This webinar features a panel of leading investors sharing their perspectives on corporate digital responsibility related to AI. They will discuss specific AI assurance practices they look for, examples where AI governance concerns have impacted investments, and the role of third-party audits and ethics review boards in building confidence.
Attending this webinar will equip responsible AI practitioners with an understanding of the clear business case for AI assurance, enabling them to champion it within their own organizations. This session will also break down silos by demonstrating that investors are aware of and consider AI assurance mechanisms, underscoring their purpose and prioritization in due diligence and funding efforts.
Hear the investors' views on the challenges for startups in scaling AI assurance as systems advance. Learn how to align responsible AI initiatives with investor needs and expectations. Investors face significant challenges in evaluating the risks and potential of AI-driven companies and technologies, particularly in the realm of AI assurance and responsible AI practices. As AI becomes increasingly integrated into business operations and products, investors need to accurately assess the robustness, ethics, and long-term viability of AI systems. However, many investors lack a clear framework for evaluating AI assurance practices, leading to potential oversights in due diligence and investment decisions.
Don't miss this opportunity to understand why responsible AI is critical for attracting investment and long-term growth for startups and scale-ups.
Attending this webinar will provide audience members with a compelling business case for AI assurance, empowering them to advocate for it more effectively within their own organizations. This session will also help bridge knowledge gaps by clearly demonstrating that investors are keenly aware of AI assurance mechanisms and actively consider them when conducting due diligence and making funding decisions, underscoring the critical importance of prioritizing AI assurance practices.
