Every enterprise IT department is dealing with some version of the same problem: business teams need new tools and applications faster than IT can realistically build them. That gap has existed for years, but the rise of natural language AI assistants embedded directly into development platforms is starting to change what “fast” actually means for enterprise app development.
Rather than treating AI as a separate layer bolted onto existing tools, a growing number of platforms are building AI assistance directly into the development process itself, allowing both professional developers and non-technical business users to describe what they need in plain language and get a working application in return. Jitterbit’s approach to this shift centers on its App Builder platform, which pairs a traditional low-code visual interface with an AI assistant capable of generating and modifying applications from natural language prompts.
Why the IT Backlog Problem Keeps Growing
The volume of applications enterprises now need has expanded well beyond what centralized IT teams can reasonably deliver through traditional development cycles. Internal tools, dashboards, workflow apps, and department-specific systems all compete for the same limited pool of developer time, and the backlog rarely shrinks on its own. Low-code platforms emerged as a partial answer to this problem, allowing business users to build simpler applications themselves. AI assistance is now pushing that capability further, reducing the technical fluency required to build something functional in the first place.
With Jitterbit’s low code app builder, users can create applications through a visual design interface or by describing the application they need to an AI assistant, which then generates the underlying structure, tables, and business logic. For IT teams, this doesn’t eliminate the need for skilled developers on complex, mission-critical systems, but it does mean simpler requests, the kind that used to sit in a backlog for weeks, can often be resolved directly by the business teams that need them.
Balancing Accessibility With Governance
One of the persistent challenges with democratizing app development is making sure accessibility doesn’t come at the expense of security or consistency. Applications built outside of IT’s direct oversight can introduce compliance risks if there is no structure governing how they connect to existing data and systems. This is part of why platforms built for enterprise use increasingly pair AI-assisted development with the same integration layer used for other automation, ensuring that an app built by a business user still connects into existing data sources and business rules rather than existing as an isolated, ungoverned tool.
Jitterbit’s platform has been recognized in Gartner’s Magic Quadrant for Enterprise Low-Code Application Platforms for its approach to this balance, and user reviews collected through Gartner Peer Insights have highlighted the platform’s ability to reduce dependence on highly specialized development resources while maintaining enterprise-grade security and compliance controls.
What This Means for the Next Generation of Business Applications
The broader implication of AI-assisted low-code development is a shift in who gets to build software within an enterprise. Historically, application development required either a trained developer or a lengthy request process through IT. As natural language interfaces mature, that requirement is loosening, without necessarily removing IT from the equation entirely. Instead, IT’s role shifts toward governance, architecture, and handling the genuinely complex builds, while AI-assisted tools absorb a larger share of the simpler, high-volume requests that used to consume disproportionate amounts of developer time.
For a closer look at how this works in practice, Jitterbit has published a demo walking through how its AI Assistant generates a working application from a natural language description in real time.
