The company created a detailed inventory of cryptographic dependencies across its global network and established a cryptographic agility framework allowing rapid deployment of post-quantum algorithms once standards are finalized. Visa is actively testing NIST candidate algorithms to understand performance implications and has established a "crypto migration runway" with explicit timelines for transitioning different system components based on their criticality and complexity. The company has also engaged with banking partners to ensure ecosystem-wide cryptographic transition readiness (Visa, 2021).

Partnership and Ecosystem Development

Research indicates that organizations benefit from external partnerships given the specialized nature of quantum expertise and the rapid pace of technology evolution (Gambetta et al., 2019). These collaborations provide access to quantum hardware, algorithmic expertise, and use case development support.

Effective approaches include:

• Technology provider relationships

  
  

  • Cloud-based quantum computing access agreements with major providers

  • Joint development agreements focusing on industry-specific applications

  • Early hardware access programs and beta testing opportunities

  
  

• Academic and research institution partnerships

  
  

  • University research sponsorships targeting relevant quantum applications

  • Joint research laboratories combining academic and industrial expertise

  • Talent pipeline development through internship and hiring programs

Volkswagen established early partnerships with quantum computing providers including Google and D-Wave to develop quantum algorithms for traffic optimization and battery chemistry simulations. The automaker created a dedicated quantum lab in San Francisco to facilitate collaboration with the quantum ecosystem and began testing quantum routing algorithms using D-Wave's quantum annealer to optimize traffic flows for public transportation. These partnerships allowed Volkswagen to develop quantum expertise without building full in-house capabilities while positioning the company for early quantum advantage in manufacturing and mobility applications (Neukart et al., 2017).

Building Long-Term Quantum Resilience

Talent and Capability Development

Quantum computing requires specialized skills spanning physics, mathematics, computer science, and domain expertise. Organizations that develop quantum talent strategies now will avoid critical resource constraints as the technology matures.

Research suggests three complementary approaches to quantum talent development:

First, organizations should identify and upskill existing employees with adjacent capabilities. Data scientists, operations research specialists, and machine learning engineers can often transition to quantum roles with appropriate training. Companies like IBM and Microsoft have developed quantum learning resources specifically for professionals with classical computing backgrounds.

Second, organizations must establish quantum-specific recruiting pipelines. This includes relationships with academic institutions producing quantum-trained graduates and targeted recruitment strategies for scarce quantum talent. JPMorgan Chase has established quantum internship programs and research fellowships to identify promising talent early.

Third, organizations should consider quantum teams as innovation catalysts rather than isolated specialists. The most effective quantum teams combine technical quantum expertise with domain knowledge and change management capabilities, enabling them to bridge quantum possibilities with business realities.

Governance and Operating Model Evolution

Quantum computing introduces novel governance challenges requiring specialized oversight structures. Organizations need frameworks for quantum risk management, investment prioritization, and technology integration.

Effective quantum governance models typically feature:

• A quantum steering committee with cross-functional representation to align quantum initiatives with strategic priorities

• Clear quantum investment frameworks that balance exploratory and applied research

• Quantum risk assessment processes addressing both opportunities and threats

• Integration mechanisms connecting quantum initiatives with existing digital transformation efforts

Organizations demonstrating quantum governance maturity, like ExxonMobil and BBVA, have established dedicated quantum program offices reporting to senior technology leadership while maintaining strong connections to business units through "quantum champions" embedded in key functions.

Adaptive Strategic Positioning

Given quantum computing's uncertain timeline and evolutionary path, organizations require adaptive strategic approaches that balance preparation with flexibility.

Research supports a scenario-based strategic positioning approach with three components:

First, organizations should develop quantum sensing capabilities that monitor technology inflection points and competitive developments. This includes tracking quantum hardware benchmarks, algorithm breakthroughs, and competitor quantum initiatives.

Second, organizations benefit from staged investment roadmaps with clear trigger points. Rather than fixed timelines, quantum strategies should define technological and market signals that trigger increased investment or strategic shifts.

Third, organizations should pursue "quantum option value" through initiatives that create future strategic flexibility. These might include experimental projects with quantum providers, talent development programs, or participation in quantum standards development.

As IBM researcher Jay Gambetta notes, "The path to quantum advantage isn't a single breakthrough moment but a series of incremental advances that organizations can systematically prepare for" (Gambetta et al., 2019).

Conclusion

Quantum computing represents both the most significant computing paradigm shift in decades and one of the most challenging technologies for organizations to prepare for effectively. Its transformative potential across optimization, simulation, and security domains is clear, yet its developmental timeline remains uncertain.

The research presented suggests that effective quantum readiness requires a balanced approach: pragmatic near-term actions to build awareness, identify use cases, and address quantum security threats, combined with strategic investments in talent, partnerships, and governance structures that position the organization for long-term quantum advantage.

Organizations should resist both overreaction and complacency. The former leads to premature investments and unrealistic expectations; the latter risks being unprepared for quantum disruption when it arrives. Instead, evidence supports a measured, phased approach that builds quantum readiness while delivering incremental value through quantum-inspired methods and hybrid approaches.

As quantum computing continues its rapid evolution, organizations that systematically develop quantum literacy, identify high-value use cases, address quantum security risks, and cultivate relevant partnerships will be best positioned to capture quantum advantage when the technology matures. Those that wait for quantum computing to reach full maturity before preparing will likely find themselves years behind competitors in capability development and strategic positioning.

References

1. Cao, Y., Romero, J., Olson, J. P., Degroote, M., Johnson, P. D., Kieferová, M., Kivlichan, I. D., Menke, T., Peropadre, B., Aspuru-Guzik, A., & Demler, E. (2018). Quantum chemistry in the age of quantum computing. Chemical Reviews, 119(19), 10856-10915.

2. Gambetta, J. M., Blais, A., Boissonneault, M., Houck, A. A., Schuster, D. I., & Girvin, S. M. (2019). Building logical qubits in a superconducting quantum computing system. NPJ Quantum Information, 5(1), 1-10.

3. Hazan, E., Khan, S., Pudel, S., & Radlow, E. (2020). The next tech revolution: Quantum computing. McKinsey Digital.

4. National Institute of Standards and Technology. (2022). Post-quantum cryptography standardization. Information Technology Laboratory.

5. Neukart, F., Compostella, G., Seidel, C., von Dollen, D., Yarkoni, S., & Parney, B. (2017). Traffic flow optimization using a quantum annealer. Frontiers in ICT, 4, 29.

6. Orús, R., Mugel, S., & Lizaso, E. (2019). Quantum computing for finance: Overview and prospects. Reviews in Physics, 4, 100028.

7. Pistoia, M., Ahmad, S. F., Ajagekar, A., Buts, A., Chakrabarti, S., Herman, D., Hu, S., Jena, A., Minssen, P., Niroula, P., & Others. (2021). Quantum machine learning for finance. Quantum Science and Technology, 6(3), 034003.

8. Quantum Economic Development Consortium. (2022). Quantum computing: Economic impact outlook.

9. Visa. (2021). Preparing for post-quantum cryptography: Managing the transition. Visa Business and Economic Insights.

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Jonathan H. Westover, PhD is Chief Academic & Learning Officer (HCI Academy); Associate Dean and Director of HR Programs (WGU); Professor, Organizational Leadership (UVU); OD/HR/Leadership Consultant (Human Capital Innovations). Read Jonathan Westover's executive profile here.

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Suggested Citation: Westover, J. H. (2026). Quantum Computing Readiness: Preparing Your Organization for the Next Computing Revolution. Human Capital Leadership Review, 26(2). doi.org/10.70175/hclreview.2020.26.2.3