Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices

TL;DR

This paper presents a research agenda for developing environmentally sustainable AI-enabled systems through software engineering, emphasizing key challenges like energy assessment, benchmarking, and sustainability-aware architectures.

Contribution

It outlines open research directions and practical recommendations for integrating sustainability into AI software engineering practices.

Findings

Identified key challenges in green AI development.

Prioritized research areas like energy benchmarking and adaptive architectures.

Provided a set of practical guidelines for sustainable AI systems.

Abstract

The environmental impact of Artificial Intelligence (AI)-enabled systems is increasing rapidly, and software engineering plays a critical role in developing sustainable solutions. The "Greening AI with Software Engineering" CECAM-Lorentz workshop (no. 1358, 2025) funded by the Centre Europ\'een de Calcul Atomique et Mol\'eculaire and the Lorentz Center, provided an interdisciplinary forum for 29 participants, from practitioners to academics, to share knowledge, ideas, practices, and current results dedicated to advancing green software and AI research. The workshop was held February 3-7, 2025, in Lausanne, Switzerland. Through keynotes, flash talks, and collaborative discussions, participants identified and prioritized key challenges for the field. These included energy assessment and standardization, benchmarking practices, sustainability-aware architectures, runtime adaptation, empirical methodologies, and education. This report presents a research agenda emerging from the workshop, outlining open research directions and practical recommendations to guide the development of environmentally sustainable AI-enabled systems rooted in software engineering principles.