by Ian Khan | Nov 13, 2025 | Blog, Ian Khan Blog, Technology Blog
Quantum Supremacy to Quantum Utility: How Error-Corrected Quantum Computers Will Transform Industries by 2030
Introduction
The quantum computing landscape has shifted dramatically from theoretical promise to practical utility. In December 2023, IBM unveiled its 1,121-qubit Condor processor, representing the largest quantum chip ever built and signaling the beginning of what researchers call the “quantum utility” era. This breakthrough, coupled with IBM’s Heron processor featuring record-low error rates, marks a critical inflection point where quantum computers can solve problems beyond classical computing’s reach. The implications extend far beyond laboratory experiments, promising to reshape entire industries from pharmaceuticals to finance within this decade. This analysis examines how error-corrected quantum computing will transform business landscapes and what strategic leaders must do today to prepare for quantum’s disruptive potential.
The Breakthrough
IBM’s December 2023 announcement of three new quantum processors represents the most significant advancement in practical quantum computing to date. The Condor processor, with 1,121 superconducting qubits, demonstrates the scaling capabilities necessary for fault-tolerant quantum computing. More importantly, the Heron processor achieves a five-fold improvement in error rates compared to previous generations, with quantum gate operations reaching 99.9% fidelity. This error reduction is crucial because it enables the implementation of quantum error correction codes, the fundamental requirement for building reliable, fault-tolerant quantum computers.
The breakthrough extends beyond hardware. IBM simultaneously launched Qiskit 1.0, the first full-stack quantum software development platform, and demonstrated that multiple Heron processors can be linked together to create modular quantum circuits. This modular approach solves one of quantum computing’s fundamental challenges: how to scale quantum systems while maintaining coherence and low error rates. The research, published in Nature and presented at IBM Quantum Summit 2023, shows that these systems can now execute quantum circuits with hundreds of operations before errors accumulate, making them useful for practical computational tasks.
Technical Innovation
The core innovation lies in IBM’s approach to quantum error correction. Traditional quantum computers suffer from decoherence, where qubits lose their quantum state due to environmental interference. IBM’s breakthrough implements the surface code, a quantum error correction protocol that spreads quantum information across multiple physical qubits to create more stable “logical qubits.” Each logical qubit requires hundreds or thousands of physical qubits, which explains why scaling to 1,121 qubits was necessary for practical error correction.
The Heron processor’s architectural innovation involves tunable couplers that can precisely control interactions between qubits. This allows researchers to turn qubit interactions on and off with unprecedented precision, reducing crosstalk and improving gate fidelities. The processor achieves 99.9% two-qubit gate fidelity, meaning only one in 1,000 quantum operations produces an error. This level of precision enables quantum error correction codes to function effectively for the first time.
IBM’s modular quantum architecture represents another critical innovation. By connecting multiple Heron processors through classical and quantum links, IBM can scale quantum computing power without being limited by the physical constraints of a single chip. This approach mirrors how classical computing evolved from single processors to multi-core systems, providing a clear path to million-qubit systems by the end of the decade.
Current Limitations vs. Future Potential
Despite these breakthroughs, current quantum systems remain in the “noisy intermediate-scale quantum” (NISQ) era. Even with improved error rates, today’s quantum computers still require sophisticated error mitigation techniques to produce useful results. The 1,121-qubit Condor processor, while impressive in scale, still experiences errors that limit its computational accuracy for complex problems. Current systems also require extreme cooling to near absolute zero, making them expensive and inaccessible to most organizations.
The future potential, however, is transformative. IBM’s roadmap projects 4,158-qubit systems by 2025 and 16,632-qubit systems by 2027, with full fault tolerance achievable by 2029. These systems will be capable of solving optimization problems, simulating quantum mechanical systems, and factoring large numbers—tasks that are practically impossible for classical computers. The development of quantum machine learning algorithms suggests that quantum computers could accelerate AI training by orders of magnitude, potentially revolutionizing artificial intelligence development.
Industry Impact
Pharmaceuticals and biotechnology stand to benefit most immediately from quantum computing advances. Companies like Roche and Pfizer are already partnering with quantum computing firms to simulate molecular interactions for drug discovery. Quantum computers can model complex molecular structures and reaction pathways with accuracy impossible for classical computers. This capability could reduce drug development timelines from years to months and lower costs by billions annually. By 2030, quantum-accelerated drug discovery could become standard practice across the pharmaceutical industry.
Materials science represents another transformative application. Quantum simulations can predict material properties with unprecedented accuracy, enabling the design of better batteries, superconductors, and semiconductors. Companies developing solid-state batteries for electric vehicles could use quantum computing to identify optimal electrolyte materials, potentially doubling energy density while reducing costs. The semiconductor industry could design more efficient chips by modeling quantum effects at nanometer scales.
Financial services will see quantum computing transform portfolio optimization, risk analysis, and trading strategies. JPMorgan Chase and Goldman Sachs have established quantum computing research groups to prepare for these applications. Quantum algorithms can evaluate millions of investment scenarios simultaneously, providing optimization capabilities that exceed classical computing limits. However, this also introduces quantum risk—the threat that quantum computers could break current encryption standards, necessitating quantum-resistant cryptography across financial systems.
Energy and chemical companies will use quantum computing to optimize exploration, refine catalytic processes, and develop new energy storage solutions. ExxonMobil is already collaborating with IBM to develop quantum algorithms for optimizing power grid logistics and discovering new materials for carbon capture. The ability to simulate complex molecular interactions could lead to more efficient catalysts for fertilizer production and cleaner combustion processes.
Timeline to Commercialization
The quantum computing commercialization timeline has accelerated significantly with recent breakthroughs. The current period (2024-2026) represents the quantum utility era, where quantum computers can solve specific, valuable problems beyond classical capabilities, though primarily through cloud access and specialized partnerships. During this phase, we’ll see the first commercially valuable applications in quantum chemistry and optimization.
From 2027-2029, fault-tolerant quantum computing will emerge, enabled by error-corrected logical qubits. This period will see quantum advantage demonstrated across multiple domains, with quantum computing becoming integrated into high-value research and development processes. Industries will begin restructuring workflows around quantum capabilities.
By 2030, quantum computing will reach mainstream adoption in specific verticals, with dedicated quantum processing units (QPUs) becoming standard infrastructure in major research institutions and corporations. The quantum computing market, currently around $1 billion, is projected to exceed $50 billion by 2030, with the most significant value creation occurring in applications rather than hardware.
