Successful organizations take a systematic approach to Responsible AI from the start. They understand the scale and complexity of change required. And they address challenges in parallel.
Like this, they move from principles to practice with confidence, support the professionalization of AI enterprise-wide, and put in place the structures needed to prove the long-term value of Responsible AI.
Our conversations identified a range of organizational, operational, technical and reputational challenges that hold well-intentioned organizations back. While the initial focus is often on ethical and legal requirements, success is also a function of an organization’s ability to modify its traditional ways of working to support Responsible AI—and AI more broadly. In undertaking this process, organizations also establish the structures needed to demonstrate the long-term value of Responsible AI by scaling it across the organization and enable the essential move from “practice to proof.”
We use a set of 25 questions to help our clients to benchmark their motivators and challenges, together with their maturity in terms of people, process and technology against their peers. Where are you on your Responsible AI journey?