In recent years, generative AI such as ChatGPT has been born, and AI continues to develop. Under these circumstances, the demand for AI human resources who can handle AI-related technologies is increasing. However, even though we call them AI personnel, their work is diverse, from engineers who develop AI to project planners and researchers.
Here, for those in charge of companies considering entering the AI field, we will introduce the types of AI human resources, required skills, and in-house training methods.
table of contents
- 1 What is AI human resources?
- 1 What kind of human resources are AI human resources?
- 2Difference between AI human resources and digital human resources
- 2 Why AI human resources are important
- 1Eliminating human resource shortages
- 2 The future of AI technology
- 3 This will help address the shortage of human resources due to the declining birthrate and aging population.
- 3 Types of AI human resources
- 1 Human resources engaged in the development and research of cutting-edge AI algorithms
- 2 Human resources involved in AI development
- 3 Human resources who lead AI business planning and business
- FourHuman resources who can analyze data using AI tools and utilize it for business
- Four skills required for AI personnel
- 1 programming
- 2 data science
- 3 machine learning, deep learning
- Four digital literacy
- Five Domain knowledge for each business
- Five How to develop AI human resources
- 1 Challenges in AI human resource development
- 2 How to solve the challenges of AI human resource development
- 3 Steps to develop AI human resources
- 6 summary
What is AI human resources?
First of all, let’s take a look at what kind of human resources are AI human resources. Here, we will provide an overview of AI human resources and explain the difference between them and IT human resources, which are often confused with each other.
What kind of human resources are AI human resources?
AI human resources are human resources who have knowledge and skills in machine learning, deep learning, data science, etc., and who build and operate AI systems and improve technology. Due to their characteristics, AI human resources are often associated with science backgrounds, but humanities backgrounds can also play an active role in advancing projects and promoting the introduction of AI.
In recent years, as the use of AI has progressed in various fields, developing and acquiring AI human resources is considered an important issue not only for companies but also for the nation. Plans have already been announced in the United States to train teachers to develop AI human resources, and a project has started in China to develop human resources involved in creating innovation.
Difference between AI human resources and digital human resources
Digital human resources are often confused with AI human resources. The Small and Medium Enterprise Agency’s “ Small and Medium Enterprise White Paper (2023 Edition) Part 2, Chapter 3′ ‘ defines digital human resources as “ Classification of human resources compatible with digital business in the Information-technology Promotion Agency (IPA) ` `DX White Paper 2021.” Concerning the above, digital human resources are classified into two categories: “human resources who promote digitalization strategies” and “human resources responsible for digitalization technology.” While AI human resources are people who specialize in AI-related knowledge and technology among digital and IT technologies, digital human resources are people who are engaged in the information service industry and IT software and service provision business, which refers to a broader range of human resources, including employees in the information systems department.
Why AI human resources are important
As mentioned above, AI human resources are considered important and necessary for both corporate growth and national growth. Let’s look at the reasons for this from three points.
- Eliminating human resource shortages
- The future of AI technology
- This will help address the shortage of human resources due to the declining birthrate and aging population.
Eliminating human resource shortages
With the rapid spread and development of AI-related technologies, the demand for AI human resources has increased, and the shortage of AI human resources has become obvious. According to the Ministry of Economy, Trade and Industry, the shortage of AI/IT human resources is predicted to expand from approximately 370,000 in 2020 to approximately 790,000 in 2030 (*). AI-related technologies are used in a wide variety of fields, including manufacturing, retail, medical care, agriculture, and logistics, and as the demand for AI human resources continues to grow, the shortage of human resources is expected to expand.
While there is a need for AI human resources, it is currently difficult to develop AI human resources who can become a force. As I will explain later, training AI talent is difficult because they require many skills, including knowledge of machine learning and deep learning, as well as programming and data science knowledge and techniques for utilizing big data. Therefore, the government has started implementing skills certification systems, etc., but the shortage of AI human resources will continue for some time.
The future of AI technology
AI-related technologies are still in the development stage, and the promise of the future of AI technology itself is one reason why AI human resources are becoming more important. We are currently in the era of the third AI boom, and developments continue, including the accumulation of big data due to the spread of the Internet and smartphones, and the emergence of generative AI. AI technology is now being used in services created by companies and in business systems. Therefore, countries and companies around the world are looking forward to the future of AI technology.
This will help address the shortage of human resources due to the declining birthrate and aging population.
The development of AI technology is also expected to play a role in preventing human resource shortages and declines in productivity due to the declining birthrate and aging population. In many developed countries, including Japan, there are concerns about labor shortages and declining productivity due to the declining birthrate and aging population, as well as a decline in social functions, and AI technology is essential to maintaining the standard of living.
