Generative AI and low-code accelerate innovation

Independently, generative artificial intelligence and low-code software are two very popular technologies. But experts say that combining the two harmonizes in a way that accelerates innovation beyond the status quo.

Low-code development allows you to build applications with minimal need for hard-coding, instead of using visual tools and other models for development. The intersection of low-code and AI is a natural one, but it’s important to consider nuances like data integrity and security to ensure meaningful integration.

According to Microsoft’s Low-Code Signals 2023 report, 87% of Chief Innovation Officers and IT professionals believe that “increased AI and automation built into low-code platforms will allow us to make better use of all their capabilities.” I think.

According to Dinesh Varadharajan, CPO of Kissflow, a low-code/no-code work platform, the convergence of AI and low-code will allow the system to manage the work instead of humans working for it.

Varadarajan further said that instead of the AI ​​revolution replacing low-code, “rather than one replacing the other, the two forces will bring many possibilities.”

Varadharajan says the development gap will close as AI and low-code technologies come together. Low-code software makes development more accessible across organizations (often so-called citizen developers), and generative AI makes organizations more efficient and harmonious.

According to Jim Rose, CEO of an automation platform for software delivery teams called CircleCI, these large language models, which serve as the foundation for generative AI platforms, will eventually be able to change the language of low-code. Become. Instead of building apps and websites through a visual design format, Rose says, “You’ll be able to query the model itself and say, ‘I need an easy-to-manage e-commerce shop.’ ‘ said. sell vintage shoes ”

Rhodes agrees that one reason is that it “must know how to talk” to generative AI to get what you’re looking for, and that the technology hasn’t gotten this far yet. . Kissflow’s Varadharajan says that within a year he will see AI take over task management and perhaps not too long to intersect with low-code in more meaningful ways.

As with anything related to AI, there are many nuances to consider for business leaders to successfully implement and iterate AI-powered low-code.

Don Schuerman, CTO of enterprise software company Pega, prioritizes what he calls “responsible and ethical AI frameworks.”

This includes the need for transparency. In other words, can you explain how and why AI makes certain decisions? Without that clarity, companies can end up with systems that cannot serve their end users in a fair and responsible manner. He says he has a nature.

This is fused with the need for bias testing, he added. “Our society is embedded with latent biases, which means that our data is also embedded with latent biases,” he said. “That means AI will pick up on these biases unless we explicitly test and defend against them.”

In addition to checking for errors and making changes, Schuurmann said, “always keeping humans up to date” also takes into account something machine learning algorithms haven’t yet mastered: customer empathy. advocating. By prioritizing customer empathy, organizations can maintain their systems and recommend products and services that are actually relevant to their end users.

For Varadharajan, the biggest challenge anticipated by the convergence of AI and low-code is change management. Enterprise users, in particular, may be the last tier to adopt the AI-powered low-code shift because they are accustomed to doing things a certain way, he said.

Maintaining a governance layer helps leaders keep up with advances in AI, no matter what risks companies are dealing with. “We are still wrestling with the possibilities of what generative AI can do,” Varadarajan said. “We humans evolve, too. We will figure out how to manage risk.”

While many generative AI platforms derive from open-source models, CircleCI’s Rose said there will be a different kind of successor platform in the future. “The next wave is closed-loop models trained on your own data,” he said.

Of course, proprietary data and closed-loop models still need to consider the need for transparency. But if organizations can keep their data safe in this small model style, the power of generative AI could rapidly migrate across industries.

Experts say generative AI and low-code software will drive innovation on the highway unless organizations compromise on the element of responsibility. In today’s world, the speed of innovation is essential to increase competitiveness. Look at Bard. This is a product from Adobe and Google that is set to compete with OpenAI’s ChatGPT in the generative AI space.

Shulman says that when it comes to AI and low-code, “we’re starting in a much deeper area than we used to.” AI-powered low-code accelerates the speed of innovation by shortening the path from idea to experimentation and finally to actual product, he said.