Do Low And No-Code Have A Role In The AI Landscape?

Do Low And No-Code Have A Role In The AI Landscape?

Ankita Avadhani
January 23, 2024
5 min read

Artificial Intelligence (AI) is used everywhere – in autonomous cars, early detection of certain diseases, countering banking frauds, etc. It helps enterprises deliver value to customers, make better business decisions, and improve productivity.  

Despite the clear benefits, only 15% of enterprises are using AI. Why is that?  

One reason is that it’s hard to create and implement. According to Deloitte’s survey, 40% of enterprises believe that AI technologies and experts are expensive.  

There seems to be an urgent need to democratize AI and make it accessible to everyone. That’s where low-code/no-code AI could play a role.  

Low-code/no-code AI promises to allow non-technical users or those with limited technical skills to build and deploy AI and Machine Learning (ML) applications. These low-code/no-code platforms are code-free or require minimal coding. The intuitive drag-and-drop interface allows users to quickly classify, analyze, and build applications.

Building AI applications is complicated and time-consuming. However, most low-code/no-code AI platforms come with API catalogs, pre-built project templates, and ready-to-use datasets. So, it’s easier for any user to build AI applications quickly. Many platforms claim that users can build apps within hours!  

Here are a few use cases and complexities to know before deciding on using low-code/no-code platforms for AI.

Use Cases And Complexities Of Low-Code/No-Code AI Platforms
1. Use cases
  • Streamlines process automation: Typically, process automation takes between 8 to 12 weeks to complete depending upon the complexity of the process. Too much back and forth is involved between the data scientists and the process managers and users. However, modern businesses require quick solutions. As low-code/no-code AI platforms democratize AI development, process managers can improve their processes and make them more efficient without depending too much on data scientists. They possess knowledge of how the process works. So, they can use the drag-and-drop feature that the low-code/no-code AI platform provides to automate the process and deploy it. These processes can be automated swiftly to accelerate time-to-value.  
  • Helps build MVPs: Constant innovation – that’s the mantra of every enterprise in today’s hyper-competitive landscape. If enterprises want to thrive, they must test their ideas. They must build a minimum viable product (MVP) with the most basic but essential features and release it to a group of early adopters to get feedback. The idea of an MVP is to build and release the product quickly and iterate intelligently after that. Enterprises can empower citizen users who know the business better to make the MVP to accelerate the process. With the help of low-code/no-code AI platforms, citizen users can build and deploy the MVP quickly. All they have to do is upload the relevant data and use the drag-and-drop tools to build the application.
  • Optimizes workflows: In today’s times, automating and optimizing workflows is important to enable users to complete their tasks without errors and improve their productivity. However, some workflows are complex and require someone who knows the workflow well to lead the automation efforts. According to a Tech Republic survey, 17% of the respondents said they use low-code/no-code platforms to automate workflows. The low-code/no-code AI platforms can help users automate manual workflows from end-to-end and connect them to the existing systems with minimal or no coding. These platforms automatically select an algorithm that could solve a specific problem. What’s more, with the introduction of new data sets and performance analysis, the workflows can be further optimized to improve the outcomes.  
  • Not useful in building bespoke or mission-critical applications: The low-code/no-code AI platforms don’t provide access to backend code. Users cannot modify or customize it as per their needs. While it is beneficial for citizen users as they don’t have to worry about writing multiple lines of code to build an AI application, they also restrict the freedom to customize the applications. Sometimes the application may have to be adjusted according to the platform’s capabilities. That’s why these platforms may not be suitable for building bespoke or highly complex, mission-critical applications or AI applications.  
  • Migration issues: Some low-code/no-code AI platforms have limited integration options, due to which the users may not be able to migrate their legacy applications into the new ecosystem or the new applications into the existing ones.  
  • Security concerns: Security and data privacy are major concerns for enterprises that want to adopt low-code/no-code AI platforms. The low-code/no-code AI applications are built by citizen users who don’t have a background in information security. They may not be aware of the security best practices or policies and frameworks to follow to safeguard the applications. This could expose the application to vulnerabilities and pose a risk of a security breach.  
  • Vendor lock-in: If we talk of trade-offs, vendor lock-in could possibly top the list. Although low-code/no-code AI platforms allow non-technical users to build applications, they are not flexible when allowing vendor switching. The user is locked in with a particular vendor. So, if the platform has limitations and the enterprise wants to switch to another vendor that offers better features, they cannot do it without incurring heavy expenses or losing time. Some vendors may not allow app migrations too. This could restrict the innovation and flexibility that enterprises desire to achieve by democratizing AI development.  

Given the need for constant innovation and the wide skills gap, low-code/no-code AI platforms are the perfect solution for enterprises that want to build AI applications. They eliminate entry barriers and empower users to harness their knowledge and experience to build AI solutions quickly. More importantly, it frees data scientists to work on high-value and mission-critical AI solutions.  

However, it’s important to choose the right platform and the right partner who can help meet the business needs and eliminate the complexities. We help enterprises to unlock their potential and grow to the next level.

To know more about our offerings and solutions, contact us.  

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