Rapid generative AI adoption across enterprise functions presents diverse opportunities and significant challenges. Organizations recognize clear pathways to enhanced productivity and new revenue streams, yet most deployments remain cautious and limited, yielding minimal rewards. Despite widespread generative AI risk awareness, most enterprises are unprepared to manage these effectively. However, enterprises with mature risk management strategies achieve 25% higher rewards compared to those who do not have similar risk management maturity, highlighting the vital link between risk management capability and business value.
In this report, we examine how enterprises can move beyond cautious experimentation to realize substantial returns from their generative AI investments. The report explores the quality function’s role in assuring AI applications across layers and adoption stages. This research benefits enterprises seeking to build robust risk management strategies while scaling their AI initiatives responsibly and sustainably.
Scope
All industries and geographies
Contents
In this report, we:
Examine generative AI adoption’s current enterprise status
Recommend a roadmap for managing generative AI adoption risks
Analyze the approach for the quality function to assure generative AI rewards
