Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework
Sung Une Lee, Harsha Perera, Yue Liu, Boming Xia, Qinghua Lu, Liming Zhu, Jessica Cairns, Moana Nottage
TL;DR
The paper addresses the need to integrate Responsible AI with ESG considerations from an investor perspective by delivering a practical ESG‑AI framework and toolkit. It follows a collaborative, three-phase methodology—pre-engagement, engagement with 28 companies across eight sectors, and a framework development phase with iterative investor input—to produce three core components: AI Use Case, RAI Governance Indicators, and RAI Deep Dive Assessment. Key contributions include the 10 governance indicators with a governance score, a 42-question deep-dive aligned to eight AI ethics principles, and 43 guide metrics plus six mandatory metrics (with ERA-aligned requirements from EU AI Act and NIST RMF) to support disclosure and risk management. The framework has demonstrated real-world applicability, released publicly in April 2024, and has generated substantial investor and industry engagement, signaling practical impact for guiding ethical and sustainable AI investments across sectors.
Abstract
Artificial Intelligence (AI) is a widely developed and adopted technology across entire industry sectors. Integrating environmental, social, and governance (ESG) considerations with AI investments is crucial for ensuring ethical and sustainable technological advancement. Particularly from an investor perspective, this integration not only mitigates risks but also enhances long-term value creation by aligning AI initiatives with broader societal goals. Yet, this area has been less explored in both academia and industry. To bridge the gap, we introduce a novel ESG-AI framework, which is developed based on insights from engagements with 28 companies and comprises three key components. The framework provides a structured approach to this integration, developed in collaboration with industry practitioners. The ESG-AI framework provides an overview of the environmental and social impacts of AI applications, helping users such as investors assess the materiality of AI use. Moreover, it enables investors to evaluate a company's commitment to responsible AI through structured engagements and thorough assessment of specific risk areas. We have publicly released the framework and toolkit in April 2024, which has received significant attention and positive feedback from the investment community. This paper details each component of the framework, demonstrating its applicability in real-world contexts and its potential to guide ethical AI investments.