How to find the business value in AI and ML

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - August 3. Join AI and data leaders for insightful talks and exciting networking opportunities. There's no doubt that, when applied effectively, machine learning (ML) and artificial intelligence (AI) have proven potential to deliver significant value and cutting-edge technological innovation. But many organizations are struggling with the "effectively" part, according to a new survey. Despite the fact that businesses are increasingly undertaking initiatives to leverage ML and AI, many tools and projects lack appropriate resources, are far less productive than they should be, lag in deployment, and more often than not, fail or are abandoned. In short, business value is rarely captured – and very often falls short of expectations – because significant time, resources and budgets are being wasted, according to a 2021 survey of ML practitioners, "Too Much Friction, Too Little ML." "Building AI is hard," said Gideon Mendels, CEO and cofounder of Comet, the enterprise ML development platform company that commissioned the survey. "ML is often a slow, iterative process with many potential pitfalls and moving parts.