Generative AI and “low code” can empower businesses to develop intuitive applications rapidly. The creativity of AI and the ease of use of these platforms enable non-technical users to build sophisticated solutions.
Generative AI in Low Code Development
In “low code” software development, developers use their expertise and drag-and-drop platforms to create custom solutions. Platforms like Mendix, OutSystems, etc., have disrupted the IT industry and will continue to do so.
“No code” software development takes it even further, enabling application development without coding. These tools allow developers to be more efficient, creative, and productive.
With generative AI solutions, businesses can push the boundaries and develop intuitive applications. These solutions can generate complex outputs by analyzing datasets and patterns through Machine Learning and Natural Language Processing. Moreover, they can craft complex code empowering businesses to optimize operations.
Advantages of Generative AI Solutions in Low Code Development
Rapid Code Generation
As per this research by OutSystems, generative AI solutions will boost productivity by 30%. Let’s understand this with an example. Suppose, the requirement is to build inventory management software. Using these solutions and low-code platforms, developers can generate a prototype. If something is wrong, they can edit the prompt and ask Gen AI for the correct code snippet.
If this is done without AI solutions, it would take a significant amount of time, resulting in delayed deployment. However, with AI, developers can iterate the process multiple times and still deliver the project within the deadline.
Intelligent Code Augmentation
Generative AI can act as a code augmentation tool in “low-code” and “no-code” platforms. It can identify potential issues and provide recommendations for rectification. This guidance can help citizen developers develop intuitive applications as per business requirements.
Simplifying Complex Codes
The “low code” AI platforms have built-in algorithms to optimize the code for faster compilation. The simplicity will help developers bring innovative features to the application. Now, even a non-technical person can utilize the features to configure and deploy intuitive features without technical know-how.
Predictive Testing and Maintenance
“Low code” AI platforms can be used to run automated test classes to check vulnerabilities, performance issues, and robustness. Moreover, they can be used post-deployment to identify issues and provide suggestions.
Scalability
Low code application development platforms empower companies to adapt and scale their processes as per the requirement. This agility will help developers stay ahead of their competitors.
Enhanced Productivity
Automation is one of the best uses of AI in business, especially in software development. With Generative AI, developers can automate the mundane code generation process and deliver superior products. This way, they can focus on areas that need their attention, thus improving the project lifecycle.
Drawbacks
Relatively New Technology
Although we have several applications of AI in business, “low code-Gen AI” technology is relatively new. The AI models need extensive training to understand different personas and business logic.
Concerns Regarding Privacy and Security
AI LLMs use a large of data to automate the code generation process. How these data sets are used when they contain sensitive data is still a matter of concern. As rightly stated by the marketing head of Zoho Creator, questions like this need to be raised. If businesses want to practice ethical AI implementation, they need to guardrail this technology as soon as possible.
Data Quality (Bias & Hallucination)
The low code-no code AI platforms are still not free from bias and hallucinations. Due to this, the machine will produce outputs that diverge from the intended output. Also, hallucination in LLM models is pretty common. In case of hallucination, the model might produce code full of errors and might not be able to rectify it. In these cases, a trained eye is needed to identify these issues and help LLMs learn from the mistake.
User Training and Adoption
Implementing no code/ low code AI can be challenging, as businesses might not be ready for a disruption. Although these platforms can democratize the software development process, an extensive training program is needed. It will be possible if there is a significant shift in the corporate mindset.
Compliance and Governance
Compliance and governance should be checked for any application of AI in business. Without them, an organization is more likely to land on legal issues.
Applications of Generative AI Low Code Solutions
Chatbots
Companies can automate their customer care service by creating a chatbot using AI-powered “low code” platforms. Gen AI can not only be used to provide the code but also automate the email replies to frequently asked questions. Developers can also use a human verification process to ensure that the replies are matching the query.
Workflow Generation
These AI “low code” systems can be used to create automated workflows as per use cases. Low-code development can help visualize the processes, while Gen AI deals with generating and automating them.
UX Autocorrection
“Low code/ no code” platforms are quite popular for UX development. Gen AI can take it further, by suggesting corrections to improve the application’s interface. These suggestions can enhance a customer’s user experience.
Top Generative AI low code platforms
Early Movers
Google AutoML
Google brings Machine Learning and low code development together to automate the code generation process. Users need to have a solid understanding of ML to configure it, so it’s a bit on the technical side.
OutSystems
One of the prominent names in this field, Outsystems, has changed the rapid application development process. It is connected to GPT 3.5 and can recognize over 20 million patterns. It is versatile and contains multiple AI tools to help with “low code” development.
Salesforce Einstein
Salesforce Einstein’s AI low code platform provides suggestions on how to improve an app’s performance and behavior. It is a pretty neat platform for those who do not have intricate coding knowledge.
Aside from these three early movers, here are some more platforms to choose from:
Apple CreateML
With Apple CreateMl, you can create applications with quite advanced features, such as image recognition and text processing. As the name suggests, it deploys machine learning algorithms in the background. Like its Google counterpart, ML enthusiasts may get a higher advantage while using the platform.
DataRobot
DataRobot is a perfect “low code” platform to create applications for the public sector, retail, manufacturing, and healthcare. It supports different use cases and can be utilized to deploy features that work best for the organization.
Conclusion
Business can revolutionize their software development processes by integrating generative AI and “low code” platforms. These technologies will boost the project delivery process, leading to faster turn-around and accelerated time-to-market. They can enable developers to refactor codes by providing intelligent suggestions and generating codes. However, companies should understand that this technology is still new, and rules and regulations must be in place.
Chirpn, being an AI-first technology services and solutions company understands the rapid application development cycle. AutoCAR is an AI framework that revolutionizes software development and improves efficiency and time-to-market. Chirpn’s technical expertise will enable businesses to boost operations and enhance customer experience.