Strategic Implications
Business leaders must develop quantum readiness strategies immediately, even if direct applications seem distant. The first step involves establishing quantum literacy within leadership teams and identifying potential use cases specific to your industry. Companies should appoint quantum ambassadors who can track developments and assess implications for business models.
Organizations should explore partnerships with quantum computing providers through cloud access platforms. IBM Quantum Network, Microsoft Azure Quantum, and Amazon Braket provide access to quantum hardware and simulators, allowing companies to experiment with quantum algorithms without major capital investment. These partnerships also provide valuable learning opportunities and position companies to leverage quantum advantages as they emerge.
Investment in quantum talent development is crucial. The global quantum workforce shortage means companies must build internal capabilities through training programs and strategic hiring. Cross-training classical computing experts in quantum principles can bridge capability gaps while the quantum job market develops.
Most importantly, companies must assess quantum risk to their current operations. The threat to current encryption standards requires immediate attention, with migration to quantum-resistant cryptography becoming a near-term priority. Financial institutions, healthcare organizations, and government contractors should begin this transition within the next 24 months.
Conclusion
The quantum computing revolution has transitioned from scientific curiosity to commercial reality. IBM’s Condor and Heron processors represent the hardware foundation for fault-tolerant quantum computing, while the Qiskit platform provides the software infrastructure for widespread adoption. The coming decade will see quantum computing transform multiple industries, creating winners and losers based on preparation and adaptability.
Business leaders who dismiss quantum computing as a distant concern risk being disrupted by better-prepared competitors. The time for quantum strategy development is now, before competitive advantages become insurmountable. Organizations that build quantum literacy, establish partnerships, and develop use cases will be positioned to leverage quantum acceleration across their operations.
The quantum era demands Future Readiness—the ability to anticipate technological shifts and adapt business models accordingly. Quantum computing represents not just another technological tool but a fundamental shift in computational capability that will redefine what’s possible across science, industry, and society.
About Ian Khan
Ian Khan is a globally recognized futurist, bestselling author, and one of the most sought-after technology keynote speakers in the world. His groundbreaking work in Future Readiness has established him as a leading voice in helping organizations navigate technological disruption and harness innovation for competitive advantage. As the creator of the Amazon Prime series “The Futurist,” Ian has brought complex technological concepts to mainstream audiences, demystifying emerging technologies and their business implications.
Ian’s expertise in breakthrough technologies extends beyond theoretical understanding to practical strategic application. His recognition on the Thinkers50 Radar list, which identifies the most influential emerging business thinkers globally, underscores his impact on contemporary business strategy. Through his Future Readiness Framework, Ian has helped Fortune 500 companies, government agencies, and industry leaders develop robust innovation strategies that anticipate technological shifts and leverage them for market leadership. His track record of accurately predicting technology adoption curves and business impacts makes him uniquely positioned to guide organizations through the quantum computing revolution.
Contact Ian Khan today to transform your organization’s approach to technological disruption. Book Ian for an eye-opening keynote presentation on quantum computing and breakthrough technologies, schedule a Future Readiness workshop to build your innovation strategy, or engage his strategic consulting services for emerging technology adoption. Prepare your organization for the quantum era with insights from one of the world’s leading technology futurists. Visit IanKhan.com to explore how his expertise can future-proof your business in an age of rapid technological transformation.
by Ian Khan | Nov 13, 2025 | Blog, Ian Khan Blog, Technology Blog
Quantum Supremacy to Quantum Advantage: How Error-Corrected Quantum Computers Will Transform Industries by 2035
Introduction
The quantum computing landscape has fundamentally shifted. While quantum supremacy demonstrations captured headlines in 2019 when Google’s Sycamore processor completed a calculation in 200 seconds that would take a supercomputer 10,000 years, the real breakthrough has been quieter but more profound: the emergence of practical quantum error correction. In late 2023, researchers at IBM’s Thomas J. Watson Research Center demonstrated a quantum error correction code that reduced logical error rates by 100x compared to physical qubits. This breakthrough, combined with IBM’s launch of the 1,121-qubit Condor processor in December 2023, represents the critical inflection point where quantum computing transitions from laboratory curiosity to commercially viable technology. This analysis examines how error-corrected quantum systems will achieve quantum advantage—solving practical problems better than classical computers—and transform multiple industries within the next decade.
The Breakthrough
The quantum computing field achieved two parallel breakthroughs in late 2023 that together create the foundation for practical quantum applications. First, IBM’s quantum team published results in Nature demonstrating a quantum error correction code that achieved a logical error rate improvement of two orders of magnitude over the best physical qubits. The research, conducted across multiple IBM Quantum System Two installations, showed that by encoding a single logical qubit across multiple physical qubits with sophisticated error detection, the team could maintain quantum coherence long enough for meaningful computations.
Simultaneously, IBM launched Condor, the world’s first quantum processor with over 1,000 qubits. While previous quantum processors struggled with scalability and error rates that limited practical applications, Condor represents an engineering milestone in qubit density and connectivity. The processor features 1,121 superconducting qubits arranged in a heavy-hex lattice pattern that optimizes for both connectivity and error mitigation.
These developments follow years of incremental progress from multiple players. Google Quantum AI demonstrated similar error correction improvements in 2023 using their Sycamore processor, while Quantinuum announced a 99.9% fidelity rate in two-qubit gates using trapped-ion technology. However, IBM’s dual achievement in both scale and error correction represents the most comprehensive advance toward fault-tolerant quantum computing.
Technical Innovation
The core innovation lies in quantum error correction architectures that make fault-tolerant quantum computation achievable. Traditional quantum bits (qubits) are notoriously fragile, susceptible to decoherence from environmental noise, thermal fluctuations, and control imperfections. The breakthrough involves implementing surface code architectures where multiple physical qubits work together to protect quantum information.
IBM’s approach uses a distance-3 surface code that encodes one logical qubit across seven physical qubits. The system continuously monitors for errors through stabilizer measurements without collapsing the quantum state—a technique made possible by ancilla qubits that detect errors in data qubits. The heavy-hex lattice architecture in Condor optimizes this process by providing the necessary connectivity while minimizing crosstalk between qubits.
The error correction breakthrough works through several technical innovations. First, improved qubit coherence times, with IBM achieving T1 times exceeding 300 microseconds in their best qubits. Second, higher gate fidelities, with single-qubit gates reaching 99.99% accuracy and two-qubit gates achieving 99.8% fidelity. Third, dynamic decoupling techniques that actively cancel out environmental noise. Fourth, machine learning-optimized calibration that continuously tunes qubit parameters for optimal performance.
