Thanks to the rapid advancement of artificial intelligence (AI) technology, software development in Japan is undergoing a fundamental change. AI-assisted tools simplify routine tasks – such as drafting code and summarising information – and help developers focus on review, verification, design, and problem-solving.

While its use in software development is gaining attention, businesses still face other challenges: turning that product into a sustainable source of revenue.

In this article, we explain the advantages, main considerations, and monetisation models of AI-based software creation in Japan, against a backdrop of growing concerns about an engineer shortage.

Key takeaways

• Using AI for software development has been gaining attention in recent years because it helps improve efficiency.
  
• AI is used for a variety of tasks, from defining requirements to code analysis and bug prediction.
  
• AI-based software development offers various benefits, but it also comes with challenges that must be considered.
  
• The three main software monetisation models are subscriptions, usage-based billing, and one-time purchases.
  
• Stripe Billing allows you to easily build the right invoicing system for your software service, including setting up billing plans that align with your product's features.
  

Why AI-based software development is gaining attention

One reason expectations for AI in software development are rising is that it can broadly support automation and efficiency across the entire process – from design to implementation, testing, and operations.

As noted in the "METI Journal ONLINE", Japan faces growing concerns about a worsening engineer shortage. Against this backdrop, many companies are showing interest in adopting AI-powered development tools. A wide range of machine learning capabilities, including large language models (LLMs), help with software design, significantly simplify workflows, and improve quality.

In this way, AI is evolving beyond mere programming assistance to become a collaborator that aligns with developers' intentions and supports their work. On the other hand, while AI tools are expected to improve operational efficiency, proper verification and testing remain important to ensure these results are reliable.

The expanding Japanese AI market

As digital transformation (DX) has advanced in Japan, the AI market has also expanded rapidly. Figures from the IT research firm IDC (International Data Corporation) show the Japanese AI market reached ¥1.34 trillion in 2024 (up 56.5% from the previous year) and is projected to grow to ¥4.19 trillion by 2029.

Because the country faces a chronic shortage of software engineers, more companies are turning to AI to improve productivity, and investment in the technology is also rising. Against this backdrop, it is increasingly viewed as a growth investment capable of transforming businesses.

How AI is used in each phase of development

AI can be a powerful aid for simplifying work at every stage of development. Let's take a look at the main ways it's used:

Definition of requirements and design support

AI helps simplify requirements definition and design. In concrete terms, it supports business operations by handling the following tasks:

• Organising and structuring the content of meeting discussions and fragmented requests
  
• Creation and presentation of a logical architecture proposal
  
• Identifying prerequisites and considerations that can be overlooked as projects progress
  

Coding and document creation support

AI-assisted code generation, documentation, and autocomplete tools can produce drafts from a developer's instructions. This reduces the time and effort required to write boilerplate content considerably (standard code or text that remains largely unchanged and is reused in various places). Developers still need to review, test, and adapt the output before using it in production.

Test support, including code analysis and bug prediction

AI systems help teams identify patterns worth reviewing, such as potential defects or insecure code. As a result, developers detect bugs earlier, many of which were often overlooked in the past – but they still must supplement tests, code reviews, and established security practices.

Advantages of using AI

Using AI in software development offers the following benefits:

Faster development

The biggest benefit of AI adoption is improved work efficiency. By automating parts of the workflow, it reduces routine tasks and, more importantly, shortens the time from development to market launch.

Better quality

AI provides objective, consistent analysis, minimising human error and improving quality. Running stable, high-quality tests with AI also helps catch more bugs before launch.

Solo or small-team development

AI-assisted tools can help small teams prototype and build selected software products more efficiently. Production systems still require appropriate expertise in architecture, testing, security, operations, and customer support.

Key considerations when using AI in development

While AI can offer many benefits, consider these key points to use it safely and effectively:

Security and risk of data leaks

Before uploading code or documents, confirm how the AI provider handles inputs and outputs – including retention, access, and model-training terms – and select tools approved for the data's sensitivity.

