The Future of Generative AI in Software Engineering: A Vision from Industry and Academia in the European GENIUS Project

TL;DR

This paper presents a comprehensive vision for integrating Generative AI across the entire Software Development Life Cycle, emphasizing challenges, future advancements, and the role of industry-academic collaboration in shaping reliable, scalable solutions.

Contribution

It offers a strategic overview of GenAI's potential in software engineering, highlighting the GENIUS project's efforts to develop tools and address challenges for industry adoption.

Findings

Identified key challenges in GenAI adoption in SDLC

Outlined technological advances expected in five years

Proposed new roles and skills for software professionals

Abstract

Generative AI (GenAI) has recently emerged as a groundbreaking force in Software Engineering, capable of generating code, identifying bugs, recommending fixes, and supporting quality assurance. While its use in coding tasks shows considerable promise, applying GenAI across the entire Software Development Life Cycle (SDLC) has not yet been fully explored. Critical uncertainties in areas such as reliability, accountability, security, and data privacy demand deeper investigation and coordinated action. The GENIUS project, comprising over 30 European industrial and academic partners, aims to address these challenges by advancing AI integration across all SDLC phases. It focuses on GenAI's potential, the development of innovative tools, and emerging research challenges, actively shaping the future of software engineering. This vision paper presents a shared perspective on the future of GenAI-driven software engineering, grounded in cross-sector dialogue as well as experiences and findings within the GENIUS consortium. The paper explores four central elements: (1) a structured overview of current challenges in GenAI adoption across the SDLC; (2) a forward-looking vision outlining key technological and methodological advances expected over the next five years; (3) anticipated shifts in the roles and required skill sets of software professionals; and (4) the contribution of GENIUS in realising this transformation through practical tools and industrial validation. This paper focuses on aligning technical innovation with business relevance. It aims to inform both research agendas and industrial strategies, providing a foundation for reliable, scalable, and industry-ready GenAI solutions for software engineering teams.