Examples include training new employees using AI technology and introducing AI technology into administrative services. Furthermore, efforts have begun to incorporate AI technology into health management applications provided by the government, aiming to extend healthy lifespans as the population ages.
In this way, if AI technology makes life richer and more convenient, it will be possible to ensure sufficient productivity and maintain social functions even in an aging society with a declining birthrate. The importance of AI human resources is increasing to compensate for labor shortages in an era of declining birthrates and an aging population and to maintain living standards and social functions.
Types of AI human resources
So, what types of AI human resources are there? First, we will classify and explain AI human resources into the following four categories based on the human resources that can handle digital business as described in the “DX White Paper 2023” by the Information-technology Promotion Agency.
- Human resources engaged in the development of cutting-edge AI algorithms, etc.
- Human resources involved in AI development
- Human resources who lead AI business planning and business
- Human resources who can analyze data using AI tools and utilize it for business
Human resources engaged in the development and research of cutting-edge AI algorithms
These are people who are responsible for advanced technologies such as machine learning and blockchain. In practical terms, we conduct research to improve AI processing speed and accuracy and develop algorithms that can be utilized at the implementation level based on various research. English is often used to write, present, and read papers, and some researchers work at universities, research institutes, and companies while conducting research and development.
Human resources involved in AI development
It mainly refers to engineers, and the “DX White Paper 2023” introduces two types: “Tech Lead” and “Engineer/Programmer.”
- Tech lead: A person who can design and implement AI-related systems and lead projects.
- Engineer/Programmer: Personnel responsible for specific technical tasks such as AI implementation, infrastructure construction, maintenance/operation, and security.
As mentioned above, human resources involved in development implement and develop AI technology, so they not only have technical knowledge about AI but also understand the needs of customers who use products and services and market trends. You must implement and develop software and systems.
Human resources who lead AI business planning and business
My position is to combine knowledge of AI and business knowledge to plan products and services that utilize AI. Referring to “DX White Paper 2023”, it can be divided into the following.
- Leadership talent who will lead the realization of AI business
- Human resources responsible for planning, drafting, and promoting AI projects
Planning staff often belong to companies that handle systems and software. Compared to engineers, technical skills are not required as much, but communication skills and business knowledge are important for managing and progressing projects, so they are attracting attention as AI human resources with liberal arts backgrounds.
In addition, the people who lead the business need to give instructions not only to the members but also to the AI, so they need to acquire direction skills such as creating prompts for giving instructions.
Human resources who can analyze data using AI tools and utilize it for business
In particular, AI talent is someone who can use AI tools in business to analyze and evaluate data. It is necessary to understand the characteristics of each AI model and data analysis method, use them appropriately depending on the situation, and have the skills to evaluate the output results of AI.
Currently, there is a chronic shortage of data scientists who perform data analysis, and according to the Data Scientists Association, 58% of companies answered that they were unable to secure the number of people they targeted when recruiting. Masu(※).
* Data Scientists Association “ Results of a survey regarding the recruitment of data scientists ”
Skills required for AI personnel
When it comes to AI human resources, the skills required differ depending on the industry. Therefore, we will explain each skill that is often required for AI human resources.
- programming
- data science
- machine learning, deep learning
- digital literacy
- Domain knowledge for each business
programming
Programming skills are skills mainly required by developers (engineers). In particular, the programming language Python is often used in the field of AI technology and is used to develop tools such as machine learning and data analysis, as well as various applications. When training AI human resources, it is a good idea to have them learn Python first.
In addition to Python, languages that are in high demand by IT engineers such as C++, R, and JavaScript can also be used for AI development. Therefore, if your company has IT engineers who can speak these languages, it will be easier to train them as AI human resources.
data science
Data science skills are primarily required by researchers and data scientists. Using methods such as statistics, information engineering, and algorithms, we extract new insights and information meaningful for business from vast amounts of data. In particular, the use of AI technology in recent years always involves big data, so human resources who can handle data science are essential.
Furthermore, it is the data scientist’s job to think about how to utilize the extracted information. Sometimes I work backward to figure out what kind of results I want and think about what kind of data and what kind of logic I should use to arrive at the results. We also perform tasks such as “data cleansing,” which formats big data to make it easier to handle.
machine learning, deep learning
Machine learning and deep learning are representative areas of AI technology that are currently widely used. Therefore, knowledge of machine learning and deep learning is an essential skill for anyone involved in an AI project. Machine learning is a technology that allows AI to read data and find patterns and rules, and also derives rules and patterns to make judgments and predictions. In addition, deep learning is a machine learning method that uses a multilayer neural network to extract features from data on its own.
Although specialized skills are required by researchers and developers, basic knowledge is a must for any AI talent.
digital literacy
Digital literacy is the skill to properly understand and utilize various information handled by computers and is a skill necessary for all AI personnel. The term “Di-Lite” was defined by the Digital Literacy Council as a term to describe digital literacy.