Especially when handling personal details, proprietary algorithms, or confidential documents such as contracts and proposals, avoid feeding them into generative AI unintentionally. Also ensure the provider excludes submitted data from training, and choose services with strong security features.

Issues around copyrights and intellectual property rights

Information generated by AI might contain copyrighted material. As a result, the generated code or content could closely resemble existing works. This creates the potential for unintended legal issues.

To avoid infringing on others' copyrights or intellectual property rights, thoroughly verify that AI-generated output does not contain excessive quotations from existing articles or books. Also, use caution when handling open-source software released by third parties.

Handling hallucinations and verification by humans

AI generates information through statistical predictions drawn from vast amounts of data. As a result, it might generate what are known as hallucinations: information that does not correspond to the facts or incorrect code that appears accurate at first glance.

Hallucinations increase the risk of unintended, erroneous decisions and operational disruptions. While this is especially true for designing core systems or high-security implementations, you need to treat any AI output with caution. Qualified humans need to conduct thorough code reviews and testing to verify the content's accuracy.

Monetisation models for software developed with AI

To generate profit from a product you've developed, choose a revenue approach aligned with the product's features. Below are three monetisation models well-suited to software products:

Subscription billing

Subscription billing is a recurring billing method in which customers pay a fixed amount at regular intervals (weekly, monthly, or annually), regardless of usage volume or frequency. This model gives businesses more predictable earnings and the opportunity to build long-term relationships with customers.

Usage-based billing

This recurring billing method charges based on actual usage. Common measures include the number of application programming interface (API) calls, the number of characters processed by the system, or the volume of data processed. A main benefit is a sense of fairness tied to actual usage.

One-time purchase (perpetual licence)

As the name suggests, the customer makes a single payment. With this one-time payment, users gain permanent access to the software tools or licence.

Ways to simplify billing and invoicing for AI software

To simplify billing and invoicing for software services, keep the following points in mind:

Measure usage and bill automatically

Automating these processes can substantially improve back-office operations, such as preventing missed invoices.

• Record usage reliably and on the cadence required for your pricing model
  
• Calculate the invoice amount based on the measurements
  
• Generate and send invoices
  

Combining flat-rate and usage-based billing

Also consider a "hybrid model" where, in addition to a fixed base fee, usage-based billing applies once a certain consumption threshold is exceeded. This helps maximise earnings while recouping infrastructure costs, such as initial and operating expenses.

Enhancement of the revenue base by using a payment processing service

Upgrading your payment infrastructure is a central step in generating income from the software you've developed early. For this reason, we generally recommend a payment service provider to help establish a revenue base smoothly.

Stripe Billing lets small businesses without a dedicated team for creating payment flows quickly implement a variety of pricing options, such as subscription billing, usage-based billing, and one-time purchases.

How Stripe Billing can help

Stripe Billing lets you bill and manage customers however you want – from simple recurring billing to usage-based billing and sales-negotiated contracts. Start accepting recurring payments globally in minutes – no code required – or build a custom integration using the API.

Stripe Billing can help you:

• Offer flexible pricing: Respond to user demand faster with flexible pricing models, including usage-based, tiered, flat-fee plus overage and more. Support for coupons, free trials, prorations and add-ons is built-in.

• Expand globally: Increase conversion by offering customers' preferred payment methods. Stripe supports 125+ local payment methods and 130+ currencies.

• Increase revenue and reduce churn: Improve revenue capture and reduce involuntary churn with Smart Retries and recovery workflow automations. Stripe recovery tools helped users recover over US$8.2 billion in revenue in 2025.

• Boost efficiency: Use Stripe's modular tax, revenue reporting and data tools to consolidate multiple revenue systems into one. Easily integrate with third-party software.

Learn more about Stripe Billing or get started today.

FAQs about using AI for software development