The low-code and no-code market is experiencing significant growth, and the addition of AI-based assistance to these tools is expected to further drive market expansion. According to Forrester analyst John Bratincevic, the global low-code and no-code market is currently valued at $13.2 billion, with an annual growth rate of approximately 21% since 2019. This growth is attributed to the increasing adoption of low-code and no-code tools by enterprise developers, with 87% of them utilizing these platforms. Bratincevic predicts that citizen developers will triple the size of this market by 2030, indicating that the democratization of development to non-IT workers is on the rise.
The integration of AI into low-code and no-code platforms is expected to play a crucial role in accelerating market growth, potentially reaching $50 billion within the next four years. Bratincevic suggests that AI will encourage more citizen developer involvement. However, he also notes that AI-infused development platforms, known as TuringBots, could make traditional high coding so productive that professional developers may reject low-code and switch back to high coding. Therefore, the impact of AI on the future of low-code and no-code development is expected to lie somewhere in between, with healthy growth driven by the integration of AI and these platforms.
It is important to highlight that while low-code platforms offer the capability to deliver AI applications, it can still be challenging for developers, whether they are professionals or citizen developers, to utilize these platforms effectively. Rodrigo Coutinho, co-founder and AI lead at OutSystems, emphasizes that developing AI applications requires specific skills and knowledge. The language used to develop AI, although similar to English, requires a different approach to ensure that machines can understand the instructions. Coutinho compares it to learning a dialect and suggests that engineering courses are necessary to communicate effectively with AI. This language barrier may hinder the democratization of software development, as it requires individuals to learn a new language in order to develop applications.
Furthermore, it is crucial to distinguish between AI-assisted development and low-code and no-code development. Coutinho explains that while AI has significantly boosted productivity for traditional developers, they still need to possess a deep understanding of coding principles. Gen AI tools, which utilize AI for traditional code development, still require expertise and the ability to interpret and modify the generated code. Inexperienced developers may not be ready to work directly with generative AI to build applications, as it requires both technical experience and an understanding of how code maps to business processes. Without prior programming knowledge, inexperienced developers may struggle to ask the right questions and effectively utilize AI-enabled development tools.
However, as AI becomes more integrated into the development process, it can serve as an empathetic assistant. David Isbitski, principal developer advocate at Amazon Web Services, suggests that an ideal AI assistant within a low-code environment would be able to analyze the thought process of developers, explain how code is written and its intended functionality, and ensure correctness. This kind of AI assistant can better understand the context in which software is being written and deployed, providing valuable insights and guidance throughout the development process. Isbitski believes that AI-assisted software development should empower individuals to learn and improve themselves, rather than simply providing answers. This approach can serve as a powerful teaching tool and enhance the capabilities of developers.
In conclusion, the integration of AI into low-code and no-code platforms is expected to drive significant growth in the market. However, the language barrier and the need for technical expertise may pose challenges for developers looking to utilize AI-enabled development tools effectively. Nonetheless, as AI becomes more integrated into the development process, it has the potential to serve as an empathetic assistant, providing valuable insights and guidance to developers. AI-assisted software development should ultimately lead to new opportunities for developers, allowing them to focus on higher-level tasks and ensuring the quality of code produced by their teams.