The use of generative AI (artificial intelligence) has been rapidly expanding in Japan, with AI tools now used across a wide range of fields, including operational efficiency, customer support, and marketing.

Still, as these tools become more widespread, there is growing concern about the costs of using and maintaining them. As an alternative to relying on existing AI services, you can reduce costs by creating AI products tailored to your company’s specific needs.

Fortunately, thanks to the widespread adoption of application programming interfaces (APIs) and open-source software, the development of AI offerings, which was formerly limited to large companies, is now well within the grasp of individuals.

This article will explain how to develop AI products, including the knowledge required for development and how to monetise them.

Key takeaways

• By using APIs and open-source software, individuals can develop AI products.
  
• For individual AI development, starting by building small-scale AI services that combine existing models and APIs is recommended.
  
• In addition to programming skills in languages such as Python, AI development also requires an understanding of security, terms of service, and relevant laws.
  
• By using no-code or low-code tools, people with no programming experience are able to develop simple AI products.
  
• There are various monetisation structures for AI products, including one-time purchases, subscription-based, pay-as-you-go, and hybrid models.
  

Can an individual develop AI products?

When people hear the term “AI”, products developed by major companies, such as OpenAI’s ChatGPT, Gemini from Google, and Microsoft’s Copilot, are likely the first things that come to mind.

Developing a large language model (LLM) from scratch indeed requires vast amounts of data, GPUs, and significant build costs. It isn’t realistic for an individual to accomplish that kind of project on their own.

However, thanks to APIs and open-source models, it is now possible for small groups or solo developers to build AI applications.

For example, an individual could completely build a small-scale AI product that combines existing AI technologies, such as:

• AI chat for a specific industry
  
• PDF summary tool
  
• AI customer service
  
• Image generation service
  
• AI-powered business support tool
  

Not everyone wants or needs a general-purpose AI that handles every task. Instead, there is a growing demand for these tools tailored to specific challenges and workflows. By developing AI products tailored to your company’s website and building the services your customers need, you’ll be able to differentiate yourself from competitors while also keeping costs down.

Key AI basics for individuals

Here are a few things you need to know to make solo AI development easier:

Understanding what AI is

What exactly is AI?

AI refers to technology that artificially replicates human intelligence.

When you think of AI, you might imagine it as being as versatile as a human. In practice, though, it is generally used in the following areas where it excels:

• Calculation and analysis
  
• Text generation
  
• Audio recognition
  
• Image recognition
  
• Translation
  

When developing an AI product on your own, it will likely be something specialised for a particular field.

Understanding the AI development process

By learning from vast amounts of data, AI can provide accurate answers and predictions in response to users’ questions and requests.

Developing large-scale AI models from scratch requires vast amounts of data and high-performance computing.

When individuals build AI products, the typical process involves working with existing models.

Main approaches for AI development by individuals

Below are the most common ways individuals develop AI products:

Develop using APIs

Major companies are making their AI capabilities available as APIs, enabling solo developers to use them to build their own AI applications. For instance, by integrating a text-generation AI API into your company’s website or app, you can build an AI chatbot and an AI-powered customer support system.

The most well-known examples include the OpenAI API and Google’s Gemini API. By using existing models, individuals can develop AI products in a relatively short time.

Develop using no-code or low-code tools

An increasing range of no-code and low-code tools makes AI development more accessible.

No-code refers to a method that requires almost no coding. Low-code development enables the building of applications with minimal code.

There has been a growing number of services that allow users to build AI chatbots and business automation applications with no-code tools. Also, by integrating with external APIs and payment systems, you can develop AI-powered product recommendations, AI-assisted customer service, and subscription-based offerings on a small scale.

It is relatively straightforward to get started, including for those with little programming experience, and it supports personal projects and small-scale AI product creation.

Basic steps for starting AI development as an individual

When starting AI development as an individual, it is common to follow this order of operations:

• Decide what kind of AI product to create.
  
• Proceed with development using APIs and no-code tools.
  
• Conduct tests and make improvements as needed.
  

Rather than attempting to build a large-scale offering from the start, kicking off with a small-scale AI product designed for a narrowly defined use case makes it easier for people to move forward with development.

Skills and knowledge needed for AI development as an individual

When developing an AI product on your own, solo developers need a basic understanding of the technology itself, as well as coding, security, and legal matters.

Basic programming knowledge

When developing AI on your own, having basic programming knowledge will make that process much easier. Although it is possible to create AI products using no-code or low-code tools, programming knowledge is helpful for understanding the APIs in use and building AI applications more flexibly.

Python, SQL, and R are the most commonly used languages for AI creation.

Security and personal information protection

AI services often involve handling user data and personal information, making personal information management and security measures important.

When integrating login or payment functionality, developers must consider measures to prevent fraud.

Additionally, if you will be handling credit card payments, be sure to review the credit card security guidelines and the Payment Card Industry Data Security Standard (PCI DSS) to ensure that operations are secure.

Understanding terms of use and regulations

When releasing or selling AI offerings to the general public, you also need to understand the following points:

• The Personal Information Protection Act
  
• The Specified Commercial Transactions Act
  
• Copyright
  
• API terms of use
  

AI services can raise questions about the treatment of generated content and the use of user data. Make sure you understand the technical aspects as well as the rules and legal requirements for operating the service.

How to turn a solo-developed AI product into a profit-making service

AI products developed by individuals can be offered as services on your company’s website or app and be monetised.

A wide variety of these offerings—including chatbots, tools, and image-generation services—are available online.

AI services can charge users in the following ways:

One-time sales

With one-time sales, users pay once and receive indefinite access to the AI application.

This payment approach works well for small-scale business support applications, such as AI-powered data analysis and chart-creation tools, as it helps sole proprietors lower their costs.

Flat-rate billing (subscriptions)

A flat-rate billing plan charges customers a fixed recurring fee, regardless of use volume. For instance, platforms such as OpenAI’s ChatGPT and Google’s Gemini offer flat-rate plans tied to features and usage.

Unlike a one-time purchase, subscriptions provide continuous updates to additional features and the AI model, giving users access to the latest version.

A subscription method suits users who regularly use AI applications, and it also has the advantage of generating stable revenue for businesses.

Usage-based billing

Usage-based billing is a pricing structure in which charges vary according to factors such as use volume, API calls, or generated output.

With AI services such as image and text generation, operational costs tend to fluctuate based on activity, so a usage-based billing structure is sometimes adopted.

Because the billing reflects the actual amount used, it’s particularly user-friendly for small-scale implementations.

Hybrid billing

Hybrid billing is a model that combines flat-rate and usage-based billing. This pricing structure applies to plans with a fixed base rate that charge additional fees for exceeding a specified number of generations or API calls.

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FAQs

This section answers frequently asked questions about solo AI development.