# AI Admin

> Automate LMS administration with smart dashboards, automated reports, and intelligent course management.

- Last updated: 2026-07-27
- Canonical URL: https://www.touchclass.com/en/ai-admin
- Markdown mirror URL: https://www.touchclass.com/markdown.php/en/ai-admin.md
- Language: English
- Category: AI features

## Key points

- Automate LMS administration with smart dashboards, automated reports, and intelligent course management.

## Feature details (structured data)

### What it does

- Helps administrators ask natural-language questions about learning data, extract CSV reports, classify incomplete learners, and automate reminder operations.

### Detailed functions

- natural-language learning status queries
- CSV report extraction
- department, role, period, and course filters
- 1st, 2nd, and 3rd learning nudges
- MAU and content-supply pattern checks
- distributed sub-admin operation support

### Effects

- public product messaging cites 40+ hours per month saved on repetitive reporting and aggregation work
- supports large distributed operation models such as roughly 70 sub-admins
- reduces headquarters bottlenecks in mandatory training and field learning operations

### Source URLs

- https://www.touchclass.com/en/ai-admin
- https://www.touchclass.com/en/dashboard
- https://www.touchclass.com/en/data-report

## Page content

*The content below is extracted from the rendered source page.*

AI Admin

## Ask AI about your training operations

Learning status, data analysis, report exports. No more spreadsheets. An admin-only AI that answers in natural language.

[Book a Free Demo](https://www.touchclass.com/form/contact) Download Proposal

Natural Language

Query Method

Say "Team A's completion rate this month" and AI pulls the data and answers.

CSV

Report Export

Say "download" during a conversation and a CSV file is generated instantly.

Real-time

Data Refresh

Learning data is updated in real time. No more monthly Excel consolidation.

## Manage learning through conversation

- Natural Language Data Query

Type "What's the average learning time for the top 5% of the group that Park belongs to?" and AI queries the data and responds. Combine conditions like department, role, and date range. No SQL or pivot tables needed — just ask what you want to know.

Natural language → data response

- CSV Report Export

Ask "Download this data as CSV" during a conversation and a file is generated. Extract common metrics like unique visitors, course completion rates, and department participation — all through conversation. Eliminate monthly manual Excel work.

Conversational report generation

- Real-time Status Check

Previously, admins downloaded data monthly from the LMS admin page and processed it in Excel. AI Admin queries learning data in real time. Ask "How many non-completers today?" and get the number immediately.

AI Admin Chat Interface · illustrative mockup

What's the average learning time for the top 5% of the selected group?

For the selected period and group, show the **top 5% average learning time** alongside the whole-group average.

Show learner names and learning time

Within the administrator's permission scope, return each learner's name and learning time.

Illustrative UI · synthetic data · not a customer outcome

Conversational Report Export

Summarize this month's completion rate by department

Here are the completion rates by department this month: Sales 92% · Marketing 87% · Dev 78% Admin 95% · Logistics 64%

Download as CSV

CSV file generated.

dept_completion_2026_04.csv

5 departments · 12.3KB · just created

⬇

Generate reports with a single message

Real-time Learning Status

1,247

Today's logins

183

Non-completers

89%

Overall completion

3.8h

Avg learning/person

How many non-completers today?

Currently **183 non-completers**. Logistics 52 (28%), Sales 41 (22%).

Monthly Excel → real-time conversational queries

## Data drives your strategy

- Learning Pattern Analysis by Department

AI analyzes learning patterns by department and role. Identify which teams have low participation and which content performs well. Operations data from 100+ companies shows that when content upload frequency drops below once a week, MAU plummets. AI Admin alerts you to these warning signs early.

Pattern analysis + early warnings

- Automated Non-completer Management

AI automatically categorizes mandatory training non-completers. It classifies them by pattern and extracts reminder targets. No more manually pulling lists. Observed across 40+ companies: median MAU during mandatory training periods is 89%.

Mandatory training MAU median: 89%

- Custom Learning Strategy Proposals

AI proposes strategies based on learning data. For example, if a department's completion rate is low, it may suggest adjusting content supply frequency or applying gamification.

Learning Participation by Department

AdminSalesDevLogisticsProduction

⚠️

Logistics content supply gap detected

0 new content in 2 weeks · MAU decline expected

🚨

Production participation at critical level

42% · -18%p vs last month · immediate action needed

Early warnings based on 100+ company patterns

Auto-classified Non-completers

73

No access

58

Stalled

52

80%+ progress

Auto-extracted reminder targets

73 no-access → 1st reminder pending

Logistics 28 · Production 22 · Others 23

🟡

58 stalled → content recommendation sent

Avg progress 34% · last access 7 days ago

🟢

52 at 80%+ → encouragement message

Expected completion avg D-3

Mandatory training MAU median: 89%

AI Strategy Recommendation Interface

Why is Production's completion rate low?

