How Taisei made practical AI skills part of employee development

The problem.

Taisei wanted AI use to support employee development and become a practical part of daily work.

What changed.

HR combined training, internal events, communities and hackathons with access controls, usage logs and monitoring.

As described by OpenAI.

What was reported.

OpenAI reports 90% weekly usage, 3,300 custom GPTs and more than 5.5 hours saved per employee each week. Source: OpenAI

What we take from it.

An employee AI workshop needs a useful first task. We would ask each department to bring a repeated piece of work that can be practiced with approved or fictional data. The exercise should have a recognizable finish, such as a checked meeting brief or a draft response ready for a colleague to review.

Teach review at the same time as prompting. Participants should know how to identify an unsupported claim, check a calculation and decide when the tool lacks enough information. They also need clear examples of what can be entered into the approved system. An accessible internal policy helps people apply those decisions after the trainer leaves.

A shared library should contain a few maintained examples with named owners. We would collect employee feedback, remove prompts that no longer fit the task and measure whether the finished work is useful. The goal is confidence supported by repeatable skills, with quality and review effort tracked alongside time spent.

How to evaluate a similar idea.

Start with your situation and a question you can test. These are evaluation steps we would discuss before choosing an implementation.

1. 01

   Bring a real task

   Choose work with a clear outcome and prepare training inputs that are appropriate to share.

2. 02

   Practice checking

   Ask learners to find unsupported statements, missing context and errors before using a draft.

3. 03

   Keep examples maintained

   Give useful prompts an owner, a purpose and a review date in a small shared library.

4. 04

   Measure complete work

   Include editing and verification when comparing the new workflow with the previous approach.