Quantum Computing in 2019 - Business Applications and Future Impact

Quantum computing has moved from theoretical physics to practical engineering, with major technology companies and startups racing to develop viable quantum systems. While still in its early stages, quantum computing has the potential to solve previously intractable problems and transform industries ranging from pharmaceuticals to finance. This comprehensive guide explores the current state of quantum computing in 2019, its potential business applications, and how organizations can prepare for the quantum future.

The Current State of Quantum Computing

Where the technology stands today:

• Noisy Intermediate-Scale Quantum (NISQ) Era: Current systems with 50-100 qubits
• Quantum Supremacy Milestone: First demonstrations of quantum advantage over classical computers
• Hardware Diversity: Competing approaches including superconducting, trapped ion, and photonic systems
• Ecosystem Development: Growing software platforms, algorithms, and development tools
• Commercial Availability: Early cloud-based quantum computing services

These developments are shaping how businesses should think about quantum computing's near and long-term potential.

Quantum Computing Fundamentals

Key concepts for business leaders:

1. Quantum Bits (Qubits)

The fundamental units of quantum information:

• Superposition: Qubits existing in multiple states simultaneously
• Entanglement: Quantum correlation between qubits regardless of distance
• Quantum Parallelism: Performing many calculations at once
• Coherence Time: Duration qubits maintain quantum properties
• Error Rates: Frequency of computational mistakes

Why It Matters: These properties enable quantum computers to explore vast solution spaces simultaneously, potentially solving problems that would take classical computers millions of years.

2. Quantum Computing Approaches

Different technological implementations:

Major Approaches

• Superconducting Qubits: Used by IBM, Google, and Rigetti
• Trapped Ion: Pursued by IonQ, Honeywell, and Alpine Quantum Technologies
• Silicon Spin: Developed by Intel and various academic labs
• Topological Quantum: Microsoft's long-term approach
• Photonic Quantum: Pursued by Xanadu and PsiQuantum

Why It Matters: Different approaches offer various trade-offs in terms of qubit count, coherence time, and error rates, affecting which applications will be viable first.

3. Quantum Algorithms

Software designed for quantum hardware:

Key Algorithms

• Shor's Algorithm: Factoring large numbers exponentially faster than classical methods
• Grover's Algorithm: Searching unsorted databases with quadratic speedup
• Quantum Approximate Optimization Algorithm (QAOA): Solving combinatorial optimization problems
• Variational Quantum Eigensolver (VQE): Finding lowest energy states of molecules
• HHL Algorithm: Solving linear systems of equations exponentially faster

Why It Matters: These algorithms define the types of problems where quantum computers will offer advantages over classical systems, guiding business use case development.

4. Quantum Development Platforms

Tools for quantum programming:

Major Platforms

• IBM Qiskit: Open-source framework for superconducting quantum computers
• Google Cirq: Python framework for NISQ algorithms
• Microsoft Quantum Development Kit: Tools integrated with Visual Studio
• Rigetti Forest: Full-stack library for quantum-classical computation
• D-Wave Ocean: Software for quantum annealing applications

Why It Matters: These platforms are lowering the barrier to entry for organizations wanting to experiment with quantum computing, even without quantum physics expertise.

Potential Business Applications

Areas where quantum computing may create value:

1. Computational Chemistry and Materials Science

Simulating molecular and material properties:

Potential Applications

• Drug Discovery: Simulating molecular interactions for pharmaceutical development
• Materials Design: Creating new materials with specific properties
• Catalyst Optimization: Improving chemical reaction efficiency
• Battery Development: Designing better energy storage solutions
• Nitrogen Fixation: Finding efficient fertilizer production methods

Business Impact: Quantum computing could reduce R&D timelines from years to months, potentially saving billions in development costs while enabling breakthroughs in materials and pharmaceuticals.

Example: Volkswagen and Google are collaborating to simulate battery chemistry for electric vehicles, aiming to develop batteries with higher energy density and longer lifespans.

2. Financial Services Applications

Optimizing financial operations and models:

Potential Applications

• Portfolio Optimization: Finding optimal asset allocations with more variables
• Risk Analysis: More accurate assessment of complex financial risks
• Fraud Detection: Identifying patterns in vast transaction datasets
• Derivatives Pricing: More accurate options and derivatives valuation
• High-Frequency Trading: Optimizing trading algorithms

Business Impact: Financial institutions could gain competitive advantages through better risk management, more efficient capital allocation, and identification of previously undetectable patterns.

