What should organisations document when deploying vendor-hosted agentic AI?

What vendor-hosted agentic AI means for documentation

When a vendor runs part of the agentic ai runtime, your documentation has to show where your responsibility ends and the provider’s begins. That means recording the control points for instructions, memory, logging, retention, and support evidence, so the organisation can demonstrate what it can actually govern rather than assuming the provider’s service description is enough.

For AI agents vs agentic AI, that distinction matters because autonomy changes the governance burden. A system that can act on instructions, preserve context, and create logs is not just a hosted application, it is an operational actor whose behaviour must be explainable after the fact.

Documentation should therefore name the provider-managed components, the customer-managed decisions, and any shared controls around delegation, policy enforcement, and evidence capture. For vendor-hosted deployments, the most useful record is often the one that lets security, privacy, legal, and incident-response teams answer the same question from the same source of truth.

What needs to be documented about control, memory, and evidence

The key items are who controls instructions, who can see or export logs, whether memory can be disabled, how deletion is supported, how incidents are investigated, and what evidence the provider returns to the customer. Those are the ownership questions that determine whether a team can validate the runtime, investigate a disputed action, or support a regulatory request.

AI Agent Observability, Audit and Incident Response Guide is directly relevant here because documentation is only useful if it supports attribution and incident reconstruction. If logs cannot show which instruction was executed, which memory state was active, or which tool call occurred, the organisation may know an event happened but still be unable to prove how or why.

AI Agent Memory Security Guide reinforces the memory side of that record. Teams should document whether memory is persistent or ephemeral, who can write to it, whether it can be disabled per tenant or per workflow, and what happens to stored context at deletion or offboarding.

Agentic AI Compliance Guide is useful where documentation must support privacy and audit obligations, because retained evidence, deletion support, and accountability statements are often what make the difference between a compliant deployment and an unprovable one.

Why vendor-hosted deployments create documentation gaps

The main risk is not that the provider owns the runtime, but that ownership is implicit. If the contract, the operating model, and the incident process do not spell out who controls what, the organisation can end up with an agent that acts on its behalf without a defensible record of authority, retention, or investigation rights.

Vendor-hosted agentic systems also create a common failure mode: the customer assumes the provider will retain enough evidence for troubleshooting, while the provider assumes the customer has captured the business context needed to interpret it. That gap is especially damaging when memory, prompt history, or tool execution traces are transient or partially hidden from the customer.

OWASP Agentic AI Top 10 provides the broader threat lens, especially around identity and privilege abuse, tool misuse, and memory poisoning. Documentation has to anticipate those risks by recording where control exists, where it is delegated, and which artefacts would prove misuse if a dispute or incident arises.

NIST AI Risk Management Framework is the right external reference when organisations need a governance anchor for these ownership decisions. It helps teams treat documentation as a risk control, not a paperwork exercise, by tying the deployment record to accountability, monitoring, and response expectations.

Practitioner Guidance

What to prioritise: Document the control boundary first. Before production use, be able to answer who sets instructions, who can inspect logs, who can disable memory, and who must provide evidence after an incident.

What to verify: Confirm that deletion is real, not just a UI action. The provider should be able to explain what is removed, what is retained for legal or operational reasons, and how customers receive proof of deletion or retention exceptions.

Decision rule: If the vendor cannot return enough evidence to reconstruct a material action, treat the deployment as incomplete for regulated or high-impact use, even if the model itself is technically available.

Common mistake: Teams often document the product, but not the operating rights. A service description is not the same as evidence that the customer can investigate an incident, challenge an outcome, or demonstrate accountability to auditors or regulators.

Practitioner takeaway: For vendor-hosted agentic AI, the documentation should make shared responsibility operationally provable, not just contractually asserted.

Related resources from NHI Mgmt Group

• What makes agentic AI an NHI governance issue?
• How should organisations implement AI impact assessments before deploying agentic systems?
• When should organisations use AI for vendor risk management instead of only using it for document storage?
• What is the Agentic AI identity governance framework organisations should adopt?