The market for low-code and no-code technologies is substantial and poised for continuous expansion. The incorporation of AI-based support into these tools is expected to further drive business growth.
Research conducted by Forrester analyst John Bratincevic reveals that the global market for low-code and no-code solutions is valued at $13.2 billion, with an annual growth rate of approximately 21% since 2019. Bratincevic notes that the surge in this market is attributed to the integration of low-code in IT practices, as 87% of enterprise developers utilize tools with low-code or no-code functionalities. He predicts that by 2030, citizen developers could significantly augment the industry, showcasing the ongoing democratization of development beyond IT boundaries.
The infusion of AI technology could potentially generate up to $50 billion in the next four years, acting as a pivotal catalyst for the market’s acceleration. Bratincevic anticipates that AI will enhance programmer engagement, particularly through AI-infused development platforms like TuringBots, which may elevate the efficiency of traditional high-coding practices. However, he cautions that the impact of AI on low-code and no-code software development may fall somewhere in between, fostering growth through the integration of AI capabilities into platforms with minimal to no coding requirements.
Nevertheless, it’s worth noting that leveraging AI applications on low-code platforms may pose challenges for member or professional developers, necessitating a certain level of development expertise. Rodrigo Coutinho, co-founder and AI guide at OutSystems, emphasizes the importance of understanding the language utilized in generating general AI, indicating that proficiency in this domain is crucial for effective communication with AI systems.
The distinction between low-code, no-code, and AI-assisted development remains significant. While AI technologies like Gen AI have enhanced productivity for traditional engineers, Coutinho underscores the continued necessity for expertise in comprehending and modifying generated code. Similarly, David Isbitski, chief developer advocate at Amazon Web Services, advises that inexperienced developers may not be ready to directly engage with conceptual AI for application development without prior programming knowledge.
As AI becomes increasingly integrated into the development landscape, it can serve as a supportive tool for developers, aiding in evaluating thought processes and ensuring code accuracy. Isbitski emphasizes that AI assistants in low-code environments can enhance understanding and context, facilitating more efficient and informed coding practices.
Ultimately, the goal of AI-assisted application development is to empower individuals to learn and innovate, fostering a deep understanding of coding processes and solutions. Developers stand to gain new opportunities through AI-infused development, with the potential to streamline code review processes and enhance overall productivity within development teams.
