Artificial Intelligence: An engagement guide
1. Introduction Artificial intelligence (AI) presents both extraordinary opportunities and complexities for today’s companies. The OECD defines an AI system as “a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments”. An […]
Severine Neervoort is Global Policy Director, and Wendela Rang is Policy Executive at International Corporate Governance Network (ICGN). This post is based on their ICGN memorandum.
1. Introduction
Artificial intelligence (AI) presents both extraordinary opportunities and complexities for today’s companies. The OECD defines an AI system as “a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments”.[1] An increasing number of companies are using AI to transform existing business models or create new ones, generate greater efficiencies, and enhance strategic decision-making, all of which are critical for their competitiveness. However, AI also poses risks and challenges that company boards and management teams must be able to understand and address.
Investors expect companies to effectively navigate AI-related challenges whilst maximising the benefits of AI integration. Our Investor Viewpoint aims to encourage a constructive dialogue on this fast-evolving and increasingly important technology. We consulted the available sources and engaged with our members to provide a guide for investors and companies. This Viewpoint supports investors in assessing whether a company uses AI in a safe, ethical, and sustainable manner, leading to a series of questions for use in investors-investee dialogue. Also, by proactively using this guide, boards can anticipate investors’ areas of interest and concern, and better assess the robustness of their AI oversight.
