According to a recent report from Gartner, Inc., generative AI (GenAI) is set to create new roles in software engineering and operations, prompting an urgent need for 80% of the engineering workforce to upskill by 2027. As AI technology continues to evolve, its integration into the software development process raises questions about the future of human engineers in the industry.
While there are concerns that AI might reduce the demand for human engineers or even replace them entirely, Gartner emphasizes that human expertise and creativity remain crucial in delivering complex and innovative software solutions. The report outlines three key phases in which AI is expected to impact software engineering roles:
- Short-Term Impact: Operating Within Boundaries
In the immediate future, AI tools will work within defined limits, enhancing productivity by augmenting existing developer workflows. These productivity gains are anticipated to be most significant for senior developers operating within organizations that have established mature engineering practices. - Medium-Term Transformation: Pushing Boundaries
As AI agents become more prevalent, they will revolutionize developer work patterns by enabling the automation and delegation of a wider array of tasks. This shift will herald the advent of AI-native software engineering, where the majority of code produced is generated by AI rather than authored by humans. In this new era, software engineers will adopt an “AI-first” mindset, focusing primarily on guiding AI agents with relevant context and constraints for specific tasks. Consequently, skills in natural-language prompt engineering and retrieval-augmented generation (RAG) will become essential. - Long-Term Evolution: The Rise of AI Engineering
Looking ahead, advances in AI will further streamline engineering processes, yet the demand for skilled software engineers will surge as organizations strive to develop AI-empowered software. This will give rise to a new breed of professionals known as AI engineers, who will possess expertise in software engineering, data science, and AI/machine learning (ML). These skills are increasingly sought after, as highlighted by a Gartner survey conducted in the fourth quarter of 2023. The survey, which included responses from 300 organizations across the U.S. and U.K., revealed that 56% of software engineering leaders identified AI/ML engineers as the most in-demand role for 2024, with a notable skills gap in applying AI/ML to applications.
To effectively support AI engineers, organizations must invest in AI developer platforms that facilitate the efficient integration of AI capabilities into enterprise solutions at scale. Such investments will also necessitate upskilling data engineering and platform engineering teams, enabling them to adopt the tools and processes essential for continuous integration and development of AI artifacts.
Source: Gartner
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