As AI matures the opportunity grows for the modern enterprise—which sounds exciting.
But before a business can take advantage of AI in software development, it has to figure out how to build with unfamiliar technology and maintain rapidly changing technology. Infrastructure and expertise challenges can suppress AI opportunities for enterprises developing solutions with high code.
Low-code software development lowers the barrier to sophisticated AI technology. Connectors and pre-built components improve access to AI innovation.
Low-code and AI share common goals and mutual benefits. That’s likely why they work so well together. A recent survey showed that 85% of low-code users are seeing AI and low-code help speed up innovation.
Low-code and AI’s shared history
AI and low-code tools have a history. AI-assisted development, for instance, has been available on Mendix since 2018. That pre-dates the recent generative AI revolution.
More history means:
- more chances to grow together
- more iterations and features
- user experience upgrades
- increased ability to experiment.
Experimentation time is significant with rapidly developing technology such as AI.
A successful low-code development platform keeps up with fast-moving technologies. This foundational need drives low-code innovation. It also ensures AI and GenAI integrations work with legacy and custom enterprise setups.
Low-code technology should also make processes easier to complete. That can come from:
- Connecting to third-party technology shortcuts
- Creating more collaboration touchpoints that speed up decision-making
Visual development also makes it easier to move quickly and integrate new technology than traditional coding. Easier access to cutting-edge solutions and improved communication help developers capture a broader spectrum of AI opportunities.
Match strength with strength
With application development, almost no advance or innovation is off the table. As AI matures, new features and solutions become available. Enterprises and vendors look for ways to leverage these advances within their technology.
The takeaway? The faster new technology arrives, the more critical rapid access and integration become.
Low-code is built on the ideas of improved speed and access. So, a partnership with AI makes a ton of sense in many ways.
AI in low-code software development
Application and software development are natural use cases for AI. Similarly, a low-code platform is the natural vehicle for integrating AI into the developer’s palette of tools.
Three low-code AI software dev tools include:
AI-Assisted Development (AIAD)
AIAD streamlines and enhances software development through automation, real-time code quality recommendations, and more. Low-code chatbot assistants, which continue to evolve, are an example of AIAD.
Machine Learning
Machine learning starts with structured data inputs. Those are trained with models to discover patterns and generate outputs. Machine learning allows enterprises to make better predictions about future performances and automate decision-making processes.
AI-Augmented Apps (AIAA)
AIAA involves making your applications smarter. This includes connectors to different services, embedding your ML models, and more.
Low-code and AI: Better together
GenAI can answer development queries, complete tasks, and reduce the time it takes to process requests. Machine learning finds patterns in datasets, making future predictions based on previously learned interactions. The possibilities with AI are huge.
Traditional development, however, is susceptible to technical debt and developmental hurdles that slow down these innovations.
Low-code, on the other hand, kicks innovation into hyperspeed.
Low-code and AI have aligned goals in application and software development. The two have a longstanding relationship that can help enterprises gain an advantage by integrating LLMs and other AI/ML innovations.