In July 2024, a single faulty software update from CrowdStrike brought down airlines, hospitals, and banks worldwide, costing the global economy close to $10 billion in just one day. This wasn't a cyberattack or natural disaster. It was a routine security update that exposed how fragile our interconnected business operations have become.
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2025 had its share of hard hits on operational resiliency, presenting companies and consumers around the world with a terrifying scenario involving one of the world’s most reliable companies. 
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The CrowdStrike incident joined a growing list of operational failures that defined 2024 and 2025: Change Healthcare's $872 million cyberattack, widespread supply chain disruptions from Red Sea shipping crises, the October 2025 AWS outage that sent down a broad range of online services, including financial, food delivery, streaming and social media platforms, and countless smaller incidents collectively cost businesses trillions of dollars. These weren't one-off failures — they were symptoms of a rapidly evolving risk landscape that traditional operational risk management frameworks struggle to address.
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As we prepare for 2026, the stakes have never been higher. Adoption of AI, climate change acceleration, and geopolitical tensions are creating new categories of operational risk that didn't exist just five years ago. The companies that survive and thrive will be those that can anticipate, prevent, and rapidly recover from operational disruptions.

What will the sources of operational risk be in 2026?
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What will make 2026 different is the speed and scale at which operational risks can materialize. The AWS outage demonstrated how a single point of failure could instantly impact nearly every cloud-based company and service worldwide. Similarly, the Change Healthcare attack didn't just affect one company; it disrupted prescription processing for patients across America for weeks.
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This interconnectedness creates what risk management experts call "systemic operational risk", where failures in one organization or system can trigger cascading effects across entire industries or regions. Understanding and managing these interdependencies is now critical for any comprehensive operational risk management strategy.
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The evolution of operational risk
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Twenty years ago, operational risk was largely contained within organizational boundaries. A process failure affected one department. A system outage impacted one location. Human error had a limited scope. Today's operational risks cascade across networks, industries, and continents in minutes.
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Consider how the traditional four pillars of operational risk have evolved:
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People: Your workforce now includes remote employees across multiple time zones, gig economy contractors, AI-augmented roles, and critical dependencies on individuals with highly specialized skills that may be impossible to replace quickly.
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Processes: Business processes now span multiple cloud platforms, integrate with dozens of third-party systems, rely on automated decision-making, and must comply with an ever-changing web of international regulations.
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Systems: Your technology stack includes legacy systems, cloud infrastructure, mobile applications, IoT devices, AI models, and APIs that connect to hundreds of external services, each representing a potential point of failure.
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External events: Beyond traditional concerns like natural disasters, modern businesses face cyber warfare, supply chain weaponization, rapid regulatory changes, social media-driven reputation crises, and climate events that are becoming more frequent and severe.
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What are the different types of operational risks?

Modern operational risk management must account for several new risk categories that barely existed a decade ago. Here is an excerpt from Allianz’s Risk Barometer for 2025: 

Source: Allianz

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In summary – and our assessment – the top operational risks for 2026 and beyond will broadly fall into one of these categories: 
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Digital ecosystem risk: Your organization's dependence on cloud providers, SaaS platforms, APIs, and digital supply chains creates vulnerabilities that extend far beyond your direct control.

Artificial Intelligence risk: As businesses increasingly rely on AI for decision-making, new risks emerge around algorithmic bias, model drift, training data quality, and the potential for AI systems to make catastrophic errors at scale.
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Climate operational risk: Extreme weather events are no longer rare exceptions but regular occurrences that businesses must plan for, and often in unpredictable locations previously deemed safe. These events affect not just physical assets but also employee availability, supplier operations, and customer demand patterns.
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Supply chain and other business disruptions: As companies operate in an interconnected global economy, a single disruption in a critical node — whether a port closure, semiconductor shortage, logistics breakdown, or a political upheaval  — can cascade through entire industries, exposing the fragility of just-in-time inventory systems and concentrated supplier dependencies.

Advanced prevention strategies for 2026

As operational risks become more complex and interconnected, prevention strategies must evolve beyond traditional approaches. Here are the advanced frameworks that leading organizations are implementing to stay ahead of emerging risks.

