Dr. Curtis Rasmussen believes that the pressure on business leaders to deliver AI-driven returns has never been higher. Yet, he believes that a foundational disconnect persists: organizations continue to deploy advanced systems without fully understanding the people who must use them, the workflows those systems alter, or the technical constraints behind the tools themselves.
The consequences of this, he believes, are playing out across the industry. A recent MIT report notes that the failure rate for generative AI projects in organizations is 95%, despite directing billions of dollars in investment. For Rasmussen, those numbers reflect deep technical inefficiencies and a deeper misalignment between human readiness and machine design. He notes that together, these imbalances can lead to confusion, rushed decisions, and, in some cases, costly reversals for companies trying to automate without understanding what should and should not be automated.