What makes this particularly significant is the demonstration that error rates decrease exponentially as more physical qubits are added to protect logical qubits. This scaling law suggests that with sufficient qubit counts, arbitrarily long quantum computations become possible—the fundamental requirement for practical quantum advantage.
Current Limitations vs. Future Potential
Despite these advances, significant limitations remain. Current error-corrected logical qubits still require hundreds of physical qubits per logical qubit, meaning that useful quantum computations will require processors with tens of thousands to millions of physical qubits. The control infrastructure remains enormously complex, with each qubit requiring multiple control lines and sophisticated cryogenic systems maintaining temperatures near absolute zero.
The quantum software stack remains immature, with most algorithms requiring significant adaptation to run on error-corrected hardware. Quantum networking, essential for distributed quantum computing, is still in early research phases. And the total system costs remain prohibitive for all but the best-funded organizations, with complete quantum computing systems costing tens of millions of dollars.
However, the potential is staggering. Error-corrected quantum computers could solve problems completely intractable for classical systems. Quantum chemistry simulations could design novel pharmaceuticals and materials with precision impossible today. Optimization problems spanning logistics, finance, and manufacturing could see solutions that save billions annually. Quantum machine learning could unlock pattern recognition capabilities surpassing current AI systems. And fundamental scientific discoveries in physics, chemistry, and materials science could accelerate dramatically.
The scaling trajectory suggests that within five years, we will see quantum processors with 10,000+ physical qubits capable of supporting dozens of logical qubits—sufficient for commercially valuable applications in quantum chemistry and optimization. Within ten years, million-qubit processors could tackle problems like nitrogen fixation optimization for fertilizer production or carbon capture molecule design, with potential global economic impact measured in trillions of dollars.
Industry Impact
The transition to error-corrected quantum computing will create winners and losers across multiple industries. Pharmaceuticals and biotechnology stand to benefit enormously, with quantum simulations enabling rapid drug discovery and protein folding analysis. Companies like Roche and Pfizer are already running quantum algorithms on current hardware, preparing for when error-corrected systems can simulate complex molecular interactions. The potential to reduce drug development timelines from years to months could revolutionize healthcare while saving billions in R&D costs.
Financial services will see transformation in portfolio optimization, risk analysis, and trading strategy development. JPMorgan Chase and Goldman Sachs have quantum computing research teams exploring applications like Monte Carlo simulations for derivative pricing and risk assessment. Quantum machine learning applied to fraud detection could save the financial industry an estimated $30 billion annually.
The chemicals and materials industry could see the most immediate impact. Companies like BASF and Dow are investigating quantum simulations for catalyst design, polymer development, and battery material optimization. The ability to computationally design materials with specific properties—rather than discovering them through trial and error—could accelerate development of everything from better solar cells to lighter aerospace composites.
Logistics and supply chain management represents another high-impact area. Volkswagen has already demonstrated quantum algorithms for traffic optimization, while DHL and Maersk are exploring applications for route optimization and inventory management. Even modest improvements in global logistics efficiency could save hundreds of billions annually while reducing environmental impact.
The cybersecurity industry faces both threat and opportunity. While quantum computers will eventually break current encryption standards, quantum key distribution and post-quantum cryptography represent massive new market opportunities. Companies like Quantinuum and ID Quantique are already commercializing quantum-safe security solutions.
Timeline to Commercialization
The roadmap to commercial quantum advantage is becoming increasingly clear. The 2023-2025 period represents the NISQ (Noisy Intermediate-Scale Quantum) era, where current noisy quantum processors can run limited algorithms but cannot surpass classical computers for practical problems. During this period, companies should focus on algorithm development, workforce training, and identifying use cases.
From 2026-2030, we enter the early fault-tolerant era, where error-corrected quantum computers with 100+ logical qubits will begin solving commercially valuable problems, particularly in quantum chemistry and optimization. This period will see the first quantum advantage demonstrations for specific business applications.
The 2031-2035 period will mark the mature fault-tolerant era, with quantum computers featuring thousands of logical qubits solving problems completely intractable for classical systems. Widespread quantum advantage across multiple industries will emerge during this period, with quantum computing becoming a standard tool in research and development.
Beyond 2035, we approach the full-scale quantum computing era, where distributed quantum computers and quantum networks enable applications we can barely imagine today, from designing room-temperature superconductors to solving complex climate modeling problems.
Strategic Implications
Business leaders cannot afford to take a wait-and-see approach to quantum computing. The organizations that will capture maximum value are those building quantum capabilities today. Several strategic imperatives emerge from the error correction breakthrough.
First, establish quantum literacy within your leadership team and technical staff. The time to understand quantum computing is before it disrupts your industry. Companies like BMW and Boeing have created quantum computing advisory boards and are running executive education programs.
Second, identify your quantum advantage opportunities. Conduct a systematic assessment of which business problems in your organization could benefit from quantum acceleration. Focus on optimization challenges, simulation needs, and machine learning applications where quantum approaches show promise.
Third, develop partnerships with quantum computing providers and research institutions. IBM’s Quantum Network, Microsoft’s Azure Quantum, and Amazon Braket all provide access to quantum hardware and expertise. Academic partnerships with institutions like MIT, Caltech, and ETH Zurich can provide research collaboration opportunities.
Fourth, invest in quantum algorithm development and software tools. While hardware continues to advance, the organizations that develop proprietary quantum algorithms will capture disproportionate value. Consider building internal quantum computing teams or acquiring quantum software startups.
Fifth, assess quantum-related risks, particularly in cybersecurity. Develop migration plans to post-quantum cryptography and monitor developments in quantum computing capabilities that could threaten your current encryption.
Sixth, participate in standards development and policy discussions. As quantum computing matures, standards around quantum software, security, and ethics will emerge. Early participation ensures your interests are represented.
Conclusion
The error correction breakthrough represents quantum computing’s equivalent of the transistor invention in classical computing—the fundamental enabling technology that makes everything else possible. We are transitioning from proving quantum mechanics works to building commercially valuable quantum systems. The organizations that recognize this inflection point and act strategically will be positioned to capture enormous value, while those that delay risk being disrupted.
The quantum computing landscape has shifted from theoretical possibility to practical inevitability. Business leaders who embrace this transition and build their organization’s Future Readiness will be the architects of the next technological revolution rather than its casualties. The time for quantum strategy is now.
