Gartner predicts that by 2027, 80% of the engineering workforce will need to upskill to adapt to generative AI (GenAI), which will create new roles in software engineering and operations. Despite concerns that AI might reduce the demand for human engineers, Gartner emphasizes that human expertise will remain crucial for delivering complex and innovative software.
Gartner analysts foresee AI impacting software engineering in three phases:
1. Short-term: AI will augment current developer tasks, leading to modest productivity gains, particularly for senior developers in organizations with advanced engineering practices.
2. Medium-term: AI agents will automate more tasks, signaling the rise of AI-native software engineering, where most code is generated by AI. Developers will focus on guiding AI agents using natural-language prompt engineering and retrieval-augmented generation (RAG) skills.
3. Long-term: The demand for skilled software engineers will increase as AI continues to evolve, marking the rise of the “AI engineer.” These professionals will require expertise in software engineering, data science, and AI/machine learning (ML).
A 2023 Gartner survey found that 56% of software engineering leaders see AI/ML engineers as the most in-demand role for 2024, with AI/ML application being the largest skills gap. To meet these needs, organizations will need to invest in AI developer platforms and upskill teams in data and platform engineering to integrate AI more efficiently at scale.
