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Essential Knowledge for AX Strategy Planning

With the advancement of generative AI, many companies are pursuing AX (AI Transformation). However, in the actual field, there are not many educational programs that systematically teach what to do and how to do it compared to the demand that "AX must be done." While most AI education focuses on how to use generative AI or write prompts, this course focuses on the "AX Strategy Planning Methodology" for transforming corporate tasks and services into AI-based ones. This course is based on the practical experience of a 25-year expert who has performed DX/AX consulting and training for large corporations, the financial sector, public institutions, and various companies in the actual IT field. It allows you to learn from a practical perspective not just how to use AI well, but which tasks should undergo AX, to what extent AI should make decisions, how to control risks, and how to design and verify AX projects. Furthermore, it systematically covers core content necessary for actual AX implementation, from understanding the essence of AX to AI thinking systems, AX design methodology, Human-AI role separation, Guardrail design, and KPI and verification structures. In particular, it goes beyond simple theoretical education. Based on real corporate cases such as insurance underwriting, customer consultation, manufacturing quality, internal work support, marketing recommendations, development productivity, and management decision-making, it provides guide templates and sample materials for AX problem definitions, AX hypothesis definitions, AX performance designs, AX service structure diagrams, Guardrail designs, and AX verification plans. This ensures that after taking the course, you can secure the practical capabilities to easily plan and promote actual AX tasks. The biggest differentiator of this lecture is that it teaches how to plan and design AX from the perspective of someone who actually performs AX projects. Specifically, by providing AX strategy planning output templates and seven industry-specific AX cases that can be used in the field, it is designed so that students can refer to cases most similar to their own work and apply them immediately by modifying them to fit their environment. In short, this is not a course to create AI users, but a process to create AX strategy planners who can design and execute a company's AX.

1 learners are taking this course

Level Beginner

Course period Unlimited

AI
AI
Information Strategy Planning
Information Strategy Planning
AX(Agent Experience)
AX(Agent Experience)
AI
AI
Information Strategy Planning
Information Strategy Planning
AX(Agent Experience)
AX(Agent Experience)

What you will gain after the course

  • Acquire a framework of thinking to plan and drive corporate AX (AI Transformation) beyond the simple use of generative AI.

  • How to determine which tasks should be selected for AX and methods for identifying AX projects

  • Secure AX service design capabilities, including distinguishing between AI and human roles and incorporating guardrails, KPIs, and verification structures.

  • Learn how to create practical deliverables, such as AX problem definitions, hypothesis definitions, performance design documents, and service architecture diagrams, through real-world corporate case studies.

  • Acquire practical know-how to establish AX strategies and perform service planning, verification, and execution faster and more efficiently using generative AI.

Essential Knowledge for AX Strategic Planning 🗂

With the advancement of generative AI, many companies are pursuing AX (AI Transformation), but in actual practice, it is difficult to find a clear methodology on what to do and how to do it. While most AI education focuses on how to use generative AI or write prompts, this course focuses on AX strategy planning methodologies for transforming corporate tasks and services into AI-based ones.

This course was structured based on the practical experience of a 25-year expert who has conducted DX/AX consulting and training for various companies, including large corporations and financial institutions. It is not simply about how to use AI well, but a systematic learning experience on which tasks should undergo AX, to what extent AI should make decisions, how to control risks, and how to design and verify AX projects.

Additionally, it is structured so that you can directly review and utilize AX problem definitions, hypothesis definitions, performance design documents, service architecture diagrams, guardrail designs, and verification plans based on real-world corporate cases such as insurance underwriting, customer consultation, manufacturing quality, internal business support, marketing recommendations, development productivity, and management decision-making.



Unique Features of This Course

  • Beyond just how to use Generative AI, you can learn AX strategy planning methodologies to transform corporate tasks and services into AI-based ones.

  • You will learn based on actual deliverables, covering everything from AX problem definition to hypothesis establishment, KPI design, service architecture, guardrails, and verification plans. (Strategic planning guide deliverables provided for immediate application of what you've learned)

  • Based on DX/AX consulting experience for major corporations, financial institutions, and various companies, we provide perspectives and cases that can be immediately applied in the field.

  • Enhance your sense of application through various AX cases such as insurance underwriting, customer consultation, manufacturing quality, internal business support, marketing recommendations, development productivity, and management decision-making.

  • You can secure actionable AX planning capabilities, including the separation of roles between AI and humans, responsibility structures, risk control, and performance verification.


Recommended for these people🙋‍♀

  • AX strategy establishment and task discovery for companies, targeting strategic planning managers


  • AI-based new services and POs and PMs planning products đang lập kế hoạch cho Product

  • IT planners who want to expand existing DX tasks into AX tasks

  • BAs, consultants, and technical sales representatives who need to analyze customer business and propose AI-based solutions

  • Corporate AX consulting and DX/AX consulting practitioners preparing for implementation projects đang chuẩn bị cho các dự án triển khai

  • Business practitioners in companies applying AX (the understanding of working-level staff is also crucial for AX)


What you will learn 📚

PART 0. Course Overview

  • Course Introduction

    • Why is it the AX era now?