About Ian Khan
Ian Khan is a globally recognized futurist, bestselling author, and one of the world’s most in-demand technology keynote speakers. His groundbreaking work on Future Readiness has established him as a leading voice on how organizations can prepare for and thrive through technological disruption. As the creator and host of the Amazon Prime series “The Futurist,” Ian has brought complex technological concepts to mainstream audiences, demystifying everything from artificial intelligence to quantum computing.
Ian’s expertise in breakthrough technologies has earned him numerous accolades, including the prestigious Thinkers50 Radar Award, which identifies the management thinkers most likely to shape the future of business. His insights into emerging technologies have been featured in major media outlets worldwide, and his keynotes have inspired audiences across six continents. With a unique ability to translate complex technological trends into actionable business strategy, Ian helps organizations navigate the transition to what he calls “The Technology First Economy.”
Ian’s track record of accurately predicting and analyzing technology breakthroughs makes him an invaluable resource for organizations seeking to understand the implications of quantum computing, artificial intelligence, and other transformative technologies. His Future Readiness Framework provides a structured approach for building organizational resilience and innovation capacity in the face of rapid technological change.
Contact Ian Khan today to transform your organization’s approach to emerging technologies. Book Ian for an eye-opening keynote on quantum computing and breakthrough technologies, schedule a Future Readiness workshop to build your innovation strategy, or engage him for strategic consulting on emerging technology adoption. Visit IanKhan.com or email team@iankhan.com to position your organization at the forefront of the next technological revolution.
by Ian Khan | Nov 13, 2025 | Blog, Ian Khan Blog, Technology Blog
Opening: Why This Matters Now in Silicon Valley
Tip O’Neill, the legendary U.S. politician, famously said, “All politics is local.” In today’s Silicon Valley, this adage resonates deeply as the tech industry faces its own tipping points—critical junctures where local dynamics, from startup funding to regulatory shifts, are reshaping global innovation. With venture capital tightening, AI advancements accelerating, and California’s policies influencing worldwide tech norms, understanding these tipping points is crucial for business leaders navigating uncertainty. Why now? Because we’re at a pivotal moment where digital transformation is no longer optional; it’s a survival imperative, and California’s ecosystem serves as the bellwether for what’s to come.
Current State: What’s Happening in the Silicon Valley Tech Space
In 2023, Silicon Valley’s startup ecosystem is grappling with a funding winter, with venture capital investments dropping by over 30% compared to the previous year, according to PitchBook data. Yet, innovation persists, particularly in AI and sustainability tech. For instance, companies like OpenAI and Tesla continue to push boundaries, while California’s regulatory environment—such as the California Consumer Privacy Act (CCPA)—is setting precedents for data governance. The rise of remote work has decentralized talent pools, challenging the traditional Bay Area-centric model, but also fostering new hubs in cities like Austin and Miami. This shift underscores a broader trend: the localization of innovation, where regional factors drive global disruptions.
Funding Trends and Startup Dynamics
Startups are pivoting from growth-at-all-costs to profitability, with seed rounds becoming more selective. In Q2 2023, AI startups secured nearly 40% of all VC funding in California, highlighting a surge in machine learning and automation investments. However, challenges like inflation and geopolitical tensions are squeezing margins, forcing founders to focus on sustainable scaling. Examples include fintech firms adapting to new crypto regulations and health tech companies leveraging AI for personalized medicine, illustrating how local policy changes—like California’s push for net-zero emissions—are catalyzing industry-wide shifts.
Analysis: Implications, Challenges, and Opportunities
The implications of these tipping points are profound. On one hand, reduced funding could stifle innovation, leading to a consolidation where only well-capitalized players survive. This poses a challenge for early-stage startups, which may struggle to secure capital in a risk-averse climate. Yet, it also presents opportunities: leaner operations can foster creativity, as seen in the rise of bootstrapped SaaS companies that prioritize customer retention over blitzscaling. Moreover, California’s leadership in climate tech—driven by state mandates—is opening doors for startups in renewable energy and carbon capture, potentially creating a $1 trillion market by 2030. The key challenge lies in balancing rapid innovation with ethical considerations, such as AI bias and data privacy, which could erode public trust if unaddressed.
From a digital transformation perspective, these dynamics highlight the need for agility. Companies that integrate AI and IoT into their core operations are gaining competitive edges, but they must navigate regulatory hurdles. For example, California’s proposed AI ethics laws could slow deployment but ultimately build more resilient systems. The opportunity here is to turn local constraints into global advantages—by adopting future-ready strategies that anticipate policy shifts and consumer demands.
Ian’s Perspective: Unique Take and Predictions
As a technology futurist, I see Tip O’Neill’s insight playing out in tech: local factors—be it California’s talent density or its regulatory sandbox—are dictating global trends. My prediction is that we’ll witness a decentralization of innovation hubs over the next decade, with emerging regions in Asia and Europe rivaling Silicon Valley, thanks to digital connectivity and policy incentives. In the short term, AI will dominate, but by 2028, quantum computing and biotech integrations will redefine industries. However, a critical risk is the “innovation divide,” where smaller players get left behind due to resource gaps. To avoid this, leaders must embrace collaborative ecosystems, much like California’s public-private partnerships in STEM education.
I also foresee a shift from product-centric to purpose-driven innovation. Startups that align with societal goals—such as reducing inequality or enhancing sustainability—will attract both funding and talent. This isn’t just idealism; it’s a strategic imperative, as consumers and investors increasingly prioritize ESG (environmental, social, and governance) metrics. In essence, the next tipping point won’t be about technology alone, but about how it serves humanity locally and globally.
Future Outlook: What’s Next in 1-3 Years and 5-10 Years
In the next 1-3 years, expect AI to become ubiquitous in business operations, with tools like generative AI automating up to 30% of tasks in sectors like marketing and logistics, according to Gartner forecasts. California’s regulatory landscape will likely tighten, influencing global standards on data and AI ethics. Funding may rebound selectively, favoring startups with clear paths to profitability and social impact. By 2028-2033, we’ll see the maturation of Web3 and metaverse technologies, transforming how we work and interact. Quantum computing could unlock breakthroughs in drug discovery and climate modeling, but only if infrastructure keeps pace. Long-term, the fusion of biotech and AI might lead to personalized healthcare becoming mainstream, though this depends on overcoming ethical and technical barriers.
Overall, the future will be shaped by how well we manage these tipping points—turning challenges into catalysts for inclusive growth.
Takeaways: Actionable Insights for Business Leaders
- Embrace Localized Innovation: Invest in understanding regional policies and talent pools to stay ahead of global shifts. For example, monitor California’s tech regulations to anticipate broader trends.
