AI cuts development time by 50%, but concerns on job losses grow

New research commissioned by OutSystems in collaboration with KPMG has examined the impact of artificial intelligence (AI) on the software development lifecycle (SDLC).

The survey, which involved 555 software executives from various industries, including IT consultancy services, manufacturing, banking, financial services, and insurance, aimed to understand current AI usage, future plans, and challenges encountered by IT leaders.

According to the study, 84% of respondents stated that their organisations began incorporating AI technologies into their SDLCs between six months to five years ago. Early adopters were predominantly from IT services companies.

The research indicates that AI's primary applications in software development include testing, quality assurance, and security vulnerability detection. The study also highlights the significant potential of generative AI (GenAI) to enhance these processes and introduce new capabilities.

A key outcome from the survey is that 75% of software executives have reported up to a 50% reduction in development time due to AI and automation implementation. The future seems geared towards increased AI integration with 71% of respondents planning to incorporate AI into application development and SDLC management workflows.

Paulo Rosado, CEO and founder of OutSystems, commented, "AI is redefining the impossible. I'm laser-focused on helping teams compress multi-year legacy modernization projects into just a few months. The latest AI disruptions have brought us the potential to compress these development timelines into even shorter and faster projects. With AI, historically impossible transformation projects are not only possible but easier, cheaper, and faster to accomplish."

The role of developers is also evolving due to AI, according to Rodrigo Coutinho, Co-founder and AI Project Manager at OutSystems. "Right now, the developer's role is shifting from code writer to code reviewer. Large language models (LLMs) are a big help, but they still make mistakes. But as these models evolve, and trust in the resulting code improves, the developer's role will be more akin to that of an orchestrator and acceptance tester of AI-generated outputs," he said.

While confidence in AI has grown, the report acknowledges ongoing challenges. Half of the respondents noted that AI has improved software quality, decision-making, and efficiency in software testing. However, risks such as technical debt, orphan code, context-specific requirements, and scalability issues remain. Additionally, 56% of respondents expect to experience higher application quality with fewer bugs and improved performance due to AI.

Significant barriers to broader AI adoption in the SDLC have been identified, particularly data privacy and security concerns, which were cited by 56% of respondents. Regulatory, compliance challenges and integration difficulties with existing workflows were also prominent concerns.

Michael Harper, Managing Director at KPMG U.S., remarked, "There's a lot of speculation on what will change with the rise of GenAI. While there will be challenges, those with effective change management initiatives will reskill and upskill their workforces, leading to AI and jobs evolving in tandem."

Furthermore, one-third of the respondents indicated a backlog of between 150 and 800 use cases for GenAI. The speed of AI advancements is prompting nearly all respondents to consider increasing their investments in AI. Despite concerns over the reliability of AI-generated code, developers can mitigate risks with strategies such as user acceptance testing, unit testing, and regression testing.

However, not all feedback was positive. Challenges include the limited availability of skilled personnel and the difficulty of integrating GenAI into existing tech stacks. There is also a widespread concern about job displacement, with 89% of respondents indicating that some roles might be eliminated by AI. Nonetheless, there is a possibility that AI might create more jobs in the long run, facilitated by developers with specialised AI skills.