ISO 27001 Annex A 5.30 ICT readiness for business continuity is a control that ensures your organisation’s critical technology services can withstand and recover from a disruptive incident. In simple terms, its purpose is to make sure you have a solid backup plan for your Information and Communication Technology (ICT) so that your essential information and assets remain available even when things go wrong. While this is a vital requirement for all modern organisations, as an AI company, you face unique and significant challenges. Your reliance on complex data, proprietary models, and intricate algorithmic processes means that meeting the requirements of A.5.30 demands a more specialised and strategic approach.
Table of contents
Understanding the Foundations of ICT Readiness
Before we analyse the unique challenges your AI business faces, it is crucial to understand the core components of Control A.5.30. This section provides the essential groundwork for building a resilient compliance strategy, ensuring you have a firm grasp of the fundamental concepts that underpin any effective ICT continuity plan.
What is Annex A 5.30?
ISO 27001 Annex A 5.30 requires that your organisation’s ICT readiness is planned, implemented, maintained, and tested in line with your business continuity objectives. Its primary purpose is to ensure the availability of your information and other associated assets during a disruption. Think of it as your organisation’s formal “backup plan” for its technology infrastructure, designed to protect your critical business functions and enhance your overall business resilience when faced with an incident.
Core Concepts You Need to Know
The implementation of this control is built upon a few key concepts. Understanding them is the first step toward compliance.
- Business Impact Analysis (BIA): A Business Impact Analysis, or BIA, is the starting point for this control. It is the process you undertake to identify your most critical business activities and understand the impact a disruption would have on them over time. The BIA helps you prioritise which systems and processes need to be recovered first and informs the resources required to do so.
- Recovery Time Objective (RTO): The Recovery Time Objective, or RTO, is the target time within which a business process must be restored after a disaster or disruption to avoid unacceptable consequences associated with a break in business continuity. In essence, it answers the question: “How long until the system is back UP?”. For example, an RTO of four hours means a critical system must be operational again within that timeframe.
- Recovery Point Objective (RPO): The Recovery Point Objective, or RPO, defines the maximum acceptable amount of data loss an organisation can tolerate, measured in time. It addresses the question: “How much data can we afford to lose?”. For instance, an RPO of one hour means that in the event of a disruption, data loss should not exceed the last hour’s worth of transactions or information.
While these concepts are universal, their application within an AI environment becomes significantly more complex.
The AI Challenge: Why A.5.30 Is Different for You
For AI-driven organisations, the core assets are not just traditional data but also proprietary algorithms, vast and valuable training datasets, and complex data processing pipelines. These elements present unique and critical points of failure that demand special consideration. This section will analyse the specific, high-stakes risks you face when applying the principles of Annex A 5.30 to your unique AI workflows.
Disruption to Model Training and Data Processing
A disruption to your AI model training and data processing pipelines presents a severe risk. These pipelines are the lifeblood of your innovation, and an incident could lead to the permanent loss or exposure of sensitive and immensely valuable training datasets. The strategic impact of such an event is multifaceted: it could trigger a catastrophic data loss scenario with a severe RPO, hand a significant advantage to your competitors, and cause lasting reputational damage with your clients and stakeholders.
Disruption to Algorithmic and Inference Processes
For many AI businesses, the inference model is the product. If your core algorithmic and inference processes are unavailable, your service is down. This directly translates to immediate financial losses, contractual penalties, and a breakdown in customer trust. The direct link between the availability of these processes and revenue means they often have a very short, and demanding, Recovery Time Objective (RTO) that must be meticulously planned for.
Vulnerabilities in the AI Supply Chain
The AI ecosystem is highly interconnected, creating unique business continuity risks within your supply chain. Your organisation may depend on third-party data sources for model training, pre-trained models from other vendors, or specialised cloud computing services designed for high-performance AI workloads. These external dependencies create points of failure that are outside your direct control but must still be accounted for in your ICT continuity plan, a principle that connects directly to controls like A.5.21 (Managing information security in the ICT supply chain).
Understanding these unique risks is the first step; now let’s explore the practical actions you can take to mitigate them.
Your Action Plan: Practical Steps for AI Compliance
Achieving compliance with ISO 27001 is not about theory; it is about taking concrete, documented actions to protect your business. This section provides a clear, step-by-step guide that transforms the requirements of Annex A 5.30 into an actionable implementation plan tailored specifically for the needs of an AI-driven organisation.
