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AI Adoption in Application Development Faces IT Roadblocks

By Greg Tavarez

GenAI continues to be a talking point for many organizations. Outside of work, I personally have a few conversations about the technology at home. I mean, it is a good tool to use to assist us with work, when used responsibly.

It can be used for drafting emails, brainstorming creative campaigns or even writing code. GenAI is the jack-of-all-trades that’s shaking up the workplace.

Hmm, I suppose what I am trying to get at here is that it feels like a clever sidekick every team didn’t know they needed.

And as organizations dive headfirst into leveraging GenAI for everyday tasks, it’s no surprise that its impact stretches into application development.

In fact, OutSystems revealed in its global 2025 State of Application Development report the obstacles IT professionals face when developing modern applications. Notably, the report found that the majority use GenAI to assist with traditional coding, but also found that GenAI introduces security and governance concerns for 62% of respondents.

One of the biggest challenges developers face is GenAI’s accuracy. According to the report, some tools produce correct code as little as 31% of the time, and even the most reliable solutions cap out at around 65%. With only 40% of respondents saying they trust GenAI to code autonomously, it’s clear the technology has room for improvement.

Integration issues also weigh heavily on teams, with half of the respondents citing difficulties in incorporating AI into existing workflows. The tools might be new, but the frustrations they bring echo age-old struggles with emerging tech.

Oh, and let’s not forget the fact that IT teams are stretched thin, often facing high costs and limited manpower to meet ambitious development goals. These constraints make traditional coding methods less viable, pushing organizations to embrace alternative approaches.

Yet, even as technology evolves, there’s a clear understanding among IT leaders that human oversight remains crucial. GenAI can accelerate processes, but it’s not yet a replacement for skilled developers. The report’s findings reflect a cautious optimism: professionals recognize the potential of AI but remain wary of its current limitations.

“As enterprises are increasingly opting to build software rather than buy it, today’s developers are under immense pressure to deliver mission-critical, customer-facing apps at unprecedented speed,” said Paulo Rosado, CEO and founder of OutSystems. “While GenAI is a powerful tool to increase productivity and develop code faster, AI-written code can lead to considerable security and governance issues if left unchecked, so IT leaders must consider ways to incorporate guardrails without stalling the speed of innovation.”

So, how do organizations overcome these hurdles?

Many organizations have turned to low-code development, a methodology that simplifies application creation by minimizing hand-coding. The report found that mature low-code platforms are delivering tangible benefits, including improved developer productivity, faster time to market and easier app updates.

Low-code’s ability to bring predictability to development cycles is particularly notable. Among those using low-code, 62% reported being able to consistently forecast budgets, compared to 52% of teams relying solely on traditional coding methods.

OutSystems has positioned itself at the intersection of these trends with its new tool, OutSystems Mentor. Designed to utilize low-code and GenAI, Mentor promises to redefine how applications are built and maintained. It enables teams to generate scalable, fully functional apps in minutes while maintaining tight control over quality and governance.

“In the Generative Software Cycle, we believe that GenAI and low-code in combination will redefine application development, increase productivity while ensuring governance throughout the entire software development lifecycle,” Rosado added. “Developer teams shouldn’t have to choose between high-quality, fully functional apps and speed-to-market, and by abandoning antiquated development practices in favor of AI-powered low-code technology, they can reap the performance and agility benefits of these transformative technologies.”

The combination of GenAI and low-code is emerging as a powerful strategy, but success will depend on how well these tools are integrated and managed. For now, developers find themselves at a crossroads. They must balance the promise of cutting-edge technologies with the practical realities of implementation, all while keeping pace with soaring demand. It’s a challenging environment, but one rich with opportunities for those willing to rethink traditional methods.

Be part of the discussion about the latest trends and developments in the Generative AI space at Generative AI Expo, taking place February 11-13 in Fort Lauderdale, Florida. Generative AI Expo covers the evolution of GenAI and will feature conversations focused on the potential for GenAI across industries and how the technology is already being used to create new opportunities for businesses to improve operations, enhance customer experiences, and create new growth opportunities.




Edited by Alex Passett
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