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AX Basics for Corporate Employees: Learn How to Use AI at Work in 5 Minutes

Learn to use AI for work by reviewing business examples, writing prompts, and checking the results. Learn how to divide tasks into steps to delegate to AI and steps for you to review, enter materials and make requests within the scope permitted by your company, and compare the results of summaries, reports, meeting minutes, emails, and numerical tasks against the original materials.

3 learners are taking this course

Level Beginner

Course period Unlimited

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What you will gain after the course

  • I understand what AI does well and where it is prone to mistakes, and choose what to delegate first in my work.

  • Before adding company materials, know what to check, include the purpose, materials, requirements, and format in your request, and if the first response is unsatisfactory, point out what needs to be improved and ask again.

  • For everyday document tasks such as summaries, reports, meeting minutes, emails, and numbers, I compare AI’s results with the original material before using them.

  • Share effective prompts with the team, verify their impact through records, and change one of my tasks for 30 days.

  • We distribute AI-transformed tasks within the team and talk with team members who feel anxious about AI.

AX Basics for Corporate Employees: Learn How to Use AI at Work in 5 Minutes

(Subtitle: Learning to use AI at work by reviewing work examples, writing prompts, and checking the results)



1. Content Introduction


You often hear that you should try using AI at work, but when it comes to figuring out how to apply it to your own tasks, it can feel daunting. It may seem convenient to ask a question once and copy the answer, but it is easy to use it as is without checking whether it is correct. You may also hesitate to use AI at all because you are unsure whether it is okay to enter company materials. Using it this way will not change the way you work, even if you try AI a few times.


AX in the workplace—in other words, AI transformation—is less about learning another new program and more about reexamining the sequence of your work. Once you complete this process, you can distinguish which steps in your work to entrust to AI and which steps you need to verify yourself. Within the scope permitted by your company, you enter the relevant materials, clearly specify the result you want, compare the result you receive with the original materials, and then use it. Rather than looking only at how quickly the first draft was produced, you can also consider the time spent revising and verifying it to determine whether the work was actually reduced.


2. Content Features


One question per episode, kept short.


Each episode is 6–7 minutes long and covers just one question that people genuinely ask at work, such as “How can I verify numbers calculated by AI?” Watching a single episode is enough to fully learn its content, so you can choose whichever episode you need right now.


We follow along using materials commonly encountered at work.


We explain using materials that are laborious to handle manually, such as event notices, business trip policies, meeting notes, and quotations. We show the entire process in one flow: what materials to provide, how to make the request, what results are produced, and what people need to cross-check. All examples are created for educational purposes, and this is indicated on the screen as well.


We look at what to delegate and what to verify together.


Along with what AI is good at helping with, each time we point out where a person should verify the results. We first show useful outcomes and the effort they save, then cover how to check details such as dates, amounts, and conditions against the original materials—details where mistakes can cause problems. In every case, we also make sure to check whether the tools and materials are approved by the company.


It flows through four stages, with each stage announced by a chapter title screen.


Each episode follows four stages: concept explanation, use cases, application ideas, and a key summary. Whenever the stage changes, an intertitle screen and a brief guide indicate what is being explained, and the episode concludes with a summary of three key keywords.


We do not cover how to use the menus of any specific service.


Because each company uses different AI tools, this course covers prompting and verification methods that can be used with any tool. No programming knowledge or prior experience with specialized tools is required.


3. Target Audience


This course is for company employees who are trying to incorporate AI into their work for the first time.


- Employees who have heard a lot about AI but have not yet used it for work

- Employees who have used it a few times but aren’t sure how much they can trust its answers

- Employees who hesitate to use AI because they are concerned about whether it is safe to input company materials

- Team leaders whose team members have started using AI



4. Learning Objectives


By the end of the course, you will be able to.


1) Understand: Know what AI does well and where it is prone to errors, and choose what to delegate first in your work.

2) Ask: Know what to check before entering company materials, make requests that include the purpose, materials, conditions, and format, and if the first answer is unsatisfactory, point out what needs to be corrected and ask again.

3) Verify: In routine document tasks such as summaries, reports, meeting minutes, emails, and figures, compare AI’s output with the original materials before using it.

4) Expand: Share effective prompts with your team, verify the impact through records, and change one of your tasks for 30 days.

5) Lead (optional): Share AI-transformed workflows within the team and talk with team members who feel anxious about AI.



5. Table of Contents


[Course Introduction]

01. Course Introduction: Learn How to Use AI at Work in 5 Minutes


[Understanding]

02. What is AX at the company, and how will my work change?

03. What kinds of tasks is AI good at, and where does it make mistakes?

04. What should I have AI handle first in my work?

05. Which AI tool is right for my work?


[Requesting and Checking]

06. What should I check before putting company materials into AI?

07. How should I ask AI to do a task?

08. When the first answer falls short, how should I ask again?

09. What should you check before reporting an AI-generated answer?


[For Use in Document Work]

10. When summarizing lengthy materials, how can you include the supporting evidence?

11. What should I tell it to get a draft report?

12. How can we extract decisions and action items from meeting minutes?

13. Can I send an email written by AI as is?

14. How should I verify numbers calculated by AI?

15. Who will review documents created with AI before they are shared?


[Expanding to the Team]

16. How can we use a well-crafted prompt together as a team?

17. Automation and AI agents—how much should we entrust to them?

18. How can we check whether using AI has reduced our workload?

19. How can I change one of my tasks over 30 days?


[Leader’s Choice]

20. How should a team leader divide up work changed by AI?

21. How should I talk with a team member who feels anxious about AI?

Recommended for
these people

Who is this course right for?

  • Employees who have heard a lot about AI but have not yet used it in their work

  • An employee who has tried using it a few times but isn’t sure how much to trust the answers.

  • Employees who hesitate to use it because they’re worried about whether it’s okay to enter company materials.

  • A team leader whose team members have started using AI

Need to know before starting?

  • No development knowledge or special experience with AI tools is required.

  • The hands-on exercises use AI tools approved by the company and sample materials for training.

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Packed with practical know-how you can use right away in your business work.
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<Open Learning Lab>

* After working in the fields of e-learning, edtech, and lifelong learning, currently serving as the director of Open Learning Lab Co., Ltd.
* A doctor of educational technology with a strong interest in how individuals and organizations learn and grow
* Focused on turning ideas into reality in areas such as digital learning, edtech, lifelong learning, and the metaverse
* Active as a business content creator producing various types of content needed for business

 

<Business Areas>

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* Data analysis and learning analytics
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* Metaverse-related lectures and consulting, and world-building projects
* AI-powered vibe coding and agentic coding
* AX-related trends and consulting, etc.

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21 lectures ∙ (2hr 14min)

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