The low-code and no-code market is growing more and more. Additionally, adding AI-based assistance to these tools could lead to even greater market growth.
The low-code and no-code market represents $13.2 billion in turnover each year worldwide, with a growth rate of around 21% per year since 2019, according to a study by Forrester analyst John Bratincević.
According to him, this growth stems from “the institutionalization of low code in IT”, with 87% of enterprise developers working with low code and no code tools or platforms.
Making development productive
New developers from the trades will triple the size of this market by 2030, he continues: “The democratization of development among workers outside the information technology sector shows no signs of slowing.”
AI is the key factor that could help accelerate this market further – up to $50 billion in the next four years. AI will lead to greater involvement of new developers, says Bratincevic.
Conversely, he adds: “AI-infused development platforms (TuringBots) could make traditional coding so productive that professional developers would reject low code and return to high-level coding.
“You must learn the dialect”
AI’s impact on low-code and no-code development could fall somewhere in between, he says, with healthy growth fueled by the integration of AI and low-code platforms. code and no code.
It should be noted, however, that the ability to deliver AI applications with low-code platforms – assuming the developer is willing to do so – may prove problematic. High levels of development skills are still needed. “The language used to develop generic AI is not really easy,” Rodrigo Coutinho, co-founder and head of AI at OutSystems, pointed out during a recent podcast.
“You have to learn the dialect,” he insists. “Right now you have to take engineering courses because you have to learn in a way that the machine can understand what you’re saying. Even if the words are the same, you don’t really talk to it like you would. a person”.
There is a major distinction between AI-assisted development and no-code or no-code development
This language barrier risks hindering the long-announced democratization of software development, he continues: “It’s not as complicated as C# or JavaScript. But it’s a language that you have to learn to be able to develop.”
It’s also important to note that there is still a major distinction between AI-assisted development and code- or no-code development. “AI has brought a huge productivity boost to traditional developers, but they still need to know what they’re doing,” says Coutinho.
“To use generic AI tools for traditional code, you still need to be an expert. Even though a lot of the work is done by the machine, you still need to be able to read the work created, understand it, “Adapt it to your own needs and modify it. That’s exactly what the first version of the app does.”
“You don’t know what you don’t know”
Therefore, it is probably too early for inexperienced developers to work directly with generative AI to create applications, agrees David Isbitski, principal developer advocate at Amazon Web Services.
Unless you are familiar and experienced with programming, “you don’t know what you don’t know.” AI-driven development requires not only technical experience, but also a sense of what and how the code should be mapped to the business process.
“If you’ve coded for a while, you know how to do a process,” says Isbitski. “You can turn this process into code. But someone who has never written software before wouldn’t know what to ask.”
Technology could be used as an empathetic assistant
As AI enters the development process, the technology could be used as an empathetic assistant. The ideal AI assistant in a low-code environment “can analyze my thought process,” Isbitski says. “This is how I wrote this code, this is how it’s going to work and this is how it was enabled. It feels like magic. It’s about encouragement and making sure things are correct.”
Ultimately, an ideal AI assistant can better understand the context in which software is written and deployed, he continues: “As humans, we know all these things, what day it is, the climate, that the AI doesn’t know. These are important elements for the outcome. Bringing these elements back, as you have these conversations while you’re writing the code, is incredibly powerful.
The goal of AI-assisted software development is to “allow people to learn and improve,” says Isbitski. “Instead of giving people answers, we need to give them the opportunity to find them themselves. It’s an incredibly powerful educational tool. Perhaps because these generic AIs and LLMs are truly a reflection of us “themselves”.
“You are the team leader who will make sure everything goes well”
Ultimately, AI is expected to provide new opportunities for developers.
“In management teams, a lot of the work is looking at their subordinates’ code and making sure it’s correct, meets requirements, is of good quality, etc. That’s the “One of the impacts that generic AI will have on the developer’s life. The individual contributor is generic AI, and you are the team leader who will make sure everything goes well.”
Source: “ZDNet.com”