Managing digital ecosystem/cyber security risks
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Implement comprehensive zero-trust frameworks that assume no system or user can be trusted by default:

• Require multi-factor authentication for all system access
• Implement least-privilege access controls
• Continuously verify and validate all users and devices
• Segment networks to limit lateral movement
• Monitor all network traffic and user behavior
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Healthcare-specific cybersecurity frameworks: 

• Implement HIPAA-compliant incident response procedures
• Establish secure communication channels for patient care coordination
• Create offline backup systems for critical patient data
• Develop procedures for maintaining patient care during system outages
• Train staff on cybersecurity practices specific to healthcare workflows
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Prioritize patient care continuity and safety:  

• Establish manual processes for medication dispensing
• Create paper-based patient record systems as backups
• Implement secure communication methods for care coordination
• Develop partnerships with unaffected healthcare networks
• Train clinical staff on emergency procedures that don't rely on digital systems
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Maintain compliance even during operational disruptions:

• Establish procedures for timely breach notification
• Create documentation processes that meet regulatory requirements
• Implement secure data recovery procedures
• Develop communication plans for regulatory authorities
• Ensure business associate agreements address incident response
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Artificial Intelligence risk prevention strategies 
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Establish comprehensive governance for AI systems:

• Define clear accountability structures for AI decision-making
• Implement model validation and testing protocols
• Create audit trails for all AI-driven decisions
• Establish performance monitoring and drift detection
• Develop procedures for AI model updates and rollbacks
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Model validation and testing protocols

• Implement comprehensive backtesting with historical data
• Conduct stress testing under extreme market conditions
• Validate model performance across different market regimes
• Test for potential bias and fairness issues
• Establish ongoing monitoring of model accuracy and reliability
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Maintain human oversight over AI systems:

• Define decision thresholds that require human approval
• Implement circuit breakers for unusual AI behavior
• Train staff to understand and override AI recommendations when necessary
• Create escalation procedures for AI system anomalies
• Establish regular human review of AI decision patterns
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Climate-related disruption risk prevention strategies
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Develop comprehensive climate risk assessments and scenario plans:

• Model potential climate impacts on your specific locations and operations
• Ensure spotless mass communication and evacuation plans 
• Assess both acute risks (extreme weather events) and chronic risks (gradual climate changes)
• Create scenario plans for different climate outcomes
• Regularly update assessments based on the latest climate science
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Invest in physical resilience: infrastructure that can withstand climate impacts:

• Upgrade facilities to meet future climate conditions, not just current standards
• Implement renewable energy and backup power systems
• Create flood-resistant and fire-resistant facility designs
• Invest in climate-controlled storage for temperature-sensitive operations
• Develop mobile or distributed operations capabilities, and communication networks to accompany them
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Align insurance coverage with evolving climate risks:

• Regularly review and update coverage for climate-related losses
• Understand exclusions and limitations in current policies
• Consider parametric insurance for weather-related business interruption
• Evaluate self-insurance options for predictable climate impacts
• Work with insurers to understand changing risk assessments
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Supply chain and other business disruption risk prevention strategies
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Develop comprehensive supplier diversification strategies:

• Map all critical supply chain dependencies
• Identify single points of failure in sourcing
• Establish relationships with suppliers in multiple geographic regions
• Create supplier scorecards that include geopolitical risk factors
• Implement regular supply chain stress testing
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Build systematic approaches to evaluating geopolitical risks:

• Monitor political stability indicators in key sourcing regions
• Assess transportation route vulnerabilities
• Evaluate regulatory risks in different jurisdictions
• Create early warning systems for emerging geopolitical threats
• Develop scenario planning for various geopolitical disruptions
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Create flexible logistics networks that can adapt to disruptions

• Establish relationships with multiple shipping providers
• Pre-negotiate alternative transportation routes
• Invest in regional distribution centers to reduce long-distance shipping dependencies
• Develop air freight capabilities for critical components
• Create inventory positioning strategies that account for longer lead times
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Balance cost efficiency with resilience:

• Calculate optimal safety stock levels for different risk scenarios
• Identify which products justify higher inventory investments
• Implement demand forecasting that accounts for supply disruption risks
• Create flexible inventory financing arrangements
• Develop supplier-managed inventory programs that include risk sharing
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Risk prevention tools and frameworks for 2026
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The good news? As the operational risks have become more complex and interconnected, so has the technology followed. Here are the advanced tools and frameworks that leading organizations are implementing to stay ahead of emerging risks:
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AI-powered risk management
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Artificial intelligence is transforming risk management from reactive to predictive, enabling organizations to identify and address operational risks before they materialize.
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Predictive risk analytics

Modern AI systems can analyze vast amounts of operational data to predict where failures are likely to occur:

• Machine learning models that identify patterns in historical incident data
• Predictive maintenance algorithms that identify equipment likely to fail
• Network analysis that identifies critical nodes and potential cascade effects
• Behavioral analytics that detect anomalous activities that could indicate fraud or errors
• Natural language processing that analyzes employee feedback, customer complaints, and external news for early warning signals