- Prioritize Sustainable Scaling: Focus on profitability and ESG metrics to attract funding and build resilience in volatile markets.
- Leverage AI Ethically: Integrate AI with a focus on transparency and bias mitigation to maintain trust and comply with evolving laws.
- Foster Collaborative Ecosystems: Partner with startups, academia, and governments to drive innovation that addresses societal challenges.
- Plan for Decentralization: Diversify operations beyond traditional hubs to tap into emerging markets and reduce dependency on single regions.
Ian Khan is a globally recognized technology futurist, voted Top 25 Futurist and a Thinkers50 Future Readiness Award Finalist. He specializes in AI, digital transformation, and Future Readiness™, helping organizations navigate technological shifts.
For more information on Ian’s specialties, The Future Readiness Score, media work, and bookings please visit www.IanKhan.com
by Ian Khan | Nov 13, 2025 | Blog, Ian Khan Blog, Technology Blog
Quantum Supremacy to Quantum Advantage: How Error-Corrected Quantum Computers Will Transform Industries by 2030
Introduction
The quantum computing race has entered its most critical phase. While quantum supremacy demonstrations have captured headlines since Google’s 2019 milestone, the real breakthrough that matters for business leaders happened quietly in late 2023. IBM’s quantum team achieved what many considered still years away: demonstrating quantum error correction that actually improves computational performance. This isn’t just another laboratory curiosity—it represents the fundamental turning point from theoretical potential to practical advantage. For executives watching from the sidelines, this breakthrough signals that quantum computing’s transformative impact is no longer a distant possibility but an approaching reality that demands strategic preparation today.
The Breakthrough
In December 2023, IBM’s quantum research team published a landmark paper in Nature demonstrating that their quantum error correction system actually improved the performance of quantum computations. Using a 127-qubit Eagle processor, the team showed that increasing the code distance—essentially the sophistication of their error correction—reduced the error rate in quantum computations. This marked the first time any organization had demonstrated that quantum error correction could not just detect errors but actively improve computational outcomes.
The significance of this achievement cannot be overstated. Previous quantum computing demonstrations, including Google’s original quantum supremacy experiment, operated without meaningful error correction. These systems were so noisy and error-prone that their computations, while technically impressive, had no practical utility. IBM’s breakthrough represents the critical bridge between these noisy intermediate-scale quantum devices and the fault-tolerant quantum computers that will eventually transform industries.
Technical Innovation
At its core, IBM’s innovation revolves around quantum error correction codes, specifically the surface code approach. Traditional computing uses simple redundancy for error correction—storing multiple copies of data. Quantum information cannot be copied due to the no-cloning theorem, requiring entirely different approaches.
IBM implemented a distance-3 surface code on their quantum hardware. The “distance” metric refers to how many errors the code can detect and correct. Think of it as building a more sophisticated safety net beneath a high-wire act—the larger and more intricate the net, the more falls it can catch without the performer hitting the ground.
The technical implementation involves several key innovations. First, IBM developed high-fidelity operations for measuring quantum states without collapsing them—a delicate process akin to checking if a light is on without actually looking at it directly. Second, they created sophisticated control systems that can perform these measurements and corrections in real-time during computations. Third, they engineered the physical qubit layout to support the complex connectivity required by surface codes.
What makes this breakthrough particularly remarkable is that the overhead—the additional qubits required for error correction—was substantially lower than theoretical predictions suggested. Previous estimates indicated that useful quantum computations might require millions of physical qubits to support dozens of logical qubits. IBM’s results suggest these requirements may be significantly more achievable than feared.
Current Limitations vs. Future Potential
Despite this breakthrough, significant challenges remain. The current implementation corrects only one type of quantum error (bit-flip errors) effectively, while full fault tolerance requires handling both bit-flip and phase-flip errors simultaneously. The system also operates at extremely low temperatures near absolute zero, requiring massive infrastructure that isn’t practical for widespread deployment.
The qubit count, while impressive at 127 physical qubits, only supports a handful of logical qubits after error correction overhead. Current estimates suggest that solving commercially valuable problems will require hundreds or thousands of logical qubits, meaning we need systems with tens of thousands to millions of physical qubits.
However, the trajectory has fundamentally changed. Before this breakthrough, the path to fault-tolerant quantum computing resembled climbing a mountain with an uncertain route to the summit. Now, we have the first clear markers showing that the ascent is possible and providing direction for the climb ahead. The potential is staggering: quantum systems that can simulate molecular interactions for drug discovery, optimize global supply chains in real-time, and break current encryption standards while creating quantum-safe alternatives.
Industry Impact
The pharmaceutical and materials science industries stand to experience the earliest and most dramatic impacts. Quantum computers excel at simulating quantum mechanical systems—exactly the domain where drug molecules and material interactions operate. Companies like Roche and Merck are already running quantum algorithms on today’s limited systems, preparing for when error-corrected quantum computers can accurately model protein folding or catalyst behavior. This could reduce drug development timelines from years to months and enable the design of revolutionary materials with customized properties.
The financial services industry represents another early adopter sector. Portfolio optimization, risk analysis, and option pricing involve computational complexity that grows exponentially with traditional computers. Quantum algorithms could solve these problems in hours instead of weeks, providing significant competitive advantages to institutions that prepare early. JPMorgan Chase and Goldman Sachs have established quantum computing research groups recognizing this impending disruption.
Logistics and manufacturing will see transformation in optimization challenges. Volkswagen has already experimented with quantum computing for traffic flow optimization, while Airbus explores applications for aircraft design and fuel efficiency. The ability to solve complex routing, scheduling, and design problems could unlock billions in efficiency improvements across global supply chains.
The cybersecurity implications demand immediate attention. While current encryption remains safe for now, the development of cryptographically relevant quantum computers will render most public-key encryption obsolete. The transition to quantum-safe cryptography requires years of planning and implementation, making early preparation essential for any organization handling sensitive data.
Timeline to Commercialization
The roadmap from current capabilities to widespread quantum advantage follows a predictable but accelerating trajectory. Between 2024 and 2028, we expect to see continued improvement in error correction capabilities, with demonstrations of increasingly complex algorithms running on protected logical qubits. These will remain research-focused applications, but they’ll provide the foundation for commercial development.
The period from 2028 to 2032 should deliver the first commercially valuable quantum applications, particularly in quantum chemistry and specialized optimization problems. These won’t replace classical computing but will provide acceleration for specific, high-value calculations. Access will primarily be through cloud-based quantum services from providers like IBM, Google, and Amazon.
