Hello everyone, My name is Kenshin Fujiwara and I am the CEO and founder of HACARUS Inc.
Through this series of blogs, I will discuss a wide range of topics of AI, from the history of AI to practical tips for successful application of AI projects. I hope my blog posts will help you gain a better understanding of AI and solve your business issues.
So far, I have described the steps for AI implementation, but which steps should we focus on? In general, the points of focus and methods for approaching an AI project will differ depending on the organization’s knowledge and experience.
From today, we will focus on three key points that are critical for the success of AI implementation. Based on my experience working with many companies, I will share my thoughts on common points of failure for AI implementation. I also would like to discuss how to create internal systems and organizations. For these points, it isn’t necessary to perfect all of them, but instead, consider which are important to your organization’s objectives.
So first, here are the three key points:
Point 1: AI implementation stages moving forward
Point 2: Full-scale AI implementation stages moving forward
Point 3: Stages for existing AI systems and future deployment
Point 1: AI implementation Stages Moving Forward
If AI implementation is still in the early stages, the first things to consider are “organization” and “human resources”. These days, many companies are beginning to establish cross-organizational teams such as a “DX Promotion” department. These kinds of organizational structures make sense since cooperation across departments is essential for digital transformation and AI implementation. In some cases, however, the creation of these cross-organizational teams can create a power struggle within the company.
To help combat this issue, it is important for the management team to communicate their commitment to the AI project to all relevant members. I also recommend you to find methods that work for your company. For example, place a key member of the management team in charge of these tasks, or establish a reporting line directly to the management team.
Developing In-house AI specialists
Companies should also focus on developing in-house AI specialists. As mentioned in the previous blog, there is currently a human resource barrier, where there is a lack of qualified AI specialists. When hiring an AI specialist, the hiring process may be time-consuming. To attract highly qualified applicants, you might also be required to offer very favorable terms and conditions.
During the AI implementation process, there is a wide range of areas that need to be considered. However, it is not uncommon for AI specialists to have limited areas of expertise and skills.
When it comes to human resources, there are several types of AI specialists. There are those who are skilled and knowledgeable about how to utilize AI in business, those who are good at combining existing AI tools to create software, and those who have extensive theoretical knowledge and can create AI from scratch.
When hiring new staff, it is important to avoid a situation where the company puts in a lot of effort to hire an AI professional, only to find out that they don’t match the company’s needs. One solution is to train these AI personnel within the company. Although training might seem like a long, difficult, and costly process, it is the first step for organizations that are new to AI implementation. I believe that training and developing employees is a reasonable decision in the long run.
As an additional benefit, if the company aims to expand its organization by hiring in the mid to long-term, having members who are trained in-house can become a strength. These members can reduce the risk of the previously mentioned personnel mismatches during the hiring process.
The Methods for Human Resource Development
Developing AI personnel does not necessarily mean acquiring highly specialized skills such as data analysis or programming. As a first step, it is sufficient to gain a bird’s-eye view of what AI can do and how to develop it in the future.
The methods for human resource development are becoming more readily available. At the same time, training courses also make it easier to train employees with courses for AI business planning and more. When considering these courses, I recommend that you research the business areas that the training provider specializes in beforehand. It is also useful to check if past participants are involved in industries close to your own. This is because even with the same AI technology, its application may vary depending on the business area being explored. Aside from professional courses, there are also options for self-study. Now, there are plenty of online materials available, or you can take advantage of certification exams to gain comprehensive knowledge.
Playing around with AI Tools
For individuals who want to get a feel for the practical side of things, I also recommend trying out tools that allow you to develop simple AI without the need for coding or programming knowledge. These tools allow users to develop AI without writing source code and are offered by cloud vendors such as Google, Microsoft, and Sony.
With these tools, simple AI models, like a model that can differentiate cats and dogs, can be quickly built as long as data is available. By playing around with AI, you will gain firsthand experience with how AI is constructed, learns, and produces solutions.
Through training courses, self-study, and first hand exposure to mini-projects, people can gain a reasonable understanding of how to proceed with an AI project within six months. Once reaching this point, they can begin working on the steps covered in the previous sections, focusing on their own company.
In the next blog, I will continue to discuss other key points for successful AI implementation. For your updated knowledge and insight about AI technology, subscribe to our newsletter or visit HACARUS website https://hacarus.com.