Over the past few years, automated coding approaches such as AI, low-code, and no-code have profoundly shaken the software development industry. They did this by widening programming and AI tools accessibility while making software engineers’ life easier.
As a result, the low-code and no-code market has been growing exponentially. And it doesn’t look like it’s going to stop anytime soon. According to Gartner’s forecasts, the market, worth close to $27b in 2022, should see an increase of 20% this year alone.
AI, Low-Code, and No-Code Explained
Developers often use AI as a short form of AI code. AI code is a broad term that encapsulates any type of code written by artificial intelligence programs. AI is able to generate code through the use of predictive coding, natural language processing (NLP), and machine learning.
This process is often referred to as AI-powered code completion or AI-based code generation. But writing code isn’t all AI can do. It can also assist software engineers with various tasks. Some of them are automating security, improving UX, and ensuring code quality in real-time.
Examples of AI development platforms: Microsoft Azure, Amazon SageMaker, Google Cloud AI Platform.
Low-code is a method of software development based on visual tools and model-driven processes. It allows for faster software delivery through a minimal amount of programming. It’s built on rich scripts, applications, and UI components that remove the need of having to integrate custom code into the software development process. With a very basic understanding of programming, users can build a wide range of applications, software, and websites.
Examples of low-code development platforms: Salesforce, Airtable, Microsoft PowerApps.
No-code is built on the same logic as low-code—making apps and software development more accessible. But it goes the extra mile by making programming non-compulsory. With no-code, there’s no need to be a software developer. Thanks to NCDPs (No-Code Development Platforms), you can develop an app or a service without having to type a single line of code.
Examples of no-code development platforms: Webflow, Mailchimp, Zapier.
AI, Low-Code, and No-Code: How Can They Coexist?
Thanks to the many features that come with AI (such as advanced auto-completion and coding assistants), some people believe that low-code and no-code could become obsolete in the years to come. However, many advocate that the two can cohabit and better each other.
AI and Low-Code
Many experts think that AI has a major role to play in low-code programming. AI can, for instance, support software engineers in training machine learning and deep learning models.
In turn, low-code apps can help tune, assess, and optimize AI models. Low-code can significantly lower the entry barrier to AI by incorporating seamlessly AI-driven functionalities and algorithms into applications. For example, businesses can now implement features relying on simple data sets. For example, facial recognition or handwritten text identification, without needing to code these functions into their own solutions.
Low-code is also a faster alternative to machine learning when it comes to automating certain processes. This reffers to processes like cleaning and structuring data. All-in-all, low-code gives companies an effective foundation to use. It can be built upon to develop the most efficient custom models to keep track of data.
AI and No-Code
Low-code helps make AI accessible to a broader audience. No-code is changing how we use data, opening up a lot of business opportunities.
When it comes to AI analytics, no-code platforms have first been introduced to replace complex database tools like SQL as a way to help companies make sense of the collected data.
Nowadays, AI is also used for predictive analytics (finding patterns and predicting results from data). However, this process used to only be available to technically minded people who had a solid knowledge of programming and data analysis.
Thanks to no-code solutions, predictive analysis has been made accessible to a wider audience. Rather than being limited to a handful of big corporations, no-code AI can be used by small businesses too. They an use it as a way to reduce costs, improve operations effectiveness and maximize profits. Data analysts can, for instance, benefit from machine learning without having to write code. But also, without having to train a full machine learning model (that can take up to 90 days!).
The Impact of AI, Low-Code, and No-Code on Software Development
With automation playing an ever-increasing role in software development, one thing is certain: the future of programming looks set to be codeless.
AI-based solutions are on their way to replace many current tools and processes. However, low-code and no-code still have a central part to play as a bridge between non-technical users and AI-driven functionalities.
By giving businesses of all sizes the opportunity to benefit from the latest AI technology, these solutions look to have a bright future in front of them. They’ll more than likely keep disrupting the software development industry in the years to come.
The latest market predictions seem to encourage this theory. According to those, by 2026, 80% of users of low-code and no-code solutions will be non-formal developers. But no matter what the future holds, software engineers’ expertise will always be needed to tailor solutions to business needs and oversee processes.