If software engineers don’t upgrade their skills, Gartner warns 80% may lose their jobs to AI

According to analysts at Gartner Inc., more than 80% of software engineers will need to acquire new skills, such as natural-language prompt engineering and retrieval-augmented generation (RAG), to stay competitive in the job market as generative AI continues to rise. In a recent note, the global research firm emphasized that while AI won’t replace software engineers, it will create new roles and opportunities for them. “Despite bold claims about AI’s capabilities, it won’t eliminate the need for human engineers but will reshape their roles. Human creativity and expertise will remain vital in delivering complex, innovative software,” said Philip Walsh, a senior principal analyst at Gartner.

Walsh also highlighted the significance of investing in AI developer platforms, stating that organizations will need to upskill their data and platform engineering teams to adopt tools and processes that enable continuous integration and development of AI artifacts.

Discussing recent trends, Gartner noted that a survey conducted among 300 organizations in the US and UK revealed that about 56% of software engineers believe that AI/ML engineering roles are the most in-demand. Many of them also acknowledged that they currently lack the necessary skills to integrate AI/ML capabilities into applications.

One promising use of generative AI is its potential to assist in code generation, leading to a surge in AI coding tools such as GitHub Copilot and Anthropic’s Claude. AI coding startup Supermaven gained significant attention last month when it secured $12 million in its first funding round, led by Bessemer Venture Partners.

However, there are ongoing debates about the effectiveness of AI in coding. Some studies indicate a decline in the quality of AI-generated code, and it’s uncertain whether these tools actually enhance productivity. For instance, a survey of 800 developers using GitHub Copilot found no measurable productivity gains. In fact, those developers reported a 41% increase in bugs within pull requests when using the AI tool for writing code.