Singapore Management University adopts agentic AI to tackle brittle automated workflows streamline document handling, and reduce manual errors across administrative teams.

How do business leaders modernize a document-heavy university operation when the real bottleneck is not volume, but the fragility of the automation itself?

In Singapore, a local university had been continually implementing intelligent automation to streamline admissions and back-office document handling, freeing staff from manually scrolling through files, copying data, and checking applications for qualified candidates.

However, such automation did require maintenance, and sometimes, the technology often broke when user interfaces changed. The problem was not just volume, but variability.

Standard automation struggled with documents that arrived in different formats, or included embedded tables, graphs, and inferred values — which made the process brittle and labor-intensive. The institution — Singapore Management University — also wanted a system that could handle finance report extraction, admissions queries, bursary applications, scholarship workflows, and related follow-up tasks without forcing staff to jump between systems.

So, in February 2026, SMU began another digital transformation exercise using agentic AI to improve business orchestration, introducing:

  • Intelligent document processing to extract data from unstructured and variable documents
  • Workflow automation to replace repetitive manual copying, pasting, and validation
  • Orchestration of multistep processes so tasks could move from intake to output with less human intervention
  • Customizable output generation, including PDF and spreadsheet formats with user-defined columns
  • Automated delivery of results by email after the completion of processing and screening logic

According to Cassandra Jenna Bibal, a business analyst and automation developer at SMU, “Ultimately, we see this as a step towards more intelligent, integrated automation ecosystems, where business users can interact with systems in a flexible, on-demand manner, while automations handle the complexity behind the scenes.”

SMU had chosen solutions from UiPath platform for the project, which helped the developers to apply rule-based automation to more context-aware workflows that support conversational interfaces and follow-up actions — without manual handoffs — and connect decision-making with execution through agentic AI capabilities and integrated automation.