The operating problem
Student-services staff answer recurring procedural questions using catalogs and policy documents that change between academic periods. The workflow is not simply a question-answering task: it requires a reliable relationship between business entities, current evidence, and the review responsibilities of staff.
Course requirements change by academic period, and public guidance must be separated from restricted student information. A useful initial scope therefore focuses on assembling the right context and making missing information visible. It avoids treating a generated answer as an approved business decision.
The proposed data foundation
Potential inputs include course catalogs, published policies, administrative requests. Establish a source inventory before choosing connectors. For each input, record its owner, approved use, identifier conventions, update cadence, and retention requirements.
Version published catalogs, identify the academic period, preserve policy authority, and exclude restricted records from public retrieval. The curated domain model centers on Course, Program, Published policy, Service enquiry. Keep raw source evidence separate from validated records and from the outputs prepared for a reviewer. This separation makes reconciliation and incident investigation more manageable.
AI and agent responsibilities
Find published information and draft responses to routine service questions. A permission-aware retrieval layer can assemble the relevant approved context. Extraction or generation should return structured drafts, source references, and unresolved questions; it should not silently supply facts that are absent from the records.
Map approved learning materials to program requirements for staff review. A second bounded responsibility can handle a related task while retaining the same identity and governance boundary. Multi-agent coordination is optional: use it only when separated responsibilities improve traceability or control.
Human review and exception paths
Admissions, grading, eligibility, and interventions remain human decisions. Missing documents, conflicting records, unavailable tools, and low-quality retrieval should lead to a visible exception. Define who can resolve each exception and what evidence must be retained with the decision.
How the scenario would be evaluated
Proposed evaluation areas: correct-period retrieval, citation accuracy, public/restricted separation, and staff correction frequency. Build a representative set containing normal cases, incomplete cases, outdated information, access restrictions, and tool failures. Compare the assisted workflow with the current process using the same acceptance criteria.
No percentage improvement, cost saving, or production result is asserted here. Any future benefit estimate should follow a measured baseline and a reviewed pilot, including the effort required to correct outputs and handle exceptions.
A focused next step
Agree one workflow, one accountable owner, a limited source set, and a review protocol. Use the first prototype to identify data gaps and operational changes, then decide whether additional integrations are justified.