Will AI Replace Low-Code/No-Code?

As more organizations test and deploy Artificial Intelligence (AI) in their daily business work, the technology is slowly augmenting or even replacing daily work routines. This raises the question: Will AI replace low-code/no-code development?

Simply put, it won’t – at least for the foreseeable future.

Low-code/no-code development platforms have unique advantages in that they enable non-IT professionals to contribute to the application development process. While AI may have some role in aiding application development, it cannot replace the cognitive abilities such as creativity and problem-solving, and deep domain experience of the human citizen developers building these business solutions.

Why Low-Code/No-Code Is on the Rise?

The modern business world is facing growing challenges, such as skilled staff shortages, heavy workloads, prolonged turnaround times, and rising application development requests to help streamline this work. Companies had to go digital, but mobile app developers were hard to find and even harder to hire or keep on staff. At the same time, outsourcing mobile app development was very costly and ate a lot of time. To make digital transformation possible, companies began seeking technology solutions that speed up the process for their IT teams or even made it possible for business workers to create their own apps.

Companies now rely on low-code and no-code software to take business processes digital and serve employees and customers using mobile devices. The technology bridges while addressing the talent gap  – the shortage of skilled workers with the necessary technical expertise to develop and maintain digital solutions – which 75% of employers are now struggle concerned with.

Low-code/no-code development offers a variety of benefits, including the following.

• Accelerated Application Development: Low-code/no-code platforms can reduce the time to market for businesses by significantly decreasing the development time required for applications.

 

• Increased Agility: These platforms allow organizations to respond quickly to changing market conditions and customer needs by enabling rapid application development and deployment.

 

• Cost-Effectiveness: By reducing the need for specialized programming expertise, low-code/no-code development can lower the cost of software development and maintenance.

 

• Democratization of Application Development: Non-technical users can create and deploy applications, fostering innovation and collaboration across the organization.

Current State of Low-Code/No-Code Development

While low-code platforms and no-code drag-and-drop app builders have been around for some time, the urgent call for digital transformation amid the pandemic has made these tools even more popular. Now, there is an array of platforms and solutions engineered to meet the constantly evolving requirements of modern business apps. According to a survey conducted by Gartner, low-code and no-code development platforms will create over 65% of all applications by 2024.

Low-code and no-code development platforms empower users to create applications without needing to be expert mobile app developers or without needing to know how to code at all. Using visual interfaces and intuitive app-building controls, these solutions eliminate the need for extensive programming knowledge. Reduced complexity and less need for expert skills allow businesses to rapidly develop and deploy business applications while saving time, money, and resources. This innovative software powers a dramatic productivity increase in app development. McKinsey states that using a low-code development platform can result in up to a 90% reduction in development time, ultimately leading to a significant reduction in development costs.

Many industries have successfully leveraged low-code/no-code development to streamline their operations and improve efficiency. For example, the financial sector has used these platforms to create customer-facing applications and automate internal processes, such as accounting and compliance reporting. Similarly, healthcare organizations have employed low-code/no-code solutions to develop patient portals, speed up patient intake forms, create telemedicine applications, and improve the accuracy of medical records management systems.

What Is AI's Potential Impact?

The potential of AI-driven code generation and advancements in natural language processing could challenge the relevance of low-code/no-code software. AI algorithms possess the capacity to create code more effectively and precisely than humans, optimizing the development process and eliminating human error. Moreover, with progress in natural language processing, users might have the ability to build applications using AI by merely outlining their requirements in plain language, reducing the need for visual interfaces. These collective capabilities could lead some to question the long-term viability of human-driven low-code/no-code app development in the face of increasingly sophisticated AI technologies.

Although AI can automate specific aspects of application development, it cannot replace the essential human input required for crafting intuitive and user-friendly designs. A human-centered design is an essential element in ensuring that applications address the distinct needs and preferences of end-users. Additionally, AI algorithms often lack the specific domain expertise necessary for creating industry-specific applications. In this context, the human touch and the flexibility of low-code/no-code platforms remain indispensable in the application development process, even as AI technology continues to advance. Yet when business pair low-code/no-code development with the power of AI, all new possibilities for fast, intuitive app development emerge.

Pairing AI and Low-Code/No-Code

While it appears unlikely that AI will completely replace low-code and no-code development in the near term, it is likely that the two technologies will coexist to improve modern business app development. Several scenarios exist for AI and low-code/no-code technologies to work together to provide value.

AI-Assisted Development

AI can be integrated into low-code/no-code platforms to assist users in generating code, optimizing workflows, and providing recommendations based on best practices. For instance, Microsoft's Power Apps platform now uses AI Copilot to provide users with suggestions for which components to use in their applications.

Requirements Gathering and Documentation

While essential to planning documentation and then training users on how to utilize and complete documents, parts of requirements gathering and documentation can be tedious. Some aspects of both can be automated with AI. For example, a company may use a chatbot to gather requirements from users for a new software application. The chatbot can ask targeted questions to elicit the necessary information, such as user preferences, features needed, and desired outcomes. The chatbot can also document the user's responses automatically, eliminating the need for manual documentation.

Intelligent Automation

AI can be used to enhance low-code/no-code platforms with intelligent automation capabilities, such as robotic process automation (RPA), making it easier for businesses to automate workflows. For example, AI-powered chatbots integrated into low-code development platforms can automate the testing and debugging of code, reducing manual effort and improving efficiency. They can identify and troubleshoot errors by analyzing the code and suggesting solutions, reducing the time and effort required by developers.

Custom AI Component Integration

Low-code/no-code platforms can allow developers to integrate custom AI components, such as machine learning models or natural language processing algorithms, into their applications. This would enable businesses to leverage AI capabilities tailored to their specific needs without requiring extensive coding knowledge. Google's AutoML and Microsoft's Custom Vision are examples of AI services that can be integrated into low-code/no-code platforms for custom AI model development.

Conclusion

AI has the potential to impact low-code/no-code development, but it is unlikely to completely replace these platforms or the workers who develop apps with them entirely. Instead, AI and low-code/no-code solutions can coexist and complement each other, offering businesses more powerful and efficient ways to develop applications. By integrating AI capabilities into low-code/no-code platforms, software vendors and organizations can reap the benefits of both technologies and continue their digital transformation journey.

Organizations aiming to digitally evolve their operations should not perceive AI as a risk to low-code/no-code development but instead as a beneficial enhancement to their set of tools. By adopting the collaborative strengths between AI and low-code/no-code approaches, businesses can make their application development processes more efficient, conserve time and resources, and foster innovation across the company.