Disclosure of AI-related impacts, risks, and opportunities

Key Takeaways

• As the uptake of AI systems accelerates across all industries, decision-makers need insight into how the potential impacts of AI — such as bias, privacy, and emissions — interact with companies’ ability to create value for investors and other stakeholders.
• Investors, regulators, and analysts should receive high-quality information about the impacts, risks, and opportunities of AI in formal financial and sustainability reports, just as they do today on topics such as compliance, supply chain resilience, and human capital.
• Quality and consistency in reporting across major companies can be enhanced. The substance and location of disclosures vary significantly from company to company, and dialogue is needed to develop additional disclosure recommendations that address AI’s impacts, risks, and opportunities.
• A corporate-level AI assessment framework can help companies identify and prioritize a full range of AI-related impacts, risks, and opportunities across their value chains. This framework should be developed in collaboration with companies that develop and deploy AI systems, investors, and other stakeholders.

Summary

AI is transforming business models and operations, so more high-quality information is needed about how companies are managing AI-related impacts, risks, and opportunities. As AI systems become more prevalent across multiple industries, decision-makers need greater insight into efforts to address issues such as bias, privacy, and environmental impacts.

This landscape analysis of the current state of formal reporting examined 50 of the world’s largest companies and assessed the quality and quantity of AI disclosures in financial and sustainability reports. The landscape analysis identified emerging best practices and highlighted the need for more consistent, comparable, and decision-useful information.

We found that even among the world’s major companies, the quality, quantity, and location of disclosures vary significantly. While best practices have emerged, there are significant gaps in how companies report AI-related impacts, risks, and opportunities.

Key findings of the Analysis

• Quantity of disclosure exceeds the quality of disclosure
• Disclosures lack consistency and comparability
• Location of disclosure (e.g., financial, sustainability, or AI-specific reports) varies
• Tech companies report more than non-tech companies
• Quantitative metrics are absent from disclosures
• Risks of specific AI models are not formally disclosed
• Links among impacts, risks, and opportunities are important
• Improved disclosure guidance for AI is needed

We will continue to build on this work, and look forward to collaborating with our community to advance formal reporting of AI-related impacts, risks, and opportunities. Download the full landscape analysis and read the brief.