Di-Lite is a term that spans three areas: “IT software area,” “mathematics/data science area,” and “AI/deep learning area.” In the business field, where DX and AI technology are predicted to become more widespread in the future, it is considered a common literacy that all business people should have.
Under these circumstances, the government is also emphasizing the acquisition of mathematical knowledge, such as the Ministry of Education, Culture, Sports, Science and Technology’s changes to the mathematics curriculum.
Domain knowledge for each business
AI development and implementation will not be successful just by knowing AI. To achieve results, it is necessary to have a deep understanding of the industry in which you work.
Utilizing AI is just a means to make your business successful. Therefore, in modern times, there is a need for people to understand the characteristics of AI and be able to match it to business.
How to develop AI human resources
As mentioned above, AI human resources are highly important, but it is also true that it is quite difficult to secure them through recruitment. Therefore, we will explain how to develop AI human resources in-house, breaking them down into issues, how to solve them, and the steps to develop them.
Challenges in AI human resource development
First, what kind of challenges can be considered in AI human resource development? I will introduce three points below.
The burden of developing a training plan
When training AI human resources in-house, there is a risk that the task of formulating a training plan becomes a burden for human resources personnel. This is because while running the existing business, we also have to create a development plan. Some concerns allocating human resources to training will reduce the number of human resources available to work on existing businesses or increase the burden on those in charge, worsening the workload.
In addition, many companies do not know how many AI personnel they need or what skills they need in the first place. To develop AI human resources within your company, you must first identify the necessary human resources before creating a training plan.
Difficult to find teaching materials that can be used in practice
One of the major challenges in developing AI human resources is the lack of educational materials for developing AI techniques that can be used in the field. Case studies based on actual cases are the most effective, but there are still not many teaching materials on AI technology that go into practical situations.
To begin with, AI technology itself is still in its development stage, and there are only a few cases in which it is used in practice, which is a factor, but the quality of learning will greatly change depending on how much education is put to use in practice.
Difficult to improve skills
This is related to the lack of teaching materials that can be put to practical use, but another issue that stands in the way of developing AI human resources is the inability to conveniently find opportunities to improve skills. In particular, since AI projects are often important projects for companies, it is difficult to improve skills through actual projects.
How to solve the challenges of AI human resource development
So, what kind of solutions can be considered to resolve the issues mentioned above in AI human resource development? Here, I will focus on three points.
self-study
One way to solve the problem of in-house resources being allocated to developing a training plan is to encourage self-study. If employees self-study themselves, they will be able to learn to a certain extent without the need for someone in-house to create a training plan one by one. For example, you can watch already-created video content or study qualifications related to AI.
Examples of qualifications that allow you to learn about deep learning theory and how to utilize AI include the E qualification and Generative AI Test for engineers, and the G test for non-engineers.
However, while self-study is effective for beginners and those who acquire introductory-level skills, it may not be as effective as expected for those who have more than a certain level of skill. Once you have acquired a certain level of skills through self-study, you can shift to external training and skill improvement, which will be discussed later.
Incorporate external training
External training will solve the problem of finding it difficult to find teaching materials that can be put to practical use. In particular, we will work on solving problems and developing business plans through discussions and role-playing at workshops. This method of learning in the form of exercises using practical problems as subject matter is a training method suitable for intermediate to advanced AI personnel.
Determine the goals you want and the skills you need
To solve the problem of difficulty in improving skills, it may be helpful to identify the goals desired by the company and the skills required to achieve them and narrow down the skills to be learned. Even if you blindly learn more and more skills, it will only increase the burden on the person and the cost of training, and you will not be able to acquire skills that can be put to practical use.
Especially when starting a project with the main purpose of improving skills, carefully consider what skills are required and whether the project can be used to acquire skills.
Steps to develop AI human resources
We will introduce the general steps of AI human resource development as an example.
- 1st year
– Create a training plan and select training targets
– Conduct training to acquire introductory-level knowledge and think of ways to apply it to your company’s business. - 2nd year
– Learn how to proceed with a project and learn basic skills such as programming languages, logical thinking, and machine learning
– Learn the basics of deep learning and perform demonstrations using in-house data - 3rd year
– Start an AI project and acquire the individual application skills necessary for the project
– Generate 2-3 success stories that lead to business results
The example given here is just an example, but it is generally recognized that it takes about three years to be able to produce results as an AI human resource. If you are wondering how long it should take to train AI human resources, three years is a good guideline.
summary
There are various types of AI human resources, including researchers and developers, and as demand increases, it is becoming extremely difficult to recruit them. One way to secure AI human resources is to train them in-house. Develop AI talent with the skills your company needs by incorporating self-learning tools and external training.
