Particularly driven by the lack of full-time developers throughout the world, both professional and non-technical developers continue to have a significant need for low-code, no-code, and intelligent developer technologies (LCNCIDT). According to a recent International Data Corporation (IDC) forecast, global LCNCIDT sales will reach $21.0 billion in 2026, rising at a five-year CAGR of 17.8% from 2021 to 2026.
Businesses are implementing LCNCIDT technologies to increase developer productivity. This can be done in one of two ways: either by giving professional developers the tools they need to work more quickly by streamlining or eliminating steps in the development process, or by giving non-technical developers the resources they need to create or update digital solutions on their own without the assistance of professional developers.
“The market for LCNCIDT technologies is being driven by the global shortage of full-time developers,” said Michele Rosen, research manager, Low-Code, No-Code, and Intelligent Developer Technologies at IDC. “This situation is expected to continue throughout this decade, creating a strong market for technologies that increase developer productivity or expand the potential pool of developers.”
Using Cloud-Native Technology
“The market for LCNCIDT technologies is being driven by the global shortage of full-time developers,” said Michele Rosen, research manager, Low-Code, No-Code, and Intelligent Developer Technologies at IDC.
The use of cloud-native technology as enterprises shift toward a digital-first environment is one factor driving growth in LCNCIDT. The benefits of developing cloud-native software include higher agility, reduced hosting costs, a quicker time to market, and enhanced user experience.
However, this strategy also has dangers for cost and operational management, particularly if the company lacks the requisite internal knowledge. Vendors who offer LCNCIDT developer tools, such as cloud-native design tools, IDEs, and DevOps tools, that allow the transition to and administration of cloud-native software development have the chance to help enterprises with this challenging but essential change.
Cloud-based development would benefit many of the features offered by low-code and no-code tools, and many intelligent developer technologies depend on cloud-based services. As a result, cloud-based installations have contributed significantly to LCNCIDT’s revenue during the past few years, stated IDC. By 2026, IDC projects that this trend will have continued and cloud installations would account for more than 75% of market revenue.
AI and ML
Products that streamline or eliminate steps in the development process so that professional developers can work more rapidly are included in the competitive market for low-code, no-code, and intelligent developer technologies. By offering non-technical developers development interfaces that abstract away part or all of the knowledge needed to code in conventional development environments, it would increase the number of developers.To sum up, the market is made up of:
- Low-code developer technologies – that can make the design and creation of unique digital solutions faster and easier by offering graphically guided developer tools, drag-and-drop development interfaces, prebuilt code components and templates, and tools for modeling and integrating processes and data. Application development platforms, web development platforms, UI/UX components, and database-centric low-code application development platforms are examples of low-code developer technologies.
- No-code developer technologies - which offer model-driven, AI-driven, and/or visually guided technologies that allow developers without technical backgrounds to create software (apps, websites, etc.). Technologies for no-code developers shield developers from command-line code. Application development platforms, web development platforms, and UI/UX design tools are examples of no-code developer technologies.
- Intelligent developer technologies - which utilize artificial intelligence (AI) and machine learning (ML) to quicken software development or the creation of digital products driven by AI. Code autocompletion tools, AI development tools, conversational AI development tools and platforms, and test automation are examples of intelligent developer technologies.
