Widely recognized as a game-changer, generative AI models are positioned to significantly contribute to the evolution of low-code and no-code development tools. The integration of generative AI with these platforms has the potential to break down learning barriers and unveil a whole new category of intelligent developer technology.
Low-code and no-code platforms have already made a significant impact on businesses, enabling users to create software applications with little or no coding knowledge. This seamless app creation process is expected to flourish with the introduction of generative AI to these systems, empowering a wider range of business users to utilize low-code and no-code platforms.
Generative AI is poised to revolutionize the use of low-code and no-code systems among users who may not have expertise in software programming. Analysts predict that integrating generative AI technology into development tools will make it far easier for such platforms to deliver user-friendly functionality to even non-programmers.
Business application development can be expedited significantly with generative AI's natural language processing capabilities, offering substantial advantages to both enterprises and developers. Having access to these benefits could potentially double the low-code market within the next 18 months to two years, resulting in a rapid surge in user adoption and enabling vendors to increase their revenue.
By empowering users through simple text inputs during the app development process, generative AI and no-code app builders can eliminate barriers to entry and open up opportunities for business users to take part in application development. This will enable users to rapidly create specialized low-code applications, providing a simple means to generate custom code snippets and streamline development times.
Microsoft's Power Apps, for example, already incorporates ChatGPT-based functionalities after the addition of Copilot, which includes a chat interface that facilitates simple application creation. The resulting application can even feature a ChatGPT instance for end users, thus further boosting efficiency and versatility in the app development process. Other platforms, like AppMaster, excel at the integration of UI creation for web and mobile applications, making it possible for citizen developers to create fully functional and interactive applications without coding expertise.
However, the integration of generative AI into low-code and no-code systems also brings certain challenges. Users will need time to adapt to natural language prompts, and there may be legal and security concerns tied to AI-generated content. In addition, data security measures must be implemented to protect user information in AI models, and developers may require additional training to use generative AI technologies to their full potential.
Nevertheless, the innovative capabilities of generative AI technology have the potential to create an entirely new class of development platforms, with a focus on natural language processing. Visual developer interfaces, like drag-and-drop components, could become obsolete as generative AI matures and gains popularity.
While integration of generative AI into low-code and no-code environments promises to enhance current platforms, it's also likely to lead to the emergence of new generative AI-based solutions. Vendors who can deliver value-added tools in conjunction with raw generative AI outputs will be well-positioned to attract users, thanks to the immense interest surrounding the technology.
Given these predictions, it's no surprise that giants like Microsoft, Google, and Amazon are expected to benefit greatly from the generative AI revolution. In particular, Microsoft appears to have an early advantage, as they have already made investments in generative AI technologies and are currently leading the way in enterprise low-code platform adoption.
Analysts foresee a growing demand for generative AI within low-code platforms, leading to potential mergers and acquisitions in the intelligent developer technology market. As a result, larger vendors aiming to manage the application development lifecycle may see significant growth opportunities in the near future.
