Enterprises are struggling to move beyond the pilot stage with their ai initiatives, with a significant gap between initial success and full operationalization. Various factors, including data and skills gaps, architecture, and talent shortages, are cited as potential obstacles to achieving enterprise-wide ai value. The extent to which these challenges are universal is unclear, with multiple studies and reports highlighting different aspects of the issue.