{"resourceId":"pusan-national-university-manager-ai-agent-training-20261103","versions":[{"version":"external-f5ce2de46d892a94c4702a783e6b3629ce4a87fe1772a8c39e2067edb03704de","resource":{"id":"pusan-national-university-manager-ai-agent-training-20261103","title":"Pusan National University trains 40 administrative section managers to build AI agents after staff built 12 work agents in an eight-week course","organization":"Pusan National University (AX and Informatization Innovation Headquarters)","sector":"Higher education administrative operations","geography":"Busan, South Korea","publishedAt":"3 November 2026 (Busan Ilbo)","publicationDate":"2026-11-03","eventDate":"2026-11-03","sourceName":"Busan Ilbo (busan.com)","sourceLabel":"Regional news report based on university release","sourceUrl":"https://www.busan.com/view/bstoday/view.php?code=2026110310494469233","evidenceClass":"independent-reporting","outcomeClass":"emerging","topics":["developers-agents","accessibility-workforce","operating-model"],"finding":"On 2-3 November 2026 Pusan National University's AX and Informatization Innovation Headquarters ran a six-hour course for about 40 administrative section and office managers: day one on how generative AI works in administrative tasks, day two building work AI agents with agentic tools, plus the amended public-sector AI law in force since 28 August. It followed the 'AI Maestro' staff course (19 June-15 October), in which 21 staff from 20 departments built 12 work agents over eight weeks; self-assessed AI skill rose from 2.85 to 3.94 out of 5.","sledRelevance":"Shows a campus extending agent-building from front-line staff to middle managers so they can judge which departmental work to give to AI.","evidence":"News report of a university release; outcome data is self-assessment only and the 12 agents are not described or measured.","architectureImplications":"Staff-built agents on agentic tools imply many small departmental agents; platform and hosting are not named.","governanceImplications":"Managers are trained to review staff-proposed AI uses and to check obligations under the amended public-sector AI law.","securityPrivacyImplications":"No data-handling controls for the staff-built agents are described.","caveats":"Self-reported skill gains only; no productivity, quality or error data; agent inventory not published.","streamIds":["campus-operations"],"roles":{"sales":"Sales framing: Pusan is training managers, not just staff, to decide which administrative work goes to AI agents. Interpretation: campuses with scattered staff-built agents may need help with manager-level review criteria and an agent inventory. Do not cite productivity gains; only self-assessed skill scores are reported.","engineering":"Engineering framing: 12 staff-built departmental agents implies a long tail of small agents. Interpretation: pre-sales should ask about the platform, data access, and how agents are registered, monitored and retired, none of which the report describes.","delivery":"Delivery framing: a two-tier training model where staff build and managers evaluate. Interpretation: delivery should add an agent registry, review checklist tied to the public-sector AI law, and outcome measures beyond self-assessment."},"roleDetails":{"sales":{"customerProblem":"Departments build AI agents but managers lack criteria to judge which tasks to delegate.","stakeholders":["AX/IT office head","Section managers","Department staff"],"discoveryQuestions":["How many staff-built agents exist and who approves them?","What review criteria do managers use?","How is compliance with AI law checked?"],"valueHypothesis":"Manager training may improve selection of agent use cases; no measured benefit is reported.","potentialEngagement":"A bounded agent review framework and inventory for departmental agents.","unsupportedClaims":["Productivity or time savings","Quality of the 12 agents","Durable skill gains beyond self-assessment"]},"engineering":{"fit":"Campuses with citizen-built agents in administrative departments.","architectureIntegration":"Agentic tool platform not named; departmental data sources not described.","prerequisites":["Approved agent-building platform","Data access rules","Agent registry"],"constraints":["Korean public-sector AI law obligations","Unknown hosting/jurisdiction of tools"],"security":"Need access scoping and logging for staff-built agents; none described.","proofOfValue":["Inventory and classify the 12 agents by data used","Measure task time before and after for a sample agent"]},"delivery":{"work":"Run role-tiered agent training and move from training outputs to governed departmental agents.","dependencies":["Central AX office","Department managers","Legal/compliance"],"ownership":"AX and Informatization Innovation Headquarters.","skillsAdoption":"Hands-on build labs for staff; evaluation-focused labs for managers.","governanceCheckpoints":["Manager review of staff-proposed agents","Legal check against public-sector AI law"],"acceptanceCriteria":["Proposed: every production agent registered with owner and data scope","Proposed: outcome measure defined per agent"],"risks":["Unmanaged agent sprawl","Overreliance on self-reported gains","Data exposure through unvetted tools"]}},"retrievedAt":"2026-11-03T21:53:51-06:00","enrichedAt":"2026-11-03T22:08:00-06:00","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Role-tiered training: staff build, managers assess fit; satisfaction survey planned.","procurementImplications":"Tooling vendor not named; scale-up would raise licensing and support questions.","operatingModelImplications":"Central AX office runs training; departments own use cases.","sourceVerification":{"openedUrl":"https://www.busan.com/view/bstoday/view.php?code=2026110310494469233","referenceExcerpt":"20개 부서 실무자 21명이 8주간 자신의 업무를 바탕으로 AI 에이전트 12건을 직접 제작했으며","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}