    • Individual AI utilization is different from corporate AX.

    • Why do those in charge of AX experience difficulties?

    • From DX Consulting to AX Strategic Planning

    • Overall course structure and what you will gain from this lecture


PART 1. Why AX?

  • Evolution from DX to AX

    • What is DX?

    • Core values of DX

    • Limitations of DX and the Emergence of AX

    • The AX Era

    • Key changes in the AX era

  • The true purpose of AX

    • The true purpose of AX

    • Changes beyond productivity improvement

    • Changes in organizational decision-making structures

    • Real-world corporate transformation cases

  • Organizational and Role Changes in the AX Era

    • Concepts of Organizational and Role Changes in the AX Era

    • Limitations of existing organizational structures

    • Role changes after AI

    • Changes in Strategy/Service/PO Roles

  • Understanding the overall structure of AX strategy

    • Understanding the overall flow of AX

    • Understanding the overall structure of AX strategy

    • Characteristics of AI decision-making structures

    • Human in the loop structure

    • Guardrail Structure and the Core of AX


PART 2. AI Thinking System for AX Planners (Think)

  • Difference between AX planning and AI utilization

    • Understanding the difference between AX planning and AI utilization

    • Shift in the Planner's Thinking

    • Why is understanding AI important?

    • The New Role of the AX Planner

  • When is AI needed?

    • When is AI needed?

    • Characteristics of problems that require AI

    • Areas where applying AI alone is not suitable

    • Questions for determining AI applicability

    • Structure of actual AX failure cases

  • Which AI should you choose?

    • Which AI should you choose?

    • Understanding the Basic Concepts of AI

    • Differences between AI / ML / DL / Generative AI

    • AI selection criteria in AX

    • Cost, data, accuracy, and operational perspectives

  • Core AI concepts that AX planners must know

    • Core AI concepts that AX planners must know

    • Data & Model

    • Training & Inference

    • AI Limitations and Hallucination

  • Core Knowledge of Generative AI-based AX

    • Core knowledge of Generative AI-based AX

    • The concept of models in Generative AI

    • Generalization vs. Optimization Issues

    • Performance Improvement (Fine-tuning VS RAG)

    • API AI VS Local AI

  • Separation of roles between humans and AI

    • Criteria for separating human and AI roles

    • Role Separation Thinking Framework

    • Practical Design of Human-in-the-loop

    • Real-world AX service role separation cases

  • Guardrail and AI Control Structure

    • Guardrail and AI Control Structures

    • What is a Guardrail?

    • AI Risk Types

    • Guardrail design methods

    • Difference between Human-in-the-loop and Guardrail

PART 3. AX Problem Definition and Service Design Methodology (Design)

  • AX Problem Framing

    • Understanding AX Problem Framing

    • AX Problem Discovery Methods

    • Data-driven problem discovery

    • Problem structuring methods

    • Practical Guide to AX Problem Framing

  • AX Hypothesis and Ideation

    • Understanding AX Hypothesis and Ideation

    • AX Hypothesis Design Methods

    • Defining AI Utilization Methods

    • Value Validation Thinking

    • AX Ideation Practical Guide

  • Goal-KPI-Verification Structure Design

    • Understanding the design of goal-KPI-verification structures

    • KPI vs AI Performance Metrics

    • AX Verification Structure Design

    • Experiment-based thinking

    • AX Verification Practical Guide

  • AI Function and Service Structure Design

    • Understanding AI Functionality and Service Architecture Design

    • Overall Framework for AX Service Architecture Design

    • Detailed step-by-step methods

    • AX Service Architecture Diagram Task Guide

  • Designing Service Guardrails Based on AI Constraints

    • Understanding Service Guardrail Design Based on AI Constraints

    • Reliability Design

    • Fail-safe structure design

    • Human-in-the-loop structure design

    • Guardrail Design Guide

  • AX Verification and Operation Strategy

    • Understanding AX Verification and Operation Strategies

    • AX experiment design methods

    • Continuous improvement structure design

    • AI Performance Monitoring Strategy



PART 4. AX Strategic Planning Cases and Practical Application

  • Customer Consultation AX

    • Overview of the problem situation

    • Limitations of existing methods

    • AX Application Direction

    • Analysis Case

  • Insurance Underwriting AX

    • Overview of Problem Situation

    • Limitations of the existing method

    • AX Application Direction

    • Analysis Case

  • Manufacturing Quality AX

    • Overview of the Problem Situation

    • Limitations of the existing method

    • AX Application Direction

    • Analysis Case

  • Internal Business Support AX

    • Overview of the Problem Situation

    • Limitations of the existing method

    • AX Application Direction

    • Analysis Case

  • Marketing Recommendation AX

    • Overview of the Problem Situation

    • Limitations of the existing method

    • AX Application Direction

    • Analysis Case

  • Development Productivity AX

    • Problem Overview

    • Limitations of the existing method

    • AX Application Direction

    • Analysis Case Study

  • Management Decision-Making AX

    • Overview of the Problem Situation

    • Limitations of existing methods

    • AX Application Direction

    • Analysis Case Studies


PART 5. AX Execution Acceleration Strategy (Accelerate)