Example: JPMorgan Chase is developing quantum algorithms for portfolio optimization, risk analysis, and option pricing, potentially providing better investment returns and reduced risk.

3. Logistics and Supply Chain Optimization

Solving complex optimization problems:

Potential Applications

• Route Optimization: Finding optimal delivery paths with multiple constraints
• Supply Chain Design: Optimizing global supply networks
• Warehouse Operations: Improving picking and packing efficiency
• Fleet Management: Optimizing vehicle utilization and maintenance
• Demand Forecasting: More accurate prediction of future needs

Business Impact: Organizations could reduce logistics costs by 5-10% while improving service levels and resilience, representing billions in savings for large operations.

Example: Airbus is exploring quantum computing for aircraft design optimization and supply chain management, potentially reducing costs while improving aircraft performance.

4. Artificial Intelligence and Machine Learning

Enhancing AI capabilities:

Potential Applications

• Quantum Machine Learning: Faster training of complex models
• Pattern Recognition: Identifying subtle patterns in massive datasets
• Natural Language Processing: Improving language understanding
• Recommendation Systems: More personalized and accurate recommendations
• Computer Vision: Enhanced image and video analysis

Business Impact: Quantum-enhanced AI could enable more accurate predictions, better customer insights, and automation of more complex tasks than currently possible.

Example: Google is researching quantum neural networks that could dramatically accelerate machine learning for applications ranging from healthcare diagnostics to autonomous vehicles.

Industry-Specific Quantum Applications

How different sectors may leverage quantum computing:

1. Pharmaceuticals and Healthcare

Transforming drug discovery and treatment:

• Protein Folding Simulation: Understanding disease mechanisms
• Drug-Target Interaction: Predicting how compounds interact with biological targets
• Personalized Medicine: Optimizing treatments for individual genetic profiles
• Radiotherapy Optimization: Improving cancer treatment planning
• Genomic Analysis: Finding patterns in genetic data

Example: Biogen is partnering with quantum computing companies to accelerate drug discovery for neurological diseases, potentially bringing treatments to market years faster than conventional approaches.

2. Energy and Utilities

Optimizing energy production and distribution:

• Grid Optimization: Managing complex electricity distribution networks
• Renewable Integration: Optimizing intermittent renewable energy sources
• Combustion Modeling: Improving efficiency of traditional energy generation
• Carbon Capture: Developing more effective carbon sequestration
• Nuclear Fusion Simulation: Advancing clean energy research

Example: ExxonMobil is working with IBM to apply quantum computing to solve complex energy problems, including optimizing power grids and developing more efficient carbon capture technologies.

3. Manufacturing and Materials

Improving production processes and materials:

• Process Optimization: Finding optimal manufacturing parameters
• Quality Control: Detecting subtle patterns indicating potential defects
• Supply Chain Integration: Coordinating complex manufacturing networks
• Computational Materials Design: Creating materials with specific properties
• Additive Manufacturing Optimization: Improving 3D printing processes

Example: Samsung is exploring quantum computing for semiconductor design and manufacturing optimization, potentially enabling more powerful and energy-efficient electronic devices.

4. Transportation and Automotive

Enhancing mobility systems:

• Traffic Flow Optimization: Reducing congestion in urban areas
• Autonomous Vehicle Algorithms: Improving decision-making capabilities
• Aerodynamic Design: Creating more efficient vehicle shapes
• Fleet Management: Optimizing vehicle deployment and routing
• Infrastructure Planning: Designing more efficient transportation networks

Example: Daimler AG is researching quantum computing applications for vehicle design, battery chemistry, and production logistics, aiming to accelerate the transition to electric mobility.

Quantum Computing Ecosystem

The developing quantum technology landscape:

1. Major Technology Players

Established companies investing in quantum:

Key Companies

• IBM: Offering cloud-based quantum computing with 20+ quantum systems
• Google: Developing superconducting quantum processors
• Microsoft: Building a topological quantum computer and software stack
• Intel: Focusing on silicon-based quantum chips
• Amazon: Providing quantum computing access through AWS

Strategic Approach: These companies are building full-stack quantum capabilities, from hardware to software and services, positioning themselves as platform providers.

2. Quantum Computing Startups

Emerging specialized players:

Notable Startups

• Rigetti Computing: Developing integrated quantum computing systems
• IonQ: Building trapped-ion quantum computers
• D-Wave Systems: Offering quantum annealing systems
• Zapata Computing: Creating quantum algorithms and applications
• QC Ware: Providing quantum computing as a service

Strategic Approach: These companies are focusing on specific aspects of the quantum stack, from specialized hardware approaches to industry-specific applications.

