For Sharma, that meant starting from scratch, putting together a team of data scientists, and building an AI pipeline. Sharma and his team then created a “smart audience platform” that advertises an artist’s latest release in front of listeners who are most likely to interact with that artist. The music industry may not be the first business case that comes to mind for AI and data analytics. However, AI-driven data analytics can have a transformative impact in any industry and across a wide range of use cases.
Why companies need advanced data analytics
Most organizations today are drowning in data. They collect them for regulatory and compliance reasons, and archive additional data in the hope that it will be useful someday.
This day came. Or, as Jason Hardy, global CTO of Hitachi Vantara, puts it, companies are having an “aha moment”—realizing that AI-driven data analytics can deliver real business value based on the data they collect that provides a competitive advantage. He adds: “Traditionally, companies have said, ‘Just archive it, and we’ll decide what to do with it later.’ It turned into “No, this is really affecting us right now; we need to be able to read this data in real time, process it and draw conclusions based on it.”
This has become a reality in all industries. In manufacturing, better analytics can increase productivity, reduce waste, and improve efficiency. In consumer-facing companies, AI can detect customer emotional responses to specific product placements or measure satisfaction with customer service. In industries that rely on the supply chain, AI can predict and correct supply chain disruptions before they happen.
Hardy adds: “We see clients saying, ‘I have to jump on this AI bandwagon. I must understand this. I need a platform to help me do this, whether it’s in the cloud, on-premise, or a combination of both.”
Unfortunately, most organizations don’t know where to start. Hardy says senior executives tell him, “We want to use AI and machine learning. We want to use our data. We want to create value from this. We don’t really know how. We don’t even know the question we’re trying to answer.”
This content was prepared by Insights, the user-generated content division of MIT Technology Review. This was not written by the editors of the MIT Technology Review.