  • Generative AI-based AX Planning

    • The Meaning of Generative AI-based AX Planning

    • Overall flow of Generative AI-based AX planning

    • How to write problem definition prompts

    • AI draft creation based on HTML templates

  • AX 1Pager Strategy Document

    • Concept and Purpose of 1Pager

    • Why the 1Pager is important in AX

    • AX 1Pager Dedicated Template

    • AX 1Pager Item-by-Item Writing Guide

  • Data-Driven AX Planning Practice

    • What is data-driven thinking in AX?

    • Two types of AX data-driven thinking

    • AX analysis methods for internal corporate efficiency

    • Product and Service AX Analysis Methods

    • Data analysis and guide document structure using Generative AI

  • Fast validation based on Vibe Coding

    • Understanding Vibe Coding

    • AX Planner's Perspective on Utilizing Vibe Coding

    • How to Create a Vibe Coding Prototype

    • HTML Prototype Creation Prompt

    • Prototype review and utilization methods

  • AI-based Decision Support

    • The Meaning of AI-Driven Decision Making

    • The basic structure of decision-making with AI

    • Case 1. Using AI in general ideation

    • Case 2. Using AI in document work

    • Case 3. Using AI in Scenario Writing

  • Utilizing AI in Collaboration

    • Stakeholders of an AX Strategic Planner

    • Summary of AI utilization by stakeholder and practical principles

    • Decision-makers, developers, data teams, collaborative decision-making methods and guides


Recommended for
these people

Who is this course right for?

  • Strategic planning manager responsible for establishing corporate AX strategies and identifying projects.

  • POs and PMs planning AI-based new services and products

  • IT planners looking to expand existing DX tasks into AX tasks

  • BAs, consultants, and technical sales representatives who need to analyze customer business and propose AI-based solutions

  • Working-level professionals preparing for corporate AX (AI Transformation) consulting and implementation projects

  • Working-level professionals in companies implementing AX

Need to know before starting?

  • Understanding the basic concepts of IT systems and Digital Transformation (DX) makes it easier to understand the concept of AX.

  • If you have experience using generative AI, you will understand the differences in AX strategic planning perspectives more clearly.

Hello
This is seonsin25

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I am an IT professional who has worked in development, PL, PM, and IT business management within the IT field for 25 years.

I have worked at IT startups, small and medium-sized enterprises (SMEs), mid-sized companies, and large corporations, and

I would like to share various stories and information about the IT industry that I have observed through my work in PM and IT business management.

I run a YouTube channel called [Flaming Man 25 IT Library], and

I am sharing lectures on Inflearn to provide even more information.

Thank you.

 

[Key Career Experience]

Current (Inc.) BPX CTO (Co-CEO)

Former Team Leader of DX Business Division at Corners Co., Ltd.

Former Senior Researcher for Public Projects PM and Business Management at Prompt Technology

Former CTO and Executive Director of Platform Business at Smart Olive

Former General Manager of IT Business Division at Unitrontech

Former HealthConnect

Former Asiana IDT Financial Operations Team

[Participated Projects]

Financial system construction and operation (Kumho Autolease, KDB Life Insurance, etc.)

Smart Hospital (PHR system, hospital kiosk system) and healthcare business PM management

Head of IT Business Division: SI project management and PM, IoT new business planning and development management, etc.

CTO and Head of Business for Electronic Meal Voucher Platform

Public sector project management and PM

[Major Teaching Experience]

- Lectures for major corporations (IT Planning/Proposal, Project Management, and Essential IT Knowledge)

IBK Industrial Bank of Korea, Woori Bank, Mirae Asset Securities, Samsung Life Insurance, SK Telecom, KT Aivle School, KT, KB Kookmin Bank, Samsung Financial Training Institute, 2023 ACE Academy, GS mbiz, CJ Group, Global Fintech Promotion Center, Golfzon, N-tels/N-coms, etc.

- Lectures for major public institutions (Public IT project ordering and management methods)

LH Korea Land and Housing Corporation, Health Insurance Review and Assessment Service, Korea Institute of Startup & Entrepreneurship Development, Korea Professional Sports Association, Korea Employment Information Service, etc.

- Lectures at major educational institutions (Online/Offline)

: SK m&service, KMA (Korea Management Association), Fast Campus, AhnLab Mom-it-lancer, Codestates, Multi Campus, KT Aivle School, SSAFY, etc.

- Major online lecture platforms

: Numerous lectures on the Inflearn platform

[Publication History]

Essential IT Knowledge for Collaborating with Developers [Youngjin.com]

Essential PM Knowledge That No One Tells You [Youngjin Publishing]

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Curriculum

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36 lectures ∙ (7hr 33min)

Course Materials:

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