AXHUB5 cards

3 weeks became
2 days

Instead of promises like "300% revenue,"
five before/after cases with checkable sources.
Down to who did what, and how it was cut.

Every figure here is one we confirmed in the source material

Time was cut1 / 5

01

Quality analysis 3 weeks → 2 days

LG Display's OLED plant.
When a quality defect like screen mura appeared, root-cause analysis took three weeks on average.

They built their own AI, trained on the entire body of process knowledge.
It narrows the cause, proposes a fix, and inspects all production in real time.

Analysis 3 weeks → 2 days.
Savings of over 200 billion won a year.
Design blueprints went from a month to 8 hours.

Source LG official press release · Digital Today · Seoul Shinmun (2025-08)

Time was cut2 / 5

02

Export consulting 7 days → 3 days

Korea's Ministry of Trade, Industry and Energy.
Answering exporters' overseas-certification inquiries took 7 days.

They added a specialized agent trained on overseas-certification material.
Turnaround 7 days → 3 days.

The more important part is this —
with the same staff, consultations went from 70 to 210 a month.
Not just faster; they now handle three times as much.

Source The Electronic Times — 2025 AI public-sector innovation (2025-12)

Time was cut3 / 5

03

Income verification days → seconds

Lloyds Bank, UK.
Verifying income documents in loan review took days.
After automation, seconds.

They didn't leave systems like this in the lab — they put 18 into live service.
A counterexample to "banks are bound to be slow."

Source Google Cloud official case collection (vendor-reported figures)

Time was cut4 / 5

04

5,000 hours → 600 hours

An insurer (Stanford study, anonymized).
The quote to rewrite an aging system: 7 people, 5,000 hours, done in 2027.

They changed the approach with AI coding tools.
Rewrite from scratch instead of patching.
The result: 3 people, 600 hours.

Leadership's next question —
"At this speed, couldn't we build a competitor's system fresh and move in on them?"

Source Stanford Enterprise AI Playbook p.63 (checked against original)

Time was cut5 / 5

05

18 months → a few weeks

A fintech with over 100 million customers (Stanford study, anonymized).
The legacy-migration quote was 1,000 engineers over 18 months.
Effectively abandoned.

Now an AI agent migrates, and engineers only review and apply.
It started finishing in a few weeks, department by department.

The executive in charge said — "In a few weeks, with far less effort, I saw a chance to accelerate."

Source Stanford Enterprise AI Playbook p.21·63 (checked against original)

AXHUBclosing

They share one thing

None of the five had a broad goal like "adopt AI."
Each picked one narrow, time-consuming task and went deep.

What takes three weeks on your team?
That's the starting point.

See the source material on axhub.net

All sources are in the AXHub case library — LG press release, The Electronic Times, Google Cloud, Stanford Digital Economy Lab

AXHub card No.4 — bar lengths are a visual expression of the ratios, not exact scale. Figures follow each card's source.