2023 AI Trend Predictions. The era where anyone can be a creator with no-code AI.

1. What is No-Code?

1-1. What No-Code Means

The term "No Code" first appeared in a blog post published in 2019. In the article titled "The Rise of 'No Code'", the term is used to refer to methods and services for developing applications solely through screen operations without writing code. Until now, developing applications required learning coding or programming first. However, by utilizing no-code tools, a wide range of people, not just IT professionals, can participate in application development.

>>The Rise of “No Code” (English)

1-2. What is Low Code?

Alongside no-code, a term you often see is low-code. While no-code involves writing no code at all, low-code refers to a method of developing applications by writing as little code as possible.

1-3. A Surprisingly Long History of No-Code

The terms no-code and low-code have emerged recently, but looking back at the history of computers, it is clear that efforts towards no-code and low-code have been ongoing for a long time. Many engineers and programmers have repeatedly experimented to develop applications with as little programming as possible. Throughout this evolution, programming has been streamlined, leading to the creation of software and services that allow users to operate computers solely through graphical interfaces, which is now commonplace. Microsoft Excel is also a product of these efforts.

1-4. Addressing Diversity in Society with No-Code

In recent years, as people's interests and ways of working have diversified, customer needs have become more complex and individualized, requiring companies to constantly undertake new initiatives. To sustain business by adapting to societal diversity, a method that involves smaller investments while rapidly nurturing more services and products is needed, rather than the traditional approach of investing large capital with the expectation of big returns. This approach is perfectly suited to no-code. With no-code, it becomes possible to explore previously untapped fields while keeping operational costs low. The speed from development to release, a hallmark of no-code, also helps ensure business opportunities are not missed.

2. No-Code/Low-Code Market Forecast for 2023

2-1. The Rapidly Growing No-Code/Low-Code Development Market

Let's take a look at the development scale trends in the domestic no-code/low-code development market from 2019 and the forecasts up to 2025.

Source: Created by the author based on ITR "ITR Market View: Low-Code/No-Code Development Market 2022"
*Targets vendor sales scale for the fiscal year ending in March. Figures from 2021 onward are forecasts.

 

The market is expanding at an annual growth rate exceeding 20%, and it is forecasted to reach a scale of 100 billion yen in fiscal 2023. The ease of maintenance and the benefits of in-house development, which are characteristics of no-code/low-code, are beginning to be recognized by many companies.

3. Addressing the Shortage of AI Talent with No-Code

One of the reasons why no-code, which should have been a common methodology until now, is gaining attention at this time is the shortage of human resources. There is a lack of personnel known as IT professionals who possess specialized skills such as programming.

80% of companies are facing a shortage of IT personnel

Let's take a look at the data from a survey conducted in 2020 targeting domestic IT companies, regarding the perceived surplus or shortage of IT personnel.

Source: IPA "Survey on Skill Transformation in the Digital Age" April 22, 2021, created by the author from the "IT Human Resources White Paper"

 

Combining those who feel "significantly lacking" and "somewhat lacking," it is clear that over 80% of companies are experiencing a shortage of IT personnel. This survey targets IT companies, but nowadays, in any industry, having IT knowledge is often necessary to realize new ideas in business. IT personnel can be considered essential staff. However, the current situation is that the supply does not meet the demand. Even if existing personnel acquire specialized knowledge to become IT personnel, it takes time and cost.

3-2. Growing Demand for AI Talent

The group known as AI personnel who embody AI are also IT personnel at the same time. Due to the AI boom, the IT personnel who were already in short supply have also taken on the role of developing AI, creating a situation where the labor shortage is becoming increasingly severe. There are two representative roles of AI personnel as follows.

 

・Data Scientist
A data scientist is a person who analyzes data based on statistics and algorithms to create value and solve problems. In AI development, the challenge is to perform analysis and classification suited to the purpose from vast amounts of data and to identify the role that this data plays in improving AI accuracy.

 

・AI Engineer
Also known as ML (Machine Learning) Engineer. This role involves actually performing machine learning, which is essential for AI development, and building the systems that enable AI to function.

 

These AI personnel require knowledge of mathematics and statistics, as well as programming skills to implement AI tailored to the actual work environment. It is difficult to find such personnel immediately, and even when found, many companies face various challenges, such as disagreements over compensation.

3-3. No-Code as a Measure Against Talent Shortage

No-code is gaining attention as a way to improve such situations.

 

No-code tools can be used with general IT knowledge. Until now, it has always been necessary to secure IT personnel regardless of the scale or complexity of the system to be built. However, by utilizing no-code tools, it becomes possible to address small-scale ideas or situations where a simple system is sufficient with just the existing personnel.
In situations such as creating prototype models or digitizing for business improvement, no-code can be a great help.

3-4. Concerns about No-Code

As a rule, no-code tools can only use the functions provided within their scope. Since they are not suitable for customization, they may not be practical when you want to create a unique system. Also, while programming skills are not mandatory, general IT knowledge will likely be required.

4. Introduction to No-Code AI Platforms

4-1. What is a No-Code AI Platform?

No-code AI is a method of building AI by combining pre-prepared parts, similar to assembling components without programming. To implement no-code AI, it is common to use services from no-code AI platforms. Here are some actual examples.

4-2. Learning Center

This service features an intuitive and user-friendly Japanese UI, allowing anyone to easily develop high-precision AI models without coding. No specialized knowledge in AI or programming is required, and you can manage data, automatically generate AI, and distribute it through simple inputs and clicks.

>>AI inside launches "Learning Center," enabling high-precision AI model development with no code

4-3. No-Code AI Development Tool Node-AI

As the name suggests, it is a no-code AI development tool that allows you to intuitively connect modules from your browser, enabling you to create and execute a complete pipeline from preprocessing time series data to training and evaluating AI models.

>>Introduction to the No-Code AI Development Tool Node-AI

4-4. MatrixFlow

This is a machine learning platform that allows you to create AI that can be utilized in your company's operations, performing data analysis, image recognition, and numerical predictions using AI, even without knowledge of programming languages like Python or specialized knowledge. With MatrixFlow, you can build AI without programming.

>>What is MatrixFlow? A thorough explanation of how to use MatrixFlow and how to use it for free

5. AI Consultations with Human Science

5-1. 48 million items of training data created

"I want to implement AI, but I don’t know where to start."
"I don’t know what to request, even if I outsource."
If your company is struggling with either of these issues, please feel free to contact Human Science. Our company has been involved in AI model development projects across various industries, starting with natural language processing and extending to medical support, automobiles, IT, manufacturing, and construction, just to name a few. Through direct business with many companies, including GAFAM, we have provided over 48 million pieces of high-quality training data. No matter the industry, our team is prepared to handle anything from small-scale annotation projects to long-term ventures with 150 annotators.
>> Human Science’s Annotation Services

5-2. Resource management without crowdsourcing

At Human Science, we do not use crowdsourcing. Instead, projects are handled by personnel who are contracted with us directly. Based on a solid understanding of each member's practical experience and their evaluations from previous projects, we form teams that can deliver maximum performance.

5-3. The latest data annotation tools

One of the annotation tools introduced by Human Science is AnnoFab, which lets you receive progress checks and customer feedback on the cloud, even while the project is ongoing. By ensuring that work data cannot be saved on local machines, we demonstrate appropriate security measures.

5-4. Secure room in office

Human Science has a secure room that meets ISMS standards within our Shinjuku office, so we can handle even highly confidential projects on-site. The promise of of confidentiality is extremely important to us for any of our projects. We provide continuous security training to our staff, and we handle all information and data with the utmost care, even on remote projects.