ISO 27001:2022 Annex A 5.30 ICT readiness for business continuity for AI Companies

ISO 27001 Annex A 5.30 ICT readiness for business continuity is a security control that ensures critical technology infrastructure maintains operational stability during disruptive events. The primary implementation requirement involves testing redundant GPU clusters and recovery scripts, providing the business benefit of reduced churn and proven resilience for enterprise clients.

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.

The “No-BS” Translation: Decoding the Requirement

Let’s strip away the consultant-speak. Annex A 5.30 is about proving that your redundant systems actually work. It asks: “If AWS us-east-1 disappears, does your company die?”

The Auditor’s View (ISO 27001)	The AI Company View (Reality)
“ICT readiness… shall be planned, implemented, maintained and tested based on business continuity objectives and ICT continuity requirements.”	Test your backups. It’s not enough to have a backup strategy. You have to prove you can spin up your GPU cluster in a new region within 4 hours. If you haven’t tested the restore script, you don’t have a plan; you have a hope.

The Business Case: Why This Actually Matters for AI Companies

Why should a founder care about “ICT Readiness”? Because downtime is churn.

The Sales Angle

Enterprise clients will ask: “What are your RTO (Recovery Time Objective) and RPO (Recovery Point Objective) for your inference API?” If your answer is “We don’t know,” they will assume your service is unreliable. If your answer is “We have a 15-minute RPO and a 1-hour RTO, tested quarterly,” you win the contract. Annex A 5.30 provides the test results.

The Risk Angle

The “Dead Region” Scenario: A major cloud outage hits your primary region. Your competitors (who use multi-region failover) are back online in 10 minutes. You are down for 3 days because you hardcoded us-east-1 into your codebase. You lose your customers forever.

DORA, NIS2 and AI Regulation: Continuity is Compliance

Regulators demand proof that you can stay online.

• DORA (Article 11): Financial entities must have “backup policies and recovery procedures.” You must test your ICT continuity plans at least annually. If you are a critical third-party provider (CTPP) to a bank, you must participate in their disaster recovery tests.
• NIS2 Directive: Mandates “business continuity,” including backup management and disaster recovery. You must ensure the continuity of critical services.
• EU AI Act: High-risk AI systems must have “robustness.” If a hardware failure causes your safety guardrails to fail (e.g., fallback to a smaller, less safe model), you are non-compliant.

ISO 27001 Toolkit vs SaaS Platforms: The ICT Trap

SaaS platforms help you monitor uptime, but they don’t help you plan for downtime. Here is why the ISO 27001 Toolkit is superior.

Feature	ISO 27001 Toolkit (Hightable.io)	Online SaaS Platform
The Plan	Actionable Documents. A clear “Disaster Recovery Plan” that your engineers can read offline when the internet breaks.	Cloud Dependent. If your cloud provider is down, you probably can’t access your SaaS compliance tool to read the recovery steps.
Ownership	Your Metrics. You define RTO/RPO based on business needs, not platform defaults.	Generic Monitoring. Platforms track “uptime,” but they don’t help you architect a failover strategy for your specific vector database.
Simplicity	Testing Templates. “DR Test Log” templates to record your simulations.	Over-Engineering. Platforms confuse “Incident Response” with “Disaster Recovery.” They are different disciplines.
Cost	One-off fee. Pay once. Be ready forever.	Subscription. You pay monthly for a BCP module that is just a form builder.

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.

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. Think of it as your organisation’s formal “backup plan” for its technology infrastructure.

Core Concepts You Need to Know

• Business Impact Analysis (BIA): Identifying your most critical business activities (e.g., Inference API).
• Recovery Time Objective (RTO): How long until the system is back UP? (e.g., 4 hours).
• Recovery Point Objective (RPO): How much data can we lose? (e.g., 1 hour).

The AI Challenge: Why A.5.30 Is Different for You

For AI-driven organisations, the core assets create unique points of failure.

Disruption to Model Training and Data Processing

A disruption to your training pipeline could lead to the loss of valuable work. If a 2-week training run crashes on day 13 and you have no checkpoints, you lost 2 weeks of compute cost and time. RPO for training checkpoints is critical.

Disruption to Algorithmic and Inference Processes

If your core inference model is unavailable, your service is down. This directly translates to financial losses. High-availability (HA) architecture is the only mitigation.

Vulnerabilities in the AI Supply Chain

Your organisation may depend on third-party data sources or pre-trained models. If OpenAI’s API goes down, what is your fallback? Do you switch to a local Llama model? Annex A 5.30 requires you to plan for supplier failure.

Your Action Plan: Practical Steps for AI Compliance

1. Conduct an AI-Specific BIA: Identify the criticality of your AI models. How much does it cost if the API is down for 1 hour?
2. Define RTOs and RPOs: Set strict targets. Inference: RTO < 15 mins. Training: RPO < 4 hours (checkpoints).
3. Implement Backups: Version control your models (MLflow/DVC). Backup your training data to a separate region.
4. Test Recovery: Actually try to restore a model from backup. Does it load? Does it infer correctly?

The Evidence Locker: What the Auditor Needs to See

When the audit comes, prepare these artifacts:

• ICT Continuity Plan (PDF): A document detailing your failover architecture.
• Test Report (PDF): “On [Date], we simulated a region failure. We restored services in 35 minutes. Result: Pass.”
• Backup Logs (Screenshots): Evidence that automated backups are running successfully.
• BIA Document (Excel): The analysis showing how you calculated your RTOs.

Common Pitfalls & Auditor Traps

Here are the top 3 ways AI companies fail this control:

• The “Untested” Plan: You have a great document that says “We will switch to Azure,” but you’ve never actually tried to deploy your code on Azure. When you try, it fails.
• The “Manual” Restore: Your recovery process relies on one specific engineer running commands from memory. If they are on holiday, you are dead. Automate it (Terraform/Ansible).
• The “Stale” Image: You restore from a machine image (AMI) that is 6 months old. It works, but it’s missing 6 months of security patches. You are now online but vulnerable.

Handling Exceptions: The “Break Glass” Protocol

What if the automated failover fails?

The Manual Override Workflow:

• Trigger: Automated recovery script fails or hangs.
• Authority: Engineering Lead authorizes manual intervention.
• Action: Use “Break Glass” credentials to access the backup region console directly.
• Log: Retroactive incident ticket created to document manual steps taken.

The Process Layer: “The Standard Operating Procedure (SOP)”

How to operationalise A 5.30 using your existing stack (AWS, Linear).

• Step 1: Define (Manual). Agree on RTO/RPO for the “Inference Service” (e.g., 99.9% uptime).
• Step 2: Backup (Automated). Configure AWS Backup to snapshot EBS volumes and RDS databases daily. Copy to DR region.
• Step 3: Test (Manual). Schedule a “Game Day” in Linear every 6 months.
• Step 4: Execute (Manual). Engineers try to spin up the stack in the DR region using the backups.
• Step 5: Report (Manual). Document pass/fail in the “DR Test Register” (Excel).

By conducting an AI-specific business impact analysis and developing a robust continuity plan, you can build true resilience. The High Table ISO 27001 Toolkit serves as a powerful resource in this journey.

ISO 27001 Annex A 5.30 for AI Companies FAQ

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