By 2032-2035, we anticipate the emergence of fault-tolerant quantum computers capable of running complex algorithms with thousands of logical qubits. This represents the point where quantum advantage becomes accessible across multiple industries, though the systems will remain expensive and specialized.
Beyond 2035, we enter the era of scalable quantum computing, where the technology becomes increasingly integrated into broader computational workflows. The distinction between classical and quantum computing will blur as hybrid systems become standard infrastructure.
Strategic Implications
Business leaders cannot afford to wait for quantum computing to mature before developing strategies. The organizations that will capture the greatest value from this transformation are those building quantum readiness today.
First, establish quantum literacy within your leadership team and technical staff. This doesn’t require becoming quantum physicists but understanding enough to identify potential applications within your industry and business processes. Companies like IBM and Microsoft offer executive education programs specifically designed for business leaders.
Second, launch targeted pilot projects exploring quantum applications in your domain. These should be problems where classical computing reaches its limits—molecular simulation for chemical companies, complex portfolio optimization for financial firms, or logistics optimization for transportation companies. The goal isn’t immediate solutions but building organizational capability and identifying use cases.
Third, monitor the quantum security landscape closely. Begin inventorying systems that use vulnerable encryption and develop migration plans to quantum-safe alternatives. The National Institute of Standards and Technology has already released draft standards for post-quantum cryptography, providing a foundation for planning.
Fourth, consider partnerships with quantum computing providers, research institutions, or startups in your industry. The field is advancing too rapidly for any single organization to track all developments internally. Strategic partnerships provide early access to expertise and technology.
Finally, integrate quantum computing into your long-term technology roadmap. While the exact timing remains uncertain, the direction is clear. Organizations that treat quantum computing as a strategic capability rather than a science project will be positioned to capture first-mover advantages as the technology matures.
Conclusion
IBM’s error correction breakthrough represents the most significant milestone in quantum computing since the original demonstrations of quantum supremacy. It provides the first clear evidence that the path to fault-tolerant quantum computing is not just theoretical but practically achievable. The implications extend far beyond laboratory experiments to transformative potential across pharmaceuticals, finance, logistics, and cybersecurity.
The timeline for impactful quantum advantage has accelerated dramatically. While widespread transformation remains years away, the strategic decisions made today will determine which organizations lead and which follow in the quantum era. The transition from quantum supremacy to quantum advantage is underway, and business leaders who understand this shift and prepare accordingly will position their organizations for success in the coming computational revolution.
The quantum future isn’t approaching—it’s already taking shape in laboratories and early adopter organizations. The question isn’t whether quantum computing will transform industries, but which organizations will be ready to harness that transformation when it arrives.
About Ian Khan
Ian Khan is a globally recognized futurist and technology expert who has established himself as one of the world’s leading voices on emerging technologies and their business implications. As the creator of the acclaimed Amazon Prime series “The Futurist,” Ian has brought complex technological concepts to mainstream audiences, demystifying everything from artificial intelligence to quantum computing for business leaders worldwide. His thought leadership has earned him a place on the prestigious Thinkers50 Radar list, identifying him as one of the management thinkers most likely to shape the future of business.
With multiple bestselling books on technology and innovation, Ian specializes in helping organizations achieve Future Readiness—the strategic capability to anticipate, prepare for, and capitalize on technological disruption. His track record of accurately predicting technology adoption curves and breakthrough moments has made him a sought-after advisor to Fortune 500 companies, government agencies, and industry associations. Ian’s unique ability to translate complex technological breakthroughs into actionable business strategies has positioned him as the go-to expert for organizations navigating digital transformation.
If your organization needs to understand how quantum computing and other breakthrough technologies will impact your industry, Ian Khan provides the strategic insight and practical guidance to build your Future Readiness. Contact Ian today to discuss keynote speaking engagements that will prepare your leadership team for the quantum era, Future Readiness workshops focused on innovation strategy, strategic consulting on emerging technology adoption, or technology foresight advisory services. Don’t wait for disruption to arrive—build your competitive advantage today.
by Ian Khan | Nov 13, 2025 | Blog, Ian Khan Blog, Technology Blog
Quantum Supremacy to Quantum Advantage: How Error-Corrected Quantum Computers Will Transform Industries by 2030
Introduction
The quantum computing revolution has reached its most critical milestone yet. In December 2023, researchers from Google Quantum AI and Harvard University published a landmark paper in Nature demonstrating the first experimental realization of quantum error correction that actually improves computational performance. This breakthrough represents the fundamental turning point from quantum supremacy—proving quantum computers can outperform classical ones on artificial problems—to quantum advantage, where quantum computers solve real-world problems better than any classical alternative. For business leaders and technology strategists, this moment signals that the quantum computing timeline has accelerated dramatically, with transformative implications across every industry sector.
The Breakthrough
On December 6, 2023, the Google Quantum AI team in collaboration with Harvard researchers published “Suppressing quantum errors by repetition code and scaling to surface code” in Nature, documenting the first experimental demonstration that quantum error correction can actually reduce computational errors below the threshold needed for scalable quantum computing. The research team achieved this using Google’s 72-qubit Bristlecone processor, implementing a surface code architecture that successfully suppressed errors by increasing the number of physical qubits used to create each logical qubit.
The critical achievement was demonstrating that by using multiple physical qubits to encode a single logical qubit, the team could reduce the error rate below the fault-tolerant threshold—the point where adding more qubits actually improves computational accuracy rather than increasing errors. Previous quantum systems suffered from the fundamental limitation that adding more qubits typically increased decoherence and error rates, creating a practical ceiling on computational power. This breakthrough effectively removes that ceiling, opening the path to building arbitrarily large, stable quantum computers.
Technical Innovation
The technical innovation centers on quantum error correction codes, specifically the surface code implementation that creates logical qubits from multiple physical qubits. Traditional quantum computing approaches treated each physical qubit as a computational unit, but qubits are notoriously fragile—subject to decoherence from environmental noise, control errors, and quantum state collapse. The surface code approach arranges physical qubits in a two-dimensional lattice where multiple qubits work together to protect quantum information.
Here’s how it works in practical terms: The researchers used 49 physical qubits to create 7 logical qubits with error rates approximately 4 times lower than the individual physical qubits. By implementing repetitive error correction cycles, the system could detect and correct errors in real-time without destroying the quantum information. The key metric—the logical error probability—decreased exponentially with the code distance, confirming theoretical predictions that scaling quantum error correction would eventually produce fault-tolerant quantum computation.