Automated monitoring systems

AI-powered risk monitoring can watch for risk indicators 24/7 across all business operations:

• Real-time analysis of system performance metrics
• Automated detection of unusual transaction patterns
• Continuous monitoring of third-party service performance
• Analysis of social media and news sources for reputation risks
• Integration of internal and external data sources for comprehensive risk visibility
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There are, of course, implementation considerations. Successfully deploying AI for risk management requires careful planning:

• Start with well-defined use cases where AI can add clear value
• Ensure data quality and governance standards are in place
• Maintain human oversight and interpretation of AI recommendations
• Build explainable AI models that can justify their risk assessments
• Create feedback loops to continuously improve AI model accuracy

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Resilience-by-design principles
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Rather than trying to prevent all operational failures, resilience-by-design focuses on building systems that can continue operating despite failures.
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Building antifragile operations

Antifragile systems don't just survive disruptions — they get stronger from them:

• Design redundancy that activates automatically during failures
• Create feedback loops that help systems adapt to new conditions
• Build in excess capacity that can handle unexpected loads
• Implement graceful degradation that maintains core functions during partial failures
• Establish rapid learning cycles that incorporate lessons from each incident
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Stress testing methodologies

Regular stress testing helps identify vulnerabilities before they're exposed to real events:

• Conduct "game days" that simulate various failure scenarios
• Test recovery procedures under realistic time and resource constraints
• Validate that backup systems actually work when primary systems fail
• Challenge assumptions about how different systems will interact during failures
• Include human factors and decision-making under pressure in stress tests
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Cultural and human factors

Technology and processes are only as strong as the people who operate them. Building operational resilience requires creating cultures that support good risk management.
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Risk culture in remote and hybrid environments: Distributed workforces create new challenges for risk culture that require intentional effort to overcome. Organizations must establish clear communication channels for reporting risks and incidents while creating virtual "safety moments" in team meetings to discuss operational risks.
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It's essential to ensure remote workers understand their roles in risk management and have clear processes and channels for fulfilling those roles. Above all, fostering psychological safety is critical so employees feel comfortable reporting mistakes without fear of reprisal.
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Employee engagement in risk management: Organizations should create incentive structures that reward proactive risk identification and establish suggestion systems for operational improvements. Recognizing and celebrating employees who prevent incidents reinforces the importance of vigilance and attention to risk. Providing clear escalation paths for risk concerns ensures that potential issues are addressed quickly and effectively before they can escalate into major problems.

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Building your 2026 risk assessment program — a 90-Day quick start guide
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Implementing a modern operational risk management program can seem overwhelming, but a phased approach makes it manageable while delivering value early on.
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Days 1-30: Foundation building
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Current State Assessment: Understanding where you are is essential before planning where to go:

• Inventory all existing risk management processes and procedures
• Catalog all current risk monitoring systems and data sources
• Interview key stakeholders to understand current risk concerns
• Review recent incidents to identify patterns and gaps
• Benchmark current capabilities against industry standards
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Stakeholder Alignment: Success requires buy-in from across the organization:

• Present business case for operational risk management to senior leadership
• Identify and engage key stakeholders in each business unit
• Establish risk management governance structure and communication plans
• Define roles and responsibilities for risk management activities
• Create project charter and timeline for risk management program implementation
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Technology Evaluation: Assess your technology needs and options:

• Evaluate current systems' ability to support modern risk management
• Research risk management platforms and tools that fit your needs and budget
• Assess data integration requirements and challenges
• Plan for any necessary infrastructure upgrades
• Develop technology implementation timeline and budget
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Quick Wins Identification: Identify improvements that can be implemented quickly:
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• Fix obvious control gaps that can be addressed immediately
• Implement basic risk reporting for senior management
• Establish incident reporting and tracking procedures
• Create risk awareness communication for all employees
• Begin tracking key risk indicators that are already available
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Days 31-60: Core implementation
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Framework Deployment: Begin implementing your chosen risk management framework:

• Deploy risk assessment methodology across pilot business areas
• Implement risk monitoring procedures for critical processes
• Establish risk treatment prioritization and approval processes
• Create risk reporting templates and communication procedures
• Begin training key personnel on new risk management procedures
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Tool Integration: Implement selected technology solutions:

• Deploy chosen risk management platform in pilot areas
• Integrate risk management tools with existing business systems
• Establish data feeds from operational systems to risk management platform
• Create user access controls and security procedures
• Begin populating risk management systems with initial data
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Training Program Launch: Ensure personnel have necessary skills and knowledge:

• Develop role-specific training programs for different user groups
• Create risk awareness training for all employees
• Establish ongoing training and certification requirements
• Develop internal expertise in risk management tools and procedures
• Create user guides and reference materials
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Initial Monitoring Setup: Begin systematic risk monitoring:

• Implement key risk indicator tracking for critical risks
• Establish risk dashboard and reporting procedures
• Begin regular risk assessment cycles
• Create escalation procedures for significant risk events
• Start collecting baseline data for performance measurement
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Days 61-90: Optimization and scaling
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Performance Measurement: Evaluate how well your initial implementation is working:

• Measure key performance indicators against established targets
• Collect feedback from users on system usability and effectiveness
• Assess whether risk reporting is providing actionable insights
• Evaluate whether risk treatments are reducing actual risk levels
• Compare actual implementation costs against budgeted amounts
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Process Refinement: Improve procedures based on initial experience:

• Refine risk assessment procedures based on user feedback
• Adjust risk reporting frequency and content based on stakeholder needs
• Streamline risk treatment approval and implementation processes
• Improve integration between risk management and business planning
• Enhance training programs based on user experience and questions
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Advanced Feature Deployment: Implement more sophisticated capabilities:

• Deploy predictive analytics and early warning systems
• Implement automated risk monitoring and alerting
• Integrate risk management with business continuity planning
• Establish advanced reporting and analytics capabilities
• Begin using risk information for strategic decision-making
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Continuous Improvement Setup: Establish processes for ongoing enhancement:

• Create regular review cycles for risk management framework effectiveness
• Establish procedures for incorporating lessons learned from incidents
• Create mechanisms for capturing and implementing improvement suggestions
• Develop capabilities for adapting to changing business conditions
• Plan for scaling risk management program to additional business areas
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Emerging risk horizons
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As we look beyond 2026, several emerging trends will reshape operational risk management. Organizations that prepare for these changes now will be better positioned to adapt as they arrive.
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Quantum computing threats: Quantum computing will eventually render current encryption methods obsolete, creating new cybersecurity and operational risks:

• Begin planning for post-quantum cryptography migration
• Assess which systems and data would be most vulnerable to quantum attacks
• Monitor quantum computing development timelines
• Develop relationships with cybersecurity vendors preparing for the quantum era
• Create long-term data protection strategies that account for quantum threats
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Climate tipping point impacts: Climate science suggests we may reach irreversible tipping points that could create unprecedented operational disruptions:

• Model potential impacts of various climate tipping point scenarios
• Assess business model sustainability under accelerated climate change
• Develop adaptation strategies for different climate outcomes
• Create partnerships and investments that build climate resilience
• Plan for potential mass migration and resource scarcity impacts

Geopolitical fragmentation: Increasing international tensions may lead to more fragmented global systems:

• Assess dependencies on cross-border systems and relationships
• Develop contingency plans for various trade restriction scenarios
• Create domestic or regional alternatives to global dependencies
• Build relationships that can survive geopolitical tensions
• Plan for potential internet fragmentation and digital trade barriers

Technological singularity considerations: While still theoretical, the potential for artificial general intelligence creates planning challenges. While we wrote about addressing some of this above, consider hiring specialists who can be in charge of following and anticipating AGI trends.

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Conclusion

The operational risk landscape has fundamentally changed. The traditional approach of managing risks in isolation, with annual assessments and static controls, is no longer sufficient in our interconnected, rapidly evolving business environment.
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The failures of 2024 and 2025 — from CrowdStrike's global outage to the AWS failure — demonstrate that operational risks now cascade across industries and continents in minutes. But they also provide us with lessons about prevention, preparation, and response.
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The organizations that will thrive in 2026 and beyond are those that embrace operational risk management as a strategic capability, not just a compliance requirement. They will:
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• Think systematically about interconnected risks rather than managing individual threats in isolation
• Invest in prediction rather than just protection, using AI and advanced analytics to anticipate problems before they occur
• Build resilience into their operations, designing systems that can continue functioning despite failures
• Learn continuously from their own experiences and those of others, adapting their approaches as new risks emerge
• Engage everyone in risk management, making it part of the organizational culture rather than leaving it to specialists
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The framework and strategies outlined in this guide provide you with the foundation for modern operational risk management. But remember that this is just the beginning. The most important step is to start—to begin building the capabilities, relationships, and mindsets that will serve you well regardless of what specific risks the future brings.
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Your competitors are still using yesterday's risk management approaches for tomorrow's challenges. By implementing the strategies in this guide, you can build sustainable competitive advantages through superior operational resilience.
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The question isn't whether new operational risks will emerge, it's whether you'll be ready for them when they do.

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