As the 4th industrial revolution begins in earnest, AI (Artificial Intelligence) is becoming a key driving force for innovation and growth in various industrial fields, going beyond a simple technological trend. On the other hand, many companies that are trying to introduce and utilize AI often lose their direction and wander in the early stages. Accordingly, a practical and systematic roadmap for successful introduction and utilization of AI has become more important than ever.

The recently published 'Artificial Intelligence for Business: A Roadmap for Getting Started with AI' provides practical guidance for these companies.

The authors of this book, Jeffrey L. Coveyduc and Jason L. Anderson, Anderson) presents a roadmap for leveraging the economic and technological potential of AI to its fullest potential, and how to drive business value creation and innovation.

First, the cases of FANUC Corporation, H&R Block, and BlackRock clearly show how AI is creating value in various industries such as manufacturing, service, and finance.

Japan's FANUC Corporation, a leader in robot manufacturing and factory automation, is changing the paradigm of industrial production through AI.

The company is implementing "lights-out operations" in its factories, where robots manufacture robots, freeing up humans to focus on administrative tasks.

FANUC is achieving high efficiency by applying deep learning models that utilize AI-based data to increase process precision and accelerate speed.

In particular, it has improved the robot's parts selection accuracy to over 90%, overcoming existing limitations.

H&R Block, a U.S. tax preparation service company, has significantly improved customer satisfaction through AI.

Working with IBM Watson, we built a system that analyzes customer conversations to find the maximum number of tax deductions possible.

We analyzed customer speech through natural language processing (NLP) and recommended related deduction items, helping tax professionals perform their work more efficiently.

This technology has improved the quality of tax preparation services while providing trust and satisfaction to customers.

BlackRock, the world's largest asset manager, is using AI-based Aladdin software to analyze financial data, manage risk, and support investment decisions. led the change.

Aladdin uses massive amounts of data to accurately calculate investment risks and provides models to help you make better decisions.

BlackRock is leveraging AI to overcome the limitations of data stream analysis and achieve higher performance. The advanced analytical capabilities provided by AI play a key role in securing a competitive edge in the financial markets.

Based on these cases, if we look at the roadmap for introducing AI, the first step in introducing AI is to generate a clear idea.

Organizations must clearly define the problems they want to solve and the goals they want to achieve through AI.

The authors highlight how to use business process mapping and value analysis to organize and categorize ideas that fit the unique needs of each organization. This process is also closely related to creating an innovation culture in the organization.

Next, the success of an AI project depends on data.

The book addresses the importance of data quality and accessibility, and emphasizes that data scientists play a key role in projects.

It also highlights that AI can only work well when data governance and curation are done properly, revisiting the classic principle of “garbage in, garbage out.”

AI systems are not perfect in their early stages. The authors recommend continuous improvement of the system through prototyping and feedback loop design.

It is important to conduct proof of concept using a minimum viable product (MVP) in the early stages and analyze the possibility of creating business value based on this.

After a successful prototype is completed, the next step is to develop it into a commercially viable system.

This process requires technical assessment, building a user security model, and applying an automated testing framework.

This ensures the stability of the AI system and helps it operate smoothly within the organization.

Finally, the authors emphasize that the introduction of AI is a beginning, not an end.

There is a need to continuously monitor the performance of AI systems, adopt cutting-edge technologies, and integrate user feedback to improve the system.

This will enable AI to move beyond being a simple technical tool and become a core business asset.