Keep the system of record: the architecture pattern enterprise AI needs
Do not start by replacing trusted systems
Most enterprises already run on systems people trust: CRM, ERP, case management, identity, document stores, and core platforms. Those systems are imperfect, but they hold the record of the business.
The practical AI architecture is to keep those systems in place and build a workflow layer around them.
Curate just enough context
The AI workflow should see the documents, records, policies, examples, and user role needed for the process. It should not be given free-roaming access to everything the organisation owns.
The workflow can prepare, compare, draft, or recommend; the completed outcome should write back to the appropriate system when needed, with audit and retention rules visible.
Why this scales
This pattern reduces risk because the source of truth does not move. It also makes rollout faster because each new workflow can reuse identity, governance, integration, and data-context patterns from the last one.
App layer
A brand-matched workflow that gives users the right journey for the process.
Platform layer
Identity, RBAC, audit, workflows, agents, connectors, and model routing.
Context layer
The curated, time-boxed data the workflow needs to complete its job.
Record layer
The trusted systems where source records stay and completed outcomes return.
Want to turn this into a real workflow?
Start with one process, one accountable owner, and the evidence needed to decide whether to scale.