United StatesEducation2026 – ongoing

Baylor University

AI review of every enrollment contact center call

Baylor University reviews every contact center call with AI agents, up from a 5% sample

WorkingVendor case studyVendor ↗

Problem

Baylor's enrollment contact center has about ten representatives who handle 100 to 300 calls a day about financial aid, deadlines and bills. Managers could review only about 5% of calls by sampling.

Approach

Baylor built a call review workflow with Agent Bricks on the Databricks platform. A knowledge assistant gives representatives guidance from policies. A supervisor agent checks each call against standard operating procedures and links findings to timestamps. Staff can query call data in natural language and get sentiment trends and coaching signals.

Results

100%share of calls reviewed, up from about 5% by sampling, per DatabricksVendor case study[1]

about 2 minutestime to generate a daily report that was not possible before, per DatabricksVendor case study[1]

Takeaway

Automated review replaced sampling, so coaching could draw on every call. Baylor did this without adding staff.

Sources

Agent Bricks Gives Baylor a Direct Line to the Student Voice
Databricks20 Mar 2026Vendor publication

Source summaries

[1]Databricks20 Mar 2026

Databricks describes how Baylor's enrollment contact center uses AI agents to review calls about financial aid, deadlines and bills. Coverage rose from about 5% of calls to 100%, and a daily report takes about two minutes to generate. The page says the quality review covers all calls without added headcount.

Full details are in the original sources.

Added 4 Nov 2026 · Updated 4 Nov 2026