3. Research Institutions

Academic and government research centers:

Key Organizations

• QuTech (Netherlands): Collaboration between TU Delft and TNO
• Institute for Quantum Computing (Canada): University of Waterloo research center
• Center for Quantum Technologies (Singapore): National Research Foundation initiative
• Joint Quantum Institute (USA): Partnership between University of Maryland and NIST
• Chinese Academy of Sciences: Leading China's quantum research efforts

Strategic Approach: These institutions are advancing fundamental quantum science while training the quantum workforce and collaborating with industry partners.

4. Government Initiatives

National quantum programs:

Major Programs

• U.S. National Quantum Initiative: $1.2 billion program over five years
• EU Quantum Flagship: €1 billion, 10-year research and innovation initiative
• China's National Laboratory for Quantum Information Sciences: $10 billion investment
• UK National Quantum Technologies Programme: £270 million initiative
• Australia's Centre for Quantum Computation & Communication Technology: $83 million program

Strategic Approach: Governments are treating quantum computing as a strategic technology with national security implications, driving substantial public investment.

Preparing for the Quantum Future

How organizations can position themselves:

1. Quantum Readiness Assessment

Evaluating organizational preparedness:

Assessment Elements

• Problem Identification: Finding computational challenges that could benefit from quantum approaches
• Data Preparation: Ensuring data is structured appropriately for quantum processing
• Skills Evaluation: Assessing internal quantum-related capabilities
• Partnership Opportunities: Identifying potential quantum ecosystem collaborations
• Security Implications: Understanding how quantum computing affects security posture

Best Practice: Create a cross-functional quantum task force with representatives from R&D, IT, business units, and strategy to identify potential quantum opportunities and risks.

2. Quantum Learning and Experimentation

Building organizational capabilities:

Learning Approaches

• Quantum Education Programs: Training technical teams on quantum concepts
• Cloud Quantum Access: Experimenting with available quantum systems
• Quantum Hackathons: Hands-on problem-solving with quantum tools
• Academic Partnerships: Collaborating with university research groups
• Quantum Communities: Participating in open-source quantum projects

Best Practice: Start with hybrid classical-quantum approaches that can deliver value with current NISQ systems while building capabilities for future quantum advantage.

3. Quantum Use Case Development

Identifying business applications:

Development Process

• Problem Inventory: Cataloging computationally intensive business challenges
• Quantum Advantage Assessment: Evaluating potential quantum speedup
• Proof of Concept Design: Creating small-scale quantum experiments
• Classical Benchmark Comparison: Measuring against traditional approaches
• Roadmap Development: Planning for increasing quantum capabilities

Best Practice: Focus initially on problems that are difficult but not impossible for classical computers, allowing for direct comparison and validation of quantum approaches.

4. Quantum-Safe Security Planning

Preparing for cryptographic vulnerabilities:

Security Considerations

• Cryptographic Inventory: Identifying systems using vulnerable encryption
• Quantum-Resistant Algorithm Evaluation: Assessing post-quantum cryptography options
• Migration Planning: Developing transition strategies for critical systems
• Hardware Security Module Updates: Ensuring crypto infrastructure can be updated
• Long-Term Data Protection: Addressing information that must remain secure for decades

Best Practice: Begin transitioning to quantum-resistant cryptography for systems with long-term security requirements, as retrospective decryption will become possible once large-scale quantum computers emerge.

Challenges and Limitations

Understanding current constraints:

1. Technical Challenges

Current quantum computing limitations:

• Qubit Stability: Short coherence times limiting computation duration
• Error Rates: High error rates requiring error correction
• Scalability Issues: Difficulties in scaling to many qubits
• Input/Output Bottlenecks: Challenges in getting data in and out efficiently
• Environmental Sensitivity: Requiring extreme cooling and isolation

Implication: Most business applications will require more stable and powerful quantum systems than currently available, with practical quantum advantage for complex problems likely 3-7 years away.

2. Talent and Skills Gap

Workforce challenges:

• Quantum Physicist Scarcity: Limited pool of quantum specialists
• Interdisciplinary Requirements: Need for combined expertise across fields
• Educational Pipeline Limitations: Few quantum-specific educational programs
• Knowledge Translation Challenges: Difficulty connecting quantum concepts to business problems
• Competitive Recruitment Environment: Intense competition for quantum talent

Implication: Organizations should begin building quantum capabilities now through hiring, partnerships, and training to avoid falling behind as the technology matures.