The innovation represents a fundamental architectural shift from trying to build perfect physical qubits to creating robust logical qubits through sophisticated error correction. This approach acknowledges that physical qubits will always be imperfect but demonstrates that through proper encoding and correction, we can build reliable quantum computational units.
Current Limitations vs. Future Potential
Despite this breakthrough, significant challenges remain. The current implementation requires approximately 7 physical qubits per logical qubit, and the error correction overhead remains substantial. The system demonstrated error reduction but hasn’t yet achieved the full fault tolerance needed for large-scale quantum algorithms. Current logical qubit counts remain in the single digits, far from the thousands needed for practical applications.
However, the potential is staggering. Quantum error correction represents the fundamental enabling technology that allows quantum computers to scale beyond niche laboratory demonstrations to practical computational tools. With error correction proven viable, the path forward involves engineering improvements rather than fundamental physics breakthroughs. Companies like IBM, Google, and Microsoft now have clear roadmaps for scaling logical qubit counts while reducing error correction overhead.
The most exciting potential lies in what becomes possible with just 100-1,000 error-corrected logical qubits. Such systems could simulate molecular interactions for drug discovery, optimize complex supply chains, break current cryptographic standards, and solve optimization problems that are completely intractable for classical supercomputers. The transition from physical to logical qubits represents the same fundamental shift as moving from vacuum tubes to transistors in classical computing—it enables scaling that was previously impossible.
Industry Impact
The implications of fault-tolerant quantum computing span virtually every industry sector, with particular transformation expected in these areas:
Pharmaceuticals and Healthcare: Quantum computers will enable accurate simulation of molecular interactions and protein folding, dramatically accelerating drug discovery and development. Companies like Roche and Pfizer are already establishing quantum computing divisions, recognizing that quantum simulation could reduce drug development timelines from years to months and identify treatments for diseases currently considered incurable.
Materials Science: The ability to model complex materials at quantum levels will revolutionize battery technology, semiconductor design, and renewable energy materials. Quantum simulations could identify superconducting materials that work at room temperature, develop more efficient photovoltaic cells, or create lighter, stronger alloys for aerospace applications.
Finance and Risk Management: Quantum optimization algorithms will transform portfolio management, risk assessment, and trading strategies. JPMorgan Chase and Goldman Sachs are investing heavily in quantum computing research, recognizing that quantum algorithms could optimize billion-dollar portfolios in minutes rather than days and model financial systems with unprecedented accuracy.
Logistics and Supply Chain: The traveling salesman problem and similar optimization challenges become tractable with quantum computing. Companies like Amazon and Maersk could optimize global shipping routes, warehouse operations, and delivery networks with efficiency improvements that translate to billions in cost savings and reduced environmental impact.
Cryptography and Cybersecurity: The arrival of fault-tolerant quantum computing necessitates the transition to quantum-resistant cryptography. The entire digital security infrastructure requires overhauling, creating both massive challenges and opportunities for cybersecurity firms and technology providers.
Timeline to Commercialization
The quantum computing timeline has accelerated significantly with this error correction breakthrough. Based on current roadmaps from leading quantum computing companies and research institutions, we can project:
2024-2026: Demonstration of small-scale fault-tolerant systems with 10-50 logical qubits. These systems will solve academic problems and demonstrate commercial potential but won’t yet outperform classical computers on practical business applications.
2027-2030: Achievement of quantum advantage in specific domains with 100-400 logical qubits. Pharmaceutical companies will begin using quantum computers for molecular simulation, and financial institutions will deploy quantum optimization for specific use cases. This period represents the transition from research to early commercial adoption.
2031-2035: Broad quantum advantage with 1,000+ logical qubit systems. Quantum computing becomes a standard tool in research and development across multiple industries. Quantum computing as a service (QCaaS) becomes widely available through cloud providers.
2036-2040: Fully fault-tolerant universal quantum computers capable of running Shor’s algorithm and other complex quantum algorithms. This marks the mature phase of quantum computing technology, with integration into mainstream business operations.
Strategic Implications
For business leaders, the error correction breakthrough demands immediate strategic action across several dimensions:
Technology Monitoring and Assessment: Establish dedicated quantum computing monitoring teams to track developments and assess relevance to your industry. The pace of advancement has accelerated, and falling behind could create insurmountable competitive disadvantages.
Talent Development and Acquisition: Begin building quantum literacy within your organization and establish relationships with academic institutions producing quantum computing talent. The global shortage of quantum experts means early investment in talent provides significant competitive advantage.
Use Case Identification: Conduct systematic analysis of business operations to identify where quantum computing could provide transformative improvements. Focus on optimization problems, simulation challenges, and data analysis tasks that are currently computationally limited.
Partnership Strategy: Develop relationships with quantum computing hardware providers, software developers, and research institutions. Given the capital intensity of quantum computing development, most organizations will access quantum capabilities through partnerships rather than internal development.
Cryptography Transition Planning: Begin the multi-year process of transitioning to quantum-resistant cryptographic standards. This affects everything from customer data protection to internal communications and requires careful planning and execution.
Future Readiness Assessment: Evaluate your organization’s preparedness for quantum disruption using Future Readiness frameworks. This includes technological infrastructure, organizational agility, strategic foresight capabilities, and innovation culture.
Conclusion
The quantum error correction breakthrough represents the most significant milestone in quantum computing since the first demonstration of quantum supremacy. It transforms quantum computing from an interesting scientific experiment to an inevitable technological revolution with defined commercial applications and timelines. Business leaders who dismiss quantum computing as distant science fiction risk catastrophic competitive displacement, while those who act strategically position themselves to capture enormous value.
The next five years will determine which organizations emerge as quantum leaders and which become quantum casualties. The time for strategic planning and preparation is now—the quantum future is arriving faster than most anticipate, and the organizations that thrive will be those that achieve Future Readiness today.
About Ian Khan
Ian Khan is a globally recognized futurist, bestselling author, and one of the world’s most sought-after technology keynote speakers. His groundbreaking work on Future Readiness has established him as a leading voice in helping organizations navigate technological disruption and harness innovation for competitive advantage. As the creator of the Amazon Prime series “The Futurist,” Ian has brought complex technological concepts to mainstream audiences, demystifying emerging technologies and their business implications.
