You do not need a complete architecture or a chosen model to begin. Start with a business outcome, the people affected, and the information or systems involved. That gives the conversation a practical focus and helps separate a useful first project from a broader transformation program.
Describe the current workflow.
Choose a recurring task or service problem and explain how it works today. Identify the people involved, the systems they use, and where delays, errors, or uncertainty arise. A concrete workflow gives architecture decisions something measurable to support.
Separate symptoms from assumptions about the solution. Slow reporting might result from inconsistent definitions rather than insufficient infrastructure. A difficult knowledge search might reflect outdated content or inappropriate access rather than the absence of an AI assistant.
Map the minimum technical scope.
Identify required data sources, integrations, identities, and environments. Record what can change and what must remain untouched. Include dependencies such as network access, licensing, data residency, and support arrangements that could constrain implementation.
Use high-level descriptions or redacted examples at first. Credentials, private records, and unrestricted repository access are not prerequisites for an initial scoping discussion. Agree appropriate access and handling before sharing detailed evidence.
Example: a knowledge-assistance pilot.
A team wants faster access to approved answers. A bounded first scope might use a maintained policy library, selected user roles, and read-only retrieval. The pilot can evaluate relevant answers and denied access without introducing record updates or external messaging.
Define representative questions, accepted sources, expected review, and a route for unresolved answers. Compare task quality and effort against the existing process. This produces evidence for the next investment decision rather than assuming that a working interface proves business value.
Agree deliverables and decision gates.
Specify the outputs needed from the engagement: an assessment, architecture, pilot, implementation plan, or operational handover. Define acceptance criteria, accountable owners, exclusions, and assumptions that could change effort or timing.
A useful scope explains how results will be reviewed and who decides to proceed, refine, or stop. Production deployment can require additional security, reliability, support, and adoption work even when a pilot meets its objectives. Keeping those decisions explicit helps prevent a small experiment from becoming an unsupported service.
Further reading
Compare engagement options and review service scopes before deciding on the first deliverable. Discuss your priorities using a high-level description of the work.