No-Code and Low-Code
Both accelerate development, but they differ in target users, flexibility, and how far they can be customized.
No-Code
No-Code
An approach to building business apps entirely through screen configuration, data definitions, and workflow design, with no code required. It is designed for business users to operate on their own, making it well suited to in-house development and frontline improvements.
- No programming knowledge required
- Led by business users
- Scope limited to the product's capabilities
Low-Code
Low-Code
An approach that starts with fast screen-based configuration, then extends logic and integrations with small amounts of code where needed. Engineers and business users collaborate to build more flexible systems.
- Extend with minimal code
- Collaboration between engineers and business users
- Balances flexibility and speed
Context and Trends
Why No-Code / Low-Code Is in Demand
The acceleration of DX, a shortage of IT and AI talent, and design that assumes AI integration. As these three trends converge, no-code and low-code are shifting from an option to a baseline expectation.
Rising Interest in DX and a Shrinking IT Workforce
Since the pandemic, delays in digitizing operations and leveraging data have directly affected competitiveness. DX is no longer a single IT project but a company-wide management theme. As long as legacy core systems remain in place, digitization stalls. Many companies still face this structural challenge that Japan's METI has called the "2025 Digital Cliff."
Meanwhile, the IT workforce that supports DX is projected to shrink. A supply-and-demand study by the Information-technology Promotion Agency (IPA) commissioned by METI projects a shortage of up to roughly 790,000 IT professionals by 2030. As the working-age population declines, demand for AI, cloud, and data talent will continue to grow.
To advance DX with fewer builders available, we need to stop building from scratch. Combining off-the-shelf components through no-code and low-code and adding custom development only where needed, this "minimize what you build" approach is becoming the practical answer.
The Gap Between In-House Ambitions and Resource Constraints
Bringing business and technology teams closer through in-house development helps advance DX. Yet few companies can staff enough developers internally, and relying entirely on outsourcing slows down requirements changes and improvements.
No-code and low-code have become a way to let business users take the lead in assembling business apps, making the most of limited IT resources. They still cannot reach requirements beyond their standard scope, so the mechanisms that fill this gap (technical support like ours) are becoming increasingly important.
AI Talent Is Even More Scarce
As generative AI and AI agents rapidly move into practical use, AI-related talent such as AI engineers, MLOps specialists, and prompt designers is especially scarce within IT overall. Japan's national AI strategy also positions AI talent development as a national priority.
Even companies that cannot staff an in-house AI implementation team can still make meaningful progress with AI, as long as they have a foundation that safely connects off-the-shelf AI agents and MCP servers to their business data.
Designing Systems That Assume AI Integration
Designs that safely deliver business data to AI agents (API-first and MCP-ready) are becoming a de facto standard for future systems. When data cannot be accessed by AI, AI adoption itself stalls.
A foundation that lets you build in days with no-code and low-code while freely connecting to external systems and AI agents through an API-first design accelerates DX and AI adoption together.