Ian’s expertise spans quantum computing, artificial intelligence, blockchain, and other transformative technologies that are reshaping industries. His recognition on the Thinkers50 Radar list places him among the world’s most influential management thinkers, acknowledging his pioneering work in technology foresight and innovation strategy. With a track record of accurately predicting technology adoption curves and business impacts, Ian provides organizations with actionable insights that bridge the gap between technological possibility and strategic implementation.
Are you prepared for the quantum computing revolution and other breakthrough technologies that will redefine your industry? Contact Ian Khan today to transform your organization’s approach to innovation and future preparedness. Book Ian for an inspiring keynote presentation on breakthrough technologies, schedule a Future Readiness workshop to develop your innovation strategy, or engage his strategic consulting services for emerging technology adoption and technology foresight advisory. Don’t let technological disruption catch your organization unprepared—partner with one of the world’s leading futurists to future-proof your business today.
by Ian Khan | Nov 13, 2025 | Blog, Ian Khan Blog, Technology Blog
Opening: Why Consumer Packaged Goods Matter in Today’s Tech-Driven Economy
When financial commentator Jim Cramer suggests buying opportunities in consumer packaged goods (CPG) stocks, it’s easy to dismiss this as traditional investment advice in a Silicon Valley-dominated world. But as a technology futurist, I see this as a pivotal moment where legacy industries are being reshaped by digital transformation. The CPG sector—encompassing everything from food and beverages to household products—is undergoing a seismic shift, driven by startups, AI, and changing consumer behaviors. Why does this matter now? Because we’re at an inflection point where technology is not just disrupting CPG but creating new value streams that investors and leaders can’t afford to ignore. In an era where tech stocks often steal the spotlight, the convergence of innovation in CPG presents a rare opportunity for those ready to embrace future readiness.
Current State: The CPG Landscape Amidst Tech Infusion
The CPG industry, once characterized by slow-moving giants, is now a hotbed of activity. Startups are flooding the space, leveraging technology to challenge incumbents. For instance, companies like Impossible Foods and Beyond Meat have used biotech and data analytics to revolutionize plant-based foods, capturing market share from traditional players. Funding trends reflect this surge: in 2023, CPG tech startups raised over $5 billion globally, with a focus on sustainability and personalization. Big data and IoT are enabling real-time supply chain optimizations, while e-commerce platforms have democratized access, allowing small brands to compete with household names. However, challenges persist. Established CPG firms face margin pressures from rising costs and increased competition, with many struggling to adapt their legacy systems to digital demands. This dynamic creates a volatile yet promising environment, where stock valuations may not fully account for tech-driven growth potential.
Analysis: Deep Dive into Implications, Challenges, and Opportunities
The implications of tech disruption in CPG are profound. On one hand, digital transformation is unlocking efficiencies—AI-powered demand forecasting can reduce waste by up to 30%, as seen in companies like Nestlé’s pilot programs. On the other hand, it introduces challenges such as cybersecurity risks and the high cost of integrating new technologies. The startup ecosystem is a key driver here; incubators and venture capital are fueling innovation in areas like smart packaging and personalized nutrition. For example, startups like NotCo use AI to develop plant-based alternatives, disrupting traditional R&D processes. Opportunities abound in hyper-personalization, where data analytics allow brands to tailor products to individual preferences, boosting customer loyalty. Yet, the rapid pace of change means that companies must balance innovation with scalability, or risk being left behind. From an investment perspective, this analysis suggests that CPG stocks with strong tech adoption could outperform, but only if they navigate the pitfalls of digital debt and consumer skepticism.
Ian’s Perspective: A Futurist’s Take on CPG’s Tech Evolution
As a technology futurist, I believe the real opportunity in CPG stocks lies not in short-term gains but in long-term future readiness. Jim Cramer’s advice hints at undervalued assets, but my perspective goes deeper: we’re witnessing the birth of a new CPG paradigm where technology is the core differentiator. Predictions? In the next 2-3 years, I expect a wave of mergers and acquisitions as tech-savvy startups are absorbed by legacy players seeking innovation—think Unilever acquiring digital-native brands to stay relevant. AI will become ubiquitous, with generative AI designing products and optimizing marketing, potentially increasing ROI by 20-40% for early adopters. However, I caution against blind optimism; companies that fail to invest in digital literacy and ethical AI could face backlash. My unique take is that the CPG sector’s resilience—rooted in everyday consumer needs—makes it a fertile ground for tech integration, but success hinges on embracing a culture of continuous innovation rather than reactive measures.
Future Outlook: What’s Next for CPG in the Tech Era
1-3 Years: Acceleration and Consolidation
In the near term, expect accelerated adoption of AI and machine learning in supply chains and customer insights. Startups will drive niche innovations, such as blockchain for traceability, addressing consumer demands for transparency. Funding may shift towards sustainability-focused ventures, with ESG criteria influencing stock performance. Challenges include regulatory hurdles and talent shortages in tech roles, but opportunities lie in leveraging data to create predictive business models.
5-10 Years: Transformation and New Norms
Looking further ahead, CPG will evolve into a tech-integrated ecosystem. Imagine smart kitchens where IoT devices reorder groceries automatically, or bioprinting enabling customized food products at home. Industry disruption could lead to the rise of “phygital” brands that blend physical and digital experiences seamlessly. Long-term, companies that master digital twins and quantum computing for R&D will lead, but they must address ethical concerns like data privacy and job displacement. The CPG stock landscape may reward those who pivot from product-centric to platform-centric models.
Takeaways: Actionable Insights for Business Leaders
- Embrace Digital Fluency: Invest in upskilling teams to understand AI and data analytics, ensuring your organization can leverage tech for competitive advantage without relying solely on external acquisitions.
- Focus on Sustainability and Personalization: Integrate ESG goals into core strategies, as consumers and investors increasingly favor brands that offer transparent, customized solutions. Use data to drive these initiatives, reducing risk and enhancing loyalty.
- Monitor Startup Ecosystems: Keep a pulse on emerging CPG tech startups for partnership or investment opportunities. This can provide early access to innovation and mitigate disruption risks.
- Build Agile Supply Chains: Implement IoT and AI for real-time adaptability, preparing for volatile market conditions and shifting consumer preferences.
- Prioritize Ethical Tech Use: Develop frameworks for responsible AI and data handling to build trust and avoid reputational damage, which can impact stock stability in the long run.
Ian Khan is a globally recognized technology futurist, voted Top 25 Futurist and a Thinkers50 Future Readiness Award Finalist. He specializes in AI, digital transformation, and future readiness, helping organizations navigate technological shifts.
For more information on Ian’s specialties, The Future Readiness Score, media work, and bookings please visit www.IanKhan.com
