DEVOPSdigest

Businesses have become increasingly reliant on applications — think CRM solutions, internal dashboards and workplace management platforms — for nearly every aspect of their operations. And as businesses grow, so does the need for more customized and sophisticated apps to keep everything running as expected.

To keep up, businesses need to move faster and deliver more tools as the needs of their teams and customers evolve. Traditionally, this has meant either investing more time, money and employees into the app-building process or turning to low-code/no-code platforms for an option that requires fewer technical resources.

Now, AI has emerged as the newest "must-have" technology for companies, resulting in rising speculation into whether it will eventually replace low-code/no-code tools altogether. However, according to the 2025 App Development Trends Report from App Builder, that is not the case, with the report revealing that 76% of tech leaders are looking to AI to make their existing low-code/no-code tools more efficient instead of replacing them.

Low-code/no-code platforms have been shown to speed up development, boost productivity and make app creation more accessible to more than just engineering teams. And while there's still room for improvement, especially as business needs grow more complex, AI doesn't necessarily need to compete with these tools. Instead, it can make them even smarter, faster and better aligned with teams' day to day functions.

Here are 3 ways companies can integrate AI with their low-code/no-code tools to improve business operations.

1. Speeding up and simplifying the app-building process

App development has traditionally been a long and resource-heavy process. From start to finish, developers can spend hundreds of hours working to build, test and deploy an app — and this can take even longer for those that require complex customizations or integrations with legacy systems. Investing this kind of time into a single app limits how quickly teams can respond to shifting market demands, resolve issues and capitalize on new opportunities.

Low-code/no-code platforms have helped developers solve this challenge, reducing the time they spend at every stage of the app-building process by making each step faster and more efficient. With drag-and-drop components, reusable logic and pre-built integrations, these tools significantly cut the work needed to bring new apps to market. In fact, 98% of tech leaders report saving development time using low-code/no-code platforms, with nearly 4 out of 5 companies (78%) saving up to 50%.

When AI is integrated alongside low-code/no-code tools, it can speed up and simplify every phase of the build process even more. During the design phase, for instance, AI can auto-generate UI layouts based on user requirements or business goals. In development, instead of manually configuring logic or building repetitive components, developers can describe what they need and AI can generate the corresponding code or flow within the low-code/no-code platform. And when it's time for testing, AI can auto-generate use cases, simulate edge scenarios and flag bugs or inconsistencies before deployment, which can reduce the time spent on quality assurance cycles.

2. Eliminating repetitive work so developers can focus on more strategic work

App development often requires writing extensive code — even for something seemingly simple like data input fields or basic user permissions. While these tasks are necessary, they can often be repetitive and are rarely where developers should be spending their time to add the most value.

Low-code/no-code platforms help make that shift by handling manual routine tasks, such as configuring workflows, building simple UI components and managing integrations. This frees up developers' time to focus on higher-value work like designing new product features, improving the user experiences and better aligning apps with broader business objectives. Companies have noticed a difference too, as business leaders say improving developer productivity (37%) and allowing developers to focus on more strategic work (25%) are the top reasons they use low-code/no-code tools.

AI can eliminate repetition even further to heighten developer productivity. For example, AI can take past prompts and usage patterns to automatically generate workflows and pre-fill logic accordingly — saving hours of manual setup and accelerating the entire development cycle.

For non-developers such as marketers, product managers or HR employees, AI and low-code/no-code tools allow them to have a more active role in the app-development process. Low-code/no-code tools let its users build apps with little or no coding experience, while AI can help translate their needs into functional prototypes or even finished components.

3. Enabling non-developers to create custom apps

Custom app development used to be out of reach for many businesses as only those with significant resources — time, money and qualified team members — could afford to build tailored apps from scratch. Everyone else had to rely on off-the-shelf software that offered limited customizations that rarely addressed their unique challenges and goals.

But generic applications don't cut it anymore, especially as companies work to evolve their apps to meet the unique needs of their business and customers. In fact, nearly one-third of tech leaders (29%) say their top reason for using low-code and no-code tools is to increase flexibility to create custom apps that meet specific company needs.

Now, with low-code/no-code tools, businesses of all sizes can build apps that are tailored to them without a large development team. For example, a small marketing agency might use low-code/no-code tools to build a branded campaign tracker that integrates with their clients' CRMs and automates reporting. In the same vein, an in-house marketing team could build a custom lead app that pulls from data sources to prioritize accounts.

As customer expectations evolve, so must the tools companies use to serve them. With AI, instead of relying on manual trial-and-error to design and test custom logic, teams can use the technology to generate app flows based on their goals or descriptions of a business process. AI can also simulate user interactions, recommend features based on the problem being solved and even flag performance issues before launch — essentially acting like a manager and developer rolled into one.

This shortens the feedback loop for customization. Teams can build something, test it and refine it in hours rather than weeks. And because AI can learn from previous builds and user behavior, they get better at recommending relevant features over time.

Together, AI and low-code/no-code platforms are improving the application development process for businesses — not by competing, but by supporting each other. By integrating AI into low-code/no-code platforms, companies can turn app development from a time-consuming and resource-heavy bottleneck into an opportunity to better adapt, innovate and better meet the evolving needs of their teams and customers.