Summary

In this presentation on AI trustworthiness, Sahil and Hari explore the critical challenge of ensuring safe and reliable AI systems across industries like telecommunications and industrial IoT. Drawing on McKinsey and EVI research, they highlight that while 78-95% of companies are adopting AI, only 11% are focused on AI governance, which can lead to significant silent failures with potentially millions of dollars in lost revenue. The key takeaway is that trustworthy AI requires three main pillars: explanability (understanding the decision-making process), traceability (capturing and retracing system steps), and a comprehensive approach to understanding AI's long-term impact on business operations.