Production team analysis: 1. Content supply frequency: 0.5x/month (recommended: weekly) 2. Field workers: limited mobile access 3. No allocated training time

AI Proposed Strategy

1️⃣

Push short-form content 2x/week

1-min learning for field workers → build access habits

2️⃣

Apply gamification badges

Expected +25%p participation (based on similar cases)

3️⃣

Team lead-driven encouragement system

Sub-admin access → on-site management

Data-driven decision support

## AI handles repetitive tasks

- Automated Push Notifications

Auto-send staged reminder messages (1st, 2nd, 3rd) to non-completers. Only re-sends to those who didn't confirm. No more manually pulling lists and contacting individuals.

1st → 2nd → 3rd auto-reminders

- Enrollment & Completion Tracking

Monitor learning status in real time by course, member, and group. Auto-detect learners with low progress and add them to targeted notification lists. Reduces 40+ hours of monthly manual admin work.

40+ hours/month manual work saved

- Sub-admin Permission Separation

HQ manages everything while department-level sub-admins run their own team training. Korea Railroad Corporation operates with 71 sub-admins in a distributed model — central control with local autonomy.

71 sub-admins in distributed operation

Staged Auto-reminder Process

📩 1st Reminder — D-14

Sent to 183 non-completers · 162 confirmed

📩 2nd Reminder — D-7

Re-sent to 21 unconfirmed + 94 still non-complete

📩 3rd Reminder — D-3

42 remaining non-completers · manager CC included

Final Report — D-Day

Auto-generated final non-completer list

183 → 42

Non-completers reduced

77%

Auto-resolution rate

Manual lists → 3-stage auto-reminders

Real-time Learning Status Tracking

Completion Rate by Course

Info Security

94%

Anti-harassment

88%

Sexual Harassment

82%

Safety & Health

61%

Privacy

76%

Retirement Plan

43%

Auto-detection Alerts

⚠️

Safety training progress at risk

D-5 deadline · 128 non-completers → targeted send scheduled

🚨

Retirement plan training below target

D-10 deadline · 43% completion · Production team focus

40+ hours/month manual work saved

Distributed Sub-admin Structure

🏢 HQ Admin (Full Control)

Sales Division — 12 sub-admins

Sales 1 Kim · Sales 2 Lee · Sales 3 Park...

Production Division — 18 sub-admins

Plant 1 Choi · Plant 2 Jung · QA Han...

Logistics Division — 15 sub-admins

Seoul Center Oh · Busan Center Kang...

Other Divisions — 26 sub-admins

71

Sub-admins

4

Divisions

Autonomy+Control

Operating model

Korea Railroad Corporation's actual operating structure

## How L&D admin work changes

| Task | Traditional Method | AI Admin |
| --- | --- | --- |
| Learning status check | LMS admin page → Excel download → pivot table | "Show Team A's completion rate" — one message |
| Report creation | Monthly, half-day effort | Conversational CSV export, minutes |
| Non-completer management | Manual list extraction + individual notifications | AI auto-classification + reminder target extraction |
| Data analysis | Requires dedicated analyst | Admins query directly via natural language |

### Related Features

[AI Assistant](https://www.touchclass.com/en/ai-assistant) [Admin Dashboard](https://www.touchclass.com/en/dashboard) [Managed Services](https://www.touchclass.com/en/operate)

## Let AI Admin handle your training operations. Start with TouchClass.

[Book a Free Demo](https://www.touchclass.com/form/contact)

## Related resources

- [AI features overview](https://www.touchclass.com/markdown.php/en/ai-features.md): Six AI capabilities — content creation, learning assistant, admin automation, curation, ShortClass, and ReFlash.
- [AI Learning Assistant](https://www.touchclass.com/markdown.php/en/ai-assistant.md): An AI chatbot trained on your own training materials; instant answers, no searching.
- [AI Curation](https://www.touchclass.com/markdown.php/en/ai-curation.md): AI content recommendations tailored to each learner's role, history, and goals.
- [AI ShortClass](https://www.touchclass.com/markdown.php/en/ai-shortclass.md): Auto-convert long videos into 10–60s short-form clips, with keyword-based recommendations and five types of learning analytics.
- [ReFlash (Alpha)](https://www.touchclass.com/markdown.php/en/reflash.md): Turn a script or PDF into narrated video with images and subtitles, with MP4 export and batch workflows depending on content length and settings.

> Source governance: https://www.touchclass.com/data/source-governance.json · Full LLM context: https://www.touchclass.com/en/llms-full.txt · Structured data: https://www.touchclass.com/data/capability-effects.json, https://www.touchclass.com/data/solution-use-cases.json