AI-powered data analysis helps to better understand the business

AI-powered data analysis helps to better understand the business

AI-powered data analysis helps to better understand the business

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For Sharma, that meant starting from scratch, building a team of data scientists, and creating an AI pipeline. Sharma and his team then created a “smart audience platform” that serves ads touting an artist’s latest release to listeners most likely to engage with that artist. The music industry may not be the first business case that comes to mind for AI and data analytics. Yet AI-powered data analytics can have a transformative impact in any industry and across a wide range of use cases.


Why Businesses Need Advanced Data Analytics

Today, most organizations are overwhelmed with data. They collect it for regulatory and compliance reasