For Sharma, that meant starting from scratch, assembling a team of data scientists and building an AI pipeline. Sharma and his team then created a “smart audience platform” that places ads touting an artist’s latest release to listeners who are 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. Yet AI-based 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 are drowning in data these days. They collect it for legal and compliance reasons, and they also archive additional data in the expectation that it will come in handy someday.
That day has arrived. Or as Jason Hardy, global CTO at Hitachi Vantara puts it, companies are experiencing an “aha moment”: they realize that AI-based data analytics can deliver real business value from their collected data, creating a competitive advantage. He adds: “Traditionally, companies said, ‘Just file it and we’ll figure out what to do with it later.’ That has changed to a ‘No, this is really affecting us now; we need to be able to read and process that data in real time and draw conclusions from it.’”
This has become true in all industries. In manufacturing, better analytics can improve yields, reduce waste and increase efficiency. In consumer-facing businesses, AI can detect customers’ emotional responses to specific product placements or measure customer service satisfaction. In industries that rely on a supply chain, AI can predict and fix supply chain errors before they happen.
Adds Hardy, “We see customers saying, ‘I need to hop on this AI band. I have to figure this out. I need a platform to help me with that, whether it’s in the cloud or on premise or a combination of both.”
Unfortunately, most organizations don’t know where to start. Hardy says C-level executives tell him, “We want to use AI and machine learning. We want to use our data. We want to create value from it. We don’t actually know how. We don’t even know what question we’re trying to answer.”
This content is produced by Insights, the custom content branch of MIT Technology Review. It was not written by the editors of MIT Technology Review.