- Conduct an AI-Specific Business Impact Analysis (BIA)
Your first step is to perform a BIA that moves beyond traditional IT assets. You must specifically identify the criticality of your AI models, unique training datasets, inference endpoints, and the specialised infrastructure that supports them. This means quantifying the financial impact per hour of your primary inference API being offline, or the reputational damage from the loss of a proprietary pre-processing algorithm. This analysis will form the foundation of your entire ICT continuity strategy. - Develop a Tailored ICT Continuity Plan
Based on your BIA, create a documented plan (often called a Disaster Recovery Plan) that outlines the exact procedures for restoring your critical AI systems. This plan is not a theoretical document; it must include clearly defined roles, responsibilities, and a strong chain of command to ensure that competent individuals can make authoritative decisions quickly during a crisis. - Define Realistic RTOs and RPOs for AI Assets
For each of your critical AI components, establish and document specific Recovery Time Objectives (RTOs) and Recovery Point Objectives (RPOs). For example, determine the maximum tolerable downtime for your production inference model (RTO) and the maximum acceptable data loss from your primary training data repository (RPO). - Implement Robust Backup and Recovery Procedures
Put in place strong, resilient backup solutions for both your critical data and your proprietary models. This includes version-controlled backups of not just your production models but also the specific container environments they run in. Your procedures should be clearly documented and cover scenarios like restoring a model to a new cloud region or virtual environment to ensure they can be performed reliably under pressure. - Test and Review Your AI Recovery Scenarios
An untested plan is not a plan; it is a theory. One of the most common failures in business continuity is inadequate testing. You must regularly test your recovery procedures. Instead of a generic data restore test, conduct a full-scale simulation: Can your team successfully re-deploy a critical inference model from backup to a secondary cloud provider within its RTO? Can you validate the integrity of a restored training dataset against its original hash values? Document the results of these tests and use any lessons learned to continually improve and update your plan.
Managing this web of AI-specific plans, tests, and documentation demands a structured system, which is where a dedicated toolkit becomes essential.
The Solution: Streamlining Compliance with the High Table Toolkit
Achieving and maintaining compliance with Annex A 5.30 doesn’t have to mean starting from scratch with a blank page. Using a specialised toolkit can provide the necessary structure, expert guidance, and documentation templates to protect your AI business effectively and efficiently. The High Table ISO 27001 Toolkit is designed to provide exactly this kind of support.
How the High Table Toolkit Addresses Your AI Risks
The High Table ISO 27001 Toolkit provides the specific documentation you need to meet the requirements of Annex A 5.30, allowing you to focus on tailoring the content to your unique AI risks.
- Business Impact Analysis (BIA) Templates: The toolkit includes templates to guide you through conducting a thorough BIA, ensuring you don’t overlook critical AI assets like models, data pipelines, or specialised infrastructure during your assessment.
- Business Continuity and Disaster Recovery Plans: The toolkit provides expert-written policy and plan documents that give you the exact structure required for your ICT continuity strategy. This saves you hundreds of hours of research and writing, providing a solid foundation to build upon.
- Integrates ICT Continuity into Your ISMS: The toolkit helps you build a comprehensive Information Security Management System (ISMS) where ICT readiness is not an afterthought but a core, documented component of your overall security posture.
Why a Toolkit is the Smart Choice for Your AI Business
For a dynamic AI company, a toolkit offers the perfect balance of structure and flexibility. The templates provide a solid, compliant foundation that is already aligned with ISO 27001 requirements. At the same time, they are fully customisable, giving you complete control and ownership over your compliance documentation. This ensures your ICT continuity plan perfectly fits your unique AI processes and risks, without the rigidity or high cost of other approaches.
Own Your ISMS, Don’t Rent It
Do it Yourself ISO 27001 with the Ultimate ISO 27001 Toolkit
Conclusion
While ISO 27001 Annex A 5.30 presents unique and complex hurdles for AI companies, a structured and tailored approach makes compliance entirely achievable. By performing an AI-specific business impact analysis, developing a robust and tested continuity plan, and leveraging the right tools, you can build true resilience. The High Table ISO 27001 Toolkit serves as a powerful resource in this journey, empowering you to protect your innovation, build trust with your customers, and ensure your business can withstand any disruption.
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.
