Artificial intelligence is moving rapidly from experimentation into production. South African banks, insurers, healthcare groups, retailers, logistics operators and public institutions are already relying on AI for decisions, automation, fraud detection, forecasting and customer engagement.
That creates a new concentration risk.
From sudden software restrictions to cross border cyber incidents, organisations across the world are facing a new reality: critical dependencies can be withdrawn overnight. The uncomfortable question is no longer if, but how long organisations can operate without them.
For many, the answer is measured in hours.
When the dependency is AI, the risk can be sharper than traditional software because the asset is not only code. It may also include trained models, prompts, workflows, decision logic, integrations, datasets, access credentials and ongoing vendor support.
So, is escrow relevant to AI?
Yes. Increasingly, it is necessary.
AI changes the nature of vendor dependence
Traditional software escrow focused on source code and documentation. If a vendor failed, the customer could obtain the materials needed to maintain continuity.
AI systems often require more.
If an organisation depends on a third-party AI provider, losing access may mean losing:
- The model that powers a service.
- Fine- tuned weights or custom configurations.
- Prompt libraries and orchestration logic.
- Integration layers into core systems.
- Historical outputs and decision trails.
- Operational know-how needed to run the service.
- Access to future updates or support.
Without these, continuity can be difficult, expensive or impossible.
An AI chatbot can be replaced.
An AI-driven underwriting engine, fraud model or medical workflow is a different matter.
South Africa’s proposed AI regulation direction matters
South Africa is moving towards more formal AI governance. While the regulatory framework will evolve, the direction of travel is already clear: accountability, transparency, governance, fairness, security and risk management.
That should not surprise anyone.
Where AI affects customers, markets, financial outcomes, health decisions or critical operations, boards and executives will be expected to show control over third-party dependencies.
If a critical AI supplier fails, “the vendor managed it” is unlikely to satisfy regulators, auditors or affected customers.
The practical question becomes:
How do you evidence resilience where AI is outsourced?
Escrow is one credible answer.
What AI escrow should actually cover
A serious AI escrow arrangement should be tailored to the use case. Depending on the system, it may include:
- Source code and application logic
- Model files and deployable versions
- Fine-tuned parameters or configurations
- Prompt frameworks and orchestration flows
- Technical documentation
- Build and deployment instructions
- Data schemas and interfaces
- Runbooks for continuity operation
- Periodic updates as the system changes
This is not about taking ownership of a vendor’s IP. It is about continuity rights triggered only under agreed release conditions such as insolvency, failure to support, material breach or service cessation.
Minimum viable sovereignty for AI
Many organisations cannot build every AI capability internally.
That is not the standard.
The better standard is minimum viable sovereignty: enough control to continue operating if a third-party dependency fails.
For AI, that may mean the ability to:
- Access the latest usable version.
- Transfer operations to an alternate environment.
- Maintain a critical model temporarily.
- Preserve records and outputs.
- Avoid immediate operational shutdown.
Software escrow helps create that minimum control layer.
The real risk is delay
Most continuity failures are not caused by a lack of technology.
They are caused by delay.
Delay in obtaining rights. Delay in accessing materials. Delay in understanding how the system works. Delay while legal teams argue during an outage.
Escrow solves those issues before the crisis.
Final view
AI escrow is not needed for every tool, plugin or experimental use case.
But where AI supports regulated activity, revenue generation, customer outcomes or mission-critical operations, the question is shifting.
Not: “What if the vendor fails?”
But: “How exposed are we if they do?”
For South African organisations adopting AI at scale, escrow is no longer an old software concept. It is a modern resilience control.
Share
Editorial contacts