For Sharma, that meant building a team of data scientists and building an AI pipeline from the ground up. Sharma and his team then created a “smart audience platform” that placed ads promoting the artist’s latest work in front of listeners who were most likely to engage with the artist. The music industry may not be the first to think of a business case for artificial intelligence and data analytics. However, AI-based data analytics can have a transformative impact on 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 it for regulatory and compliance reasons, and they also archive additional data in the hope that it will come in handy someday.
That day has come. Or as Jason Hardy, Global CTO of Hitachi Vantara, puts it, companies are experiencing an “aha moment” – realizing that AI-based data analysis can provide real business value from the data they collect, thereby providing a competitive advantage. He added, “Traditionally, companies would say, ‘Just archive it and we’ll figure out what to do with it later.’ That becomes, ‘No, this actually affects us; we need to be able to read that in real time. data and process and infer about it.’”
This has become a reality in all walks of life. In manufacturing, better analytics can increase yields, reduce waste and increase efficiency. In a consumer-centric business, AI can detect a customer’s emotional response to a particular product placement or measure satisfaction with customer service. In industries that rely on supply chains, AI can predict and mitigate failures in supply chains before they occur.
Adds Hardy: “We’re seeing customers say, ‘I’ve got to jump on this AI bandwagon. Of.”
Unfortunately, most organizations don’t know where to start. Hardy said C-level executives told 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 the questions we’re trying to answer.” “
This content was produced by Insights, the custom content division of MIT Technology Review. It was not written by the editorial staff of MIT Technology Review.
