A recent report from Gartner highlights that generative AI will significantly transform the landscape of software engineering and operations by 2027, creating new roles that will require upskilling for 80% of the workforce. This transformation will be driven by the increasing demand for advanced AI-empowered software and the essential skills needed to support it.
Key among these skills will be retrieval-augmented generation (RAG), a technique designed to enhance the accuracy and reliability of generative AI models. This shift will necessitate a new breed of highly skilled AI engineers capable of meeting the demands of a rapidly evolving technological environment.
Philip Walsh, Sr. Principal Analyst at Gartner, emphasized that, contrary to speculations suggesting AI might reduce the need for human engineers, the reality is quite different. “Human expertise and creativity will always be essential to delivering complex, innovative software,” he asserted.
Walsh pointed out that the future AI engineer will possess a unique blend of software engineering, data science, and AI/machine learning skills—an increasingly sought-after combination in the industry.
In the short term, Gartner analysts predict modest productivity boosts from AI tools that will augment existing developer workflows. These enhancements will be particularly impactful for senior developers in organizations with mature engineering practices.
Looking to the medium term, the rise of AI agents is expected to reshape developer work patterns, enabling them to automate and offload a greater number of tasks. This shift will usher in an era of AI-native software engineering, characterized by a predominance of AI-generated code over human-authored contributions.
“In this AI-native era, software engineers will adopt an ‘AI-first’ mindset, primarily focusing on steering AI agents toward the most relevant context and constraints for a given task,” Walsh explained. Consequently, natural-language prompt engineering and RAG skills will become critical competencies for software engineers.
In the long run, advancements in AI are anticipated to break new ground, leading to the emergence of what Gartner refers to as AI engineering. This evolution will demand an even larger pool of skilled software and AI engineers to satisfy the growing appetite for AI-driven software solutions.
A Gartner survey conducted in the fourth quarter of 2023 among 300 U.S. and U.K. organizations revealed that 56% of software engineering leaders identified AI/machine learning (ML) engineers as the most in-demand roles for 2024, citing the application of AI/ML to software as the largest skills gap.
To support the development of AI engineers, organizations must invest in AI developer platforms that facilitate the efficient construction of AI capabilities and the integration of AI into enterprise solutions at scale. “This investment will require organizations to upskill data engineering and platform engineering teams to adopt tools and processes that drive continuous integration and development for AI artifacts,” Walsh concluded.
