The number of organisations adopting low-code AI and no-code AI are growing. Low-code AI and no-code AI offer many benefits, from massive cost cutting on development and hiring experts such as AI expert, data scientists and software developers, ability to quickly build simple applications without or little coding knowledge to better users experience through simple and intuitive interface. While the rise of the two AI technologies are due to the same factor where industries need less complex AI solution compared to the traditional which require more skills and processes, the two approaches have their differences. What are the differences between low-code AI and no-code AI?
1. Coding knowledge: Little vs None
Low-code AI is a software design systems that allows building AI applications through the use little programming whereas no-code AI is a code-free technology that enables development of AI applications. As based on their definitions, low-code AI lets users build their AI applications with little programming or coding knowledge. No-code AI on the other hand, as the name suggest, allows users to build their AI application without coding knowledge at all. Simply put, building an AI applications using a low-code AI involves minimal coding while with no-code AI, no coding involved.
2. Skill level: Programmer & Non-programmer vs Non-programmer & Non-IT people
As low-code AI involves minimal programming, it is usable for both programmer and non-programmer. A low-code AI platform is built with intuitive GUI coding that is easy to understand and use. Of course, for non-programmer, getting started with a low-code may need a little bit of training. On the contrary, no-code AI platform applies visual development interface that makes it usable for non-programmer or non-IT people. Significantly the implementation of no-code AI allows non-programmer and non-IT people (anyone) to create applications through dragging and dropping software elements.
3. Customisation opportunity : Limited vs Templated
Low-code AI and no-code AI are both deficient in term of customisation opportunity. As low-code AI only allow involves small coding, only certain features can be made available into the applications thus limited personalisation can be done. Unfortunately, with no-code AI, users are restrained with the templates given in the platform. In other words, users are combining feature based on what had been there in the software design system instead of creating one based on their preference.
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Other post you may be interested in:
1. From No-code to No-code AI-What is No-code AI?
2. AI technology adoption – The Benefits of No-Code AI
3. How does adoption of No-code AI apply in different sectors?