3. Investment Considerations

Financial challenges:

• Long Time Horizons: Extended periods before commercial returns
• Uncertain Timelines: Unpredictable technology development paths
• High Capital Requirements: Substantial investment needed for hardware development
• Risk Assessment Difficulties: Challenges in quantifying quantum investment ROI
• Competitive Dynamics: Strategic necessity despite uncertain returns

Implication: Organizations should take a portfolio approach to quantum investments, balancing near-term NISQ applications with longer-term transformative opportunities.

4. Hype vs. Reality

Managing expectations:

• Inflated Expectations: Unrealistic near-term predictions
• Timeline Misperceptions: Underestimating development challenges
• Capability Misunderstandings: Confusion about what quantum computers can do
• Quantum Washing: Misleading marketing of "quantum" products
• Disillusionment Risk: Potential backlash if progress seems slow

Implication: Business leaders should maintain realistic expectations about quantum timelines while still preparing for the significant long-term impact of the technology.

The Future of Quantum Computing: 2019 and Beyond

Emerging trends and developments:

1. Quantum Hardware Evolution

Expected hardware developments:

• Error-Corrected Qubits: Progress toward logical qubits with error correction
• Increased Coherence Times: Longer-lasting quantum states
• Hybrid Quantum-Classical Systems: Optimized division of computational tasks
• Room Temperature Quantum: Advances in quantum systems operating at higher temperatures
• Quantum Networking: Development of quantum communication between processors

Strategic Implication: Organizations should track hardware developments closely, as breakthroughs could accelerate quantum advantage timelines in specific application areas.

2. Quantum Software and Algorithms

Software ecosystem development:

• Quantum Algorithm Improvement: More efficient approaches for NISQ devices
• Application-Specific Libraries: Industry-focused quantum software packages
• Abstraction Layer Development: Higher-level programming interfaces
• Quantum Machine Learning Frameworks: Specialized AI tools for quantum systems
• Quantum App Stores: Marketplaces for quantum applications

Strategic Implication: Software advances may deliver practical quantum advantage before hardware reaches full maturity, making it important to monitor algorithmic breakthroughs.

3. Quantum Computing Services

Evolution of quantum access models:

• Quantum as a Service (QaaS): Cloud-based access to multiple quantum systems
• Industry-Specific Quantum Solutions: Vertical applications for particular sectors
• Quantum Consulting Ecosystem: Specialized advisory services
• Quantum Marketplaces: Platforms connecting problems with quantum solutions
• Quantum Software as a Service: Specialized applications built on quantum backends

Strategic Implication: Cloud-based quantum services will likely be the primary access model for most organizations, making it important to develop relationships with quantum service providers.

4. Quantum Advantage Timeline

When quantum computers will surpass classical systems:

• 2019-2021: Quantum supremacy demonstrations for specialized problems
• 2021-2023: Limited quantum advantage for specific narrow applications
• 2023-2025: Practical business applications in chemistry and optimization
• 2025-2030: Broader quantum advantage across multiple domains
• 2030+: Fault-tolerant quantum computing enabling transformative applications

Strategic Implication: Organizations should develop staged quantum strategies that evolve as the technology matures, with initial focus on learning and experimentation followed by targeted applications.

Conclusion: Strategic Implications for Business Leaders

As we progress through 2019, quantum computing is transitioning from a theoretical concept to an emerging technology with practical implications. While widespread quantum advantage is still years away, the potential impact is so significant that forward-thinking organizations are already developing quantum strategies. The most successful organizations will be those that:

1. Build quantum awareness across technical and business teams
2. Identify potential quantum use cases specific to their industry
3. Develop partnerships within the quantum ecosystem
4. Invest in quantum talent through hiring and training
5. Prepare for quantum security implications by transitioning to quantum-resistant cryptography

By approaching quantum computing as a strategic technology rather than merely a research project, organizations can position themselves to capture value as quantum capabilities mature while mitigating potential risks.

Remember that quantum computing development is not a linear progression but will likely advance in unexpected ways—requiring ongoing attention, learning, and strategic adjustment as the technology evolves.

This article was written by Nguyen Tuan Si, a technology strategy specialist with experience helping organizations understand and prepare for emerging technologies across various industries.