How GenAI and Low-Code are Turbo-Charging Software Development

When low-code platforms first burst onto the scene, many considered them game-changers. The ability to rely less on traditional programmers, despite limited coding knowledge, promised a democratizing revolution in software, even if questions of governance at scale, security, and long-term maintenance were not yet fully resolved.

But as businesses grew and innovated, many companies still looked to highly skilled developers to meet their needs.

Today, the demand for tech talent is far outpacing supply. And while growth in software development as a profession is expected to swell by more than 25% over the next 10 years, it’s just not enough. An expected 750 million cloud-native apps are forecast to be created globally by 2025. To accomplish that, low-code is again back in the spotlight; only this time backed by a technology that is truly game-changing.

Enter generative AI.  When married with low-code platforms, generative AI can:

• Lower barriers of skill or technology for anyone to build automations and apps, with no coding knowledge
• Streamline dev processes and first mile setup for high skilled developers, increasing productivity and higher velocity leading to reduce IT backlogs

When employing these tools effectively, there is often a multiplier effect.

For the so-called “citizen developer”— or non-IT-trained employees who create software — there can be an almost transformative result, injecting novel approaches and a diversity of perspectives into software development. A business analyst, for example, who knows a company’s pain-points and bottlenecks could be empowered, using AI-powered low-code platforms, to automate operational processes in ways that were never possible in the past.

For the highly skilled IT worker, who knows how to prompt the AI in specific ways, that individual could see massive efficiency and velocity gains in productivity.

Assume, for example, that 60% of software development is boilerplate – it relies on sections of code that are repeated frequently with no or little variation. The other 40% is where the majority of customization and changes occur. By using a localized AI-powered low-code platform to identify and automate those boilerplate tasks, the skilled developer is then freed up to spend more time and brainpower on what the remaining 40% requires.

The result is often a better and more quickly developed product. And that is something companies are beginning to recognize in greater numbers. In fact, such tools are already reshaping much of the landscape.

By the Numbers

By 2026, it is projected that developers outside company IT divisions will account for at least 80% of the user base for low-code development tools. That’s up from 60% in 2021, according to the technological research and consulting firm, Gartner. Meanwhile, other low-code technologies, such as rapid mobile app development (RMAD) and rapid application development (RAD) programs – designed to help developers build apps more quickly – are also increasing.

Such tools, powered by generative AI, also integrate within existing systems and infrastructure. For instance, if a company wanted to build a tracker for marketing events, it could utilize pre-built ServiceNow technologies. And, by leveraging those platforms and using natural language inputs, like an English-based text, the tracker could be built within minutes.

The hurdle for companies, however, may be just in getting started. Even for those who embrace low-code, training is often needed for broader adoption among employees. But there are ways to mitigate those obstacles, including chat interfaces that are becoming ever more effective and user-friendly.

The Bottom Line

In the end, it’s worth it.

AI-powered low-code platforms are a way of shortcutting the traditional app-development process, getting to the design, dev and release phase within just minutes, as opposed to weeks or months. Governance and control are still paramount, however. And security measures need to be established to make certain applications safe before they are widely adopted.

But the possibilities are virtually endless. And with the right tools, companies can make themselves more responsive to market needs, and more agile in making good on new ideas.

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