Low-Code & Development
The Solution to the Chronic Shortage of Developers
Every company is a software company these days, whether they like it or not. Internal processes must be digitized, customer portals must be built, and systems must communicate with each other. However, there is one major problem: a severe shortage of talented software developers. For years, the IT industry has tried to bridge this gap with ‘Low-Code’ and ‘No-Code’ platforms (such as Mendix, OutSystems, Microsoft Power Apps, and Betty Blocks). These platforms enable visually oriented people to build applications using drag-and-drop components, without having to write traditional code (Citizen Development).
Although this yielded significant productivity gains, Citizen Developers often still ran into complex logic or database structures. The integration of generative AI into these platforms changes this radically and puts citizen development on steroids.
The AI Copilot as Personal Lead Developer
The latest generation of low-code platforms has integrated AI assistants (Copilots) deep into the development environment. Instead of manually clicking together visual flowcharts, a user can now describe what the application should do in natural language. For example: “Create an expense app. Employees must be able to upload a receipt, after which the app reads the amount. Receipts under €50 are automatically approved; amounts above that go to the manager for approval.”
The AI assistant understands this instruction and immediately generates the necessary database models, the user interface (including an upload button), and the underlying business logic workflow. The user then only needs to adjust the branding colors and visually fine-tune the app. This lowers the technical barrier even further, enabling business analysts, marketers, and HR staff to independently build the tools they need.
Faster Integration and Bug Fixing
One of the most complex parts of app development is integrating with external systems (APIs). If your new app needs to retrieve data from SAP or Salesforce, this typically requires in-depth technical knowledge of authentication and JSON structures. AI copilots within integration platforms take this heavy lifting off your hands. You specify which system you want to communicate with and which data you are looking for, and the AI automatically configures the correct API calls and the mapping of the data fields.
Moreover, AI helps with bug detection (debugging). If an app crashes, a low-code platform used to generate a cryptic error message. Now, the AI explains what went wrong in plain language (for example: “You are trying to save a text field in a column that only accepts numbers”) and immediately suggests the solution, including a button to fix the error with one click.
Governance: Preventing Shadow IT Chaos
However, the explosive acceleration of application development driven by AI also brings with it a major risk: the uncontrollable proliferation of applications (shadow IT). If every employee can put an app together in ten minutes, the central IT department loses control over data security and architecture. What happens if the employee who built the app leaves the company?
Establishing strong governance is therefore crucial. IT administrators must set up so-called guardrails within the low-code platforms. They determine which data sources users are allowed to access (for example: access to the public product register, but no access to payroll data in HR), and require apps to undergo a formal security scan and IT approval before being widely shared within the organization. Only with tight control does the combination of low-code and AI form a scalable engine for innovation.
Read more about the secure adoption of intelligent workplace solutions and low-code on platforms such as Emerce.
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