AI Projects Are Hard to Scale

Gartner research shows only 53% of projects make it from artificial intelligence (AI) prototypes to production. There are two reasons for that: First, in the midst of frequently overhyped expectations, a clear path toward the real value for the organization is often not defined for the initial project. The second reason, which is even more important and often ignored: The technical gap between a shiny prototype and putting the results of that prototype into production is big. Bridging that gap between the creation of a combination of data wrangling and model optimization through to deploying that process often requires a complex, sometimes even manual step. Worse, the technologies used are seldom aligned well.