Understanding Disruption in the Age of AI
Every business faces the risk of disruption, but for a company driven by artificial intelligence, the stakes are uniquely high. A crisis won’t wait for you to get ready. Your core assets are not just servers and software; they are vast datasets, complex models, and intricate algorithmic processes. These assets are both incredibly valuable and acutely vulnerable. When things go wrong, you need a plan that understands this unique landscape. This is where ISO 27001 Annex A 5.29 Information security during disruption provides a critical framework, guiding you to protect your most important assets when you are at your most vulnerable.
ISO 27001 Annex A 5.29 is a control designed to ensure you have a clear and effective plan to maintain information security at an appropriate level during a disruptive event. This could be anything from a sophisticated cyberattack or cloud provider outage to the loss of key personnel, a supply chain failure, or a physical disaster like a fire or flood. Its core purpose is to integrate information security directly into your broader business continuity and disaster recovery planning, ensuring that security is a fundamental component of your response, not an afterthought. This makes the control both preventative, as it forces you to plan ahead, and corrective, as it defines how you respond and restore security when an incident occurs.
The control requires you to build a plan that can withstand pressure. Based on the guidance in ISO 27001, this involves several key requirements:
- Planning for Security: This is about proactive preparation, not reactive panic. You must think through how your information security will be upheld during a crisis. This means planning in advance how to protect your data’s confidentiality and integrity when your normal operational environment is compromised.
- Maintaining Existing Controls: A disruption doesn’t suspend your standard security obligations. Your plan must ensure that fundamental security measures, such as access controls, encryption, and monitoring, continue to function as intended. If a control cannot be maintained, its absence must be a conscious, risk-assessed decision.
- Using Compensating Controls: When primary security controls are unavailable, you cannot simply operate without them. The standard requires you to have pre-planned, secure alternatives (often called fallback or compensating controls) ready to deploy. These ensure that security gaps are not left open while you work to restore normal operations.
For a typical business, these requirements are a matter of good practice. For a business built on AI, they present specific and significant challenges that demand a more specialised approach.
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The Unique Risks AI Companies Face with Disruption
Understanding your specific risk profile is the first step toward effective compliance and genuine operational resilience. A generic business continuity plan is not enough when your operations are far from generic. For AI-driven businesses, a disruption can threaten the very foundations of your competitive advantage and operational integrity. Let’s analyse the three most critical disruption risks that are unique to your field.
Exposure of Sensitive Training Datasets
During a crisis, you may need to switch to backup systems, alternative data centres, or manual operational processes. This transition creates a significant risk that your proprietary training data could be exposed, corrupted, or lost. This data is often the lifeblood of your AI models, and its exposure could lead to a catastrophic loss of competitive advantage. If the dataset contains personal information, a breach could also result in severe regulatory fines. This directly threatens the confidentiality of your intellectual property and the integrity of your future models.
Disruption of Algorithmic Processes
A major disruption can affect more than just your infrastructure; it can break the core algorithmic workflows of model training, validation, or inference. When you activate fallback systems, they may not have the same processing capabilities as your primary environment. This creates a serious risk that your model outputs could be altered, potentially compromising the integrity of your service. For your customers, this could mean receiving untrustworthy results, eroding their confidence in your platform. This scenario critically undermines the integrity of your algorithmic processes and threatens the availability of a reliable service.
Vulnerabilities in the AI Supply Chain
Modern AI development rarely happens in isolation. You likely rely on a complex supply chain of third-party data providers, pre-trained models, and specialised cloud services. A disruption at one of your key suppliers can have a cascading effect on your own operations. Your continuity plan must therefore account for maintaining security when a critical external dependency fails. This risk vector can compromise all three pillars of information security: a supplier breach threatens confidentiality, a compromised data feed corrupts integrity, and a service outage impacts availability.
Understanding these vulnerabilities is the critical first step; the next is to build a concrete, actionable plan to mitigate them.
Your Blueprint for Compliance: Actionable Steps for AI Businesses
Resilience isn’t defined by how you operate in the quiet; it’s proven when you must stand up secure as everything changes. Complying with Annex A 5.29 is not about creating shelf-ware; it is about embedding resilience into the heart of your business so you can protect your assets and maintain trust, even in the most challenging circumstances. This section provides a practical, actionable guide to building that resilience.
Develop AI-Centric Continuity Plans
Your first step is to create or update your Business Continuity Plan (BCP) and Disaster Recovery Plan (DRP) to specifically address the AI risks we have just identified. Do not rely on generic templates. Your plans must document the exact procedures for:
- Securing training data: How will you protect datasets during a failover to a secondary site? What encryption standards will be maintained?
- Validating algorithmic integrity: What tests will you run to ensure your models are producing reliable outputs on backup systems?
- Managing supplier outages: What are your communication protocols and alternative arrangements if a critical third-party service fails?
Documenting these AI-specific scenarios is essential for demonstrating compliance and ensuring your team knows precisely what to do during a real event.
Define and Document Your Fallback Controls
When a primary control fails during a disruption, you need a secure, pre-planned alternative. These are known as “compensating” or “fallback” controls. You must define these in advance so that your response is systematic, not improvised. The following table provides practical examples relevant to a technology or AI company.
| Scenario | Primary Control (Normal Operations) | Secure Fallback Control (During Disruption) |
|---|---|---|
| Access to Critical Systems | Single Sign-On (SSO) with MFA | Pre-configured, documented emergency admin accounts |
| Remote Developer Access | Corporate VPN with strict policies | Secure 5G dongles with an embedded corporate firewall |
| Data Processing Pipeline | Automated, encrypted database connection | Documented, secure manual process with data stored in a locked, secure location |
Clearly documenting these fallbacks ensures that security standards are upheld even when your normal operational tools are unavailable.
From Paper Plans to Demonstrable Proof
A plan on paper is only a hypothesis. It’s no longer enough to parade policies in front of an auditor; your ability to protect information during chaos is your credibility in action. You must regularly test your disruption plans through simulations that walk through different scenarios, such as a cloud provider outage or a key data pipeline failure.
The modern compliance question is this: can you quickly show evidence of your security posture on demand, even while scrambling to recover? Auditors, partners, and clients now expect live proof that controls are functioning. You must be able to produce access logs, records of fallback controls being activated, and clear evidence of team handovers. This cycle of testing, documenting, and improving is what transforms a simple compliance document into a living, effective resilience strategy that provides demonstrable proof, not just promises.
While these steps are essential, having the right structure and tools can dramatically simplify the process of building and maintaining your plans.
The Solution: Achieving Resilient Compliance with High Table
Achieving robust, auditable compliance for Annex A 5.29 does not have to be an overwhelming task built from scratch. The challenges of documenting policies, defining controls, and creating testable plans can be streamlined with an expert-designed framework. High Table provides a practical toolkit to help you build a resilient information security programme that is tailored to your business needs.
The High Table ISO 27001 Toolkit
The High Table ISO 27001 Templates Toolkit provides the essential governance structure, policies, and templates you need to satisfy the requirements of Annex A 5.29. This toolkit directly addresses the challenges discussed earlier by providing a ready-made foundation that you can tailor to your specific AI workflows. Its templates for a Business Continuity Policy, Business Continuity Plan (BCP), and Disaster Recovery Plan (DRP) ensure you have the core documentation in place, allowing you to focus on adapting it to the unique risks of your AI operations.
You can find the toolkit here: https://hightable.io/product/iso-27001-templates-toolkit/
Why a Toolkit is the Right Approach for a Modern AI Company
For a fast-moving AI company, efficiency and control are paramount. A template-based toolkit offers the perfect balance of expert guidance and complete customisation. Instead of forcing your innovative processes into a rigid, one-size-fits-all framework, these templates provide a best-practice structure that you can adapt. This allows you to build plans that precisely fit your unique AI infrastructure, data pipelines, and supply chain dependencies. The result is a set of security measures that are both practical and effective, giving you full ownership and control over your compliance documentation and, ultimately, your operational resilience.
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Conclusion: From Compliance Box-Ticking to True Resilience
For an AI company, complying with ISO 27001 Annex A 5.29 is more than just a regulatory hurdle; it is a strategic necessity for protecting your most valuable assets. In a world of increasing threats, your ability to maintain information security during a disruption is fundamental to your long-term success, customer trust, and competitive edge.
Building this capability does not have to be a daunting journey. By understanding your unique risks, developing AI-centric plans, and embracing a cycle of continuous testing, you can move beyond simple box-ticking. The High Table toolkit provides a clear and efficient path, enabling you to achieve auditable compliance and, more importantly, to secure your innovative operations against the inevitable disruptions of the modern world.
About the author
Stuart Barker is a veteran practitioner with over 30 years of experience in systems security and risk management.
Holding an MSc in Software and Systems Security, Stuart combines academic rigor with extensive operational experience. His background includes over a decade leading Data Governance for General Electric (GE) across Europe, as well as founding and exiting a successful cyber security consultancy.
As a qualified ISO 27001 Lead Auditor and Lead Implementer, Stuart possesses distinct insight into the specific evidence standards required by certification bodies. He has successfully guided hundreds of organizations – from high-growth technology startups to enterprise financial institutions – through the audit lifecycle.
His toolkits represents the distillation of that field experience into a standardised framework. They move beyond theoretical compliance, providing a pragmatic, auditor-verified methodology designed to satisfy ISO/IEC 27001:2022 while minimising operational friction.
