How should access to AI-assisted delegated authority workflows be controlled?
Give each person, service account and AI tool only the delegated authority data and actions needed for its approved task. Scope permissions by role, contract and data type; separate read, amendment and approval rights; and review access when staff, suppliers or arrangements change. Log sensitive access and test that the workflow cannot retrieve or write outside its scope. Human owners remain responsible for approval and exceptions.
Key takeaways
- Access design must cover people, integrations and AI tools.
- Restrict both which records can be seen and which actions can be taken.
- Use separate approval authority for material decisions and changes.
- Review, revoke and test permissions throughout the workflow lifecycle.
A delegated authority workflow can join bordereaux, contracts, claims and oversight records. Adding AI search or tool use may widen the path to those records if permissions are inherited too broadly. Service owners need a practical way to let staff and systems do useful work while keeping each contract and data class within its approved boundary.
Map tasks to data and actions
List who needs to submit, view, correct, approve or export each data type. Include coverholders, brokers, DCAs, managing agents, support teams, service accounts and suppliers where relevant. Scope access by contract participation and purpose, not only by a broad “DA user” label. Check whether personal or commercially sensitive fields can be masked for tasks that do not need them.
Apply established identity controls
Use approved identities, role-based permissions, least privilege and a formal provisioning process. Keep separate rights for reading data, changing mappings, accepting exceptions and approving release. Review privileged access, remove it promptly when a role ends and keep an owner for each service account. These familiar controls remain effective in AI-assisted systems when carried through to every retrieval and tool call.
Constrain AI retrieval and tool use
An AI assistant may search across indexed bordereaux or call an API. Enforce authorisation before retrieval and again before an action, using the requester’s permitted contract and task scope. Restrict available tools and credentials; do not allow the model to choose a broader privilege than the approved user or service. A generated answer should not reveal records the requester could not open directly. Test cross-contract and prompt-manipulation cases.
Monitor and revisit access
Log who or what accessed data, which contract was in scope, what action was attempted and whether it succeeded. Alert on unusual bulk export, repeated denials and privileged changes. Review access after staff moves, contract expiry, supplier changes and new AI features. Retain an escalation route for suspected overreach and suspend affected access while it is investigated. Privacy and security specialists should determine the applicable UK obligations in context.
Example
In a hypothetical managing agent, an AI assistant helps analysts answer questions about monthly risk bordereaux. A user assigned to one binder asks for exposure across all coverholders. The retrieval layer limits results to that user’s approved binder and logs the request. A separate oversight analyst with broader authorised access can run the portfolio query. Neither assistant account can approve a mapping change.
FAQs
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Is a shared service account acceptable for AI tools?
An identifiable, owned machine identity with narrowly scoped rights is preferable; shared credentials make accountability and revocation harder.
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Can a prompt instruct an AI tool to ignore permissions?
No. Permissions must be enforced by the data and tool services, independently of the prompt.
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How often should access be reviewed?
Use a documented risk-based schedule and event-driven reviews after role, contract or supplier changes; no universal interval fits every workflow.
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