It has been over two decades since I developed my second low-code program. Over the years, I have witnessed the evolution of system functions, making it easier for both software developers and programmers to create and enhance programs. The emergence of low-code and no-code approaches has accelerated app development, empowering business users to craft workflows from spreadsheets and assisting IT departments in application development. These platforms facilitate the swift creation of integrations, dashboards, IoT data streams, and various other capabilities beyond traditional applications.
Technological advancements significantly influence application creation and development. For example, the rise of smartphones and app stores necessitated a shift towards mobile-first development strategies, while cloud infrastructure enabled non-technical businesses to enhance applications and establish analytics capabilities. Currently, we are witnessing a similar trend with generative AI. The question arises: How does genAI impact the deployment and utilization of low-code platforms?
The Impact of genAI on Application Development
Generative AI is poised to revolutionize software development, potentially transforming the software development lifecycle into a manufacturing process where application components are assembled upon request. Code generators, such as GitHub Copilot, have already made a substantial impact, with over 87% of developers using it to enhance efficiency, focus on more engaging tasks, and expedite task completion.
Low-code and no-code platforms are now integrating genAI to enhance development processes, expand the developer pool, and cultivate skills required for customizing user experiences. The integration of genAI into these platforms is reshaping the landscape of application development.
According to experts like Jon Kennedy from Quickbase and David Brooks from Copado, genAI is reshaping the development landscape, potentially automating coding processes and transforming UX design. While some speculate about the replacement of low-code programs by script generators, others like Michael Beckley from Appian believe that both AI copilots and low-code platforms are essential for managing and interacting with the evolving software landscape.
Evolution of Designer Skillsets in the genAI Era
With genAI capable of generating scripts, test cases, and other software components, the skillsets required for application development are undergoing a transformation. Professionals like Dinesh Varadharajan from Kissflow foresee a shift towards cultural awareness and innovative constructs, enabling business users to create applications with minimal programming knowledge.
The Future of Software Quality and User Experience
As more individuals with diverse skill sets leverage AI assistants to develop software, questions arise regarding the impact on software quality and end-user experiences. While genAI accelerates application development, concerns about technical debt, security vulnerabilities, and software quality persist. Experts emphasize the importance of maintaining guardrails, testing, and governance within low-code platforms to mitigate these risks.
Leveraging genAI for Business Growth
The advent of generative AI in application development signifies a paradigm shift in the software development lifecycle. Businesses stand to benefit from the speed and efficiency offered by genAI-powered development processes. However, the integration of genAI into low-code and no-code platforms is likely to enhance their value and significance in creating, testing, and expanding software applications.
In conclusion, the synergy between genAI and low-code platforms presents a promising future for software development, offering unprecedented speed, efficiency, and innovation in application creation and deployment.
