Telecommunications / Mobile carrier
LG Uplus: Suggesting answers during a call
- Company
- LG Uplus
- Country
- South Korea
- Adoption stage
- In operation
- Source published
- In use from
- Date basis
- The date the source was published. It can differ from the date adoption started.
- How the source was checked
- Read the full source text
The work problem
The LG Uplus customer centre takes an average of about 75,000 enquiries a day. When a call ended, agents had to check one by one what the AI had summarised and classified and judge whether it was accurate. The procedure was complicated and took a lot of time.
Technology and data
The company developed an AI advisory assistant in house and put it into the customer centre. It was built on the roughly 18 million calls a year of conversation data held at the centre. Agentic RAG reads the context of the question, searches internal information and drafts an answer. Before the answer goes to the agent, a step was added that reviews and validates whether it matches the intent of the question. For post-call work, AI In The Loop was attached to handle summarising and classification. The company said it will also build and add AI Auto QA, in which AI evaluates the content of a call and gives feedback.
Results
LG Uplus said that after adoption the waiting time to connect per customer call fell by an average of 17 seconds and call time by an average of 30 seconds, improving total handling time by about 19 percent. On a monthly basis it calculated that about 1.17 million minutes of customer time were saved. Its own analysis put the accuracy of Agentic RAG answers at 90 percent. It explained that classifying 2,000 calls by hand took about 5,760 minutes, while AI In The Loop finished 3,000 in 40 minutes.
Limits and open questions
All of this is LG Uplus's own analysis. Customer satisfaction and call quality indicators are not in this source.
Sources
- 보도자료 | 미디어 | LGlg.co.kr, Accessed
Compiled from public sources. These are not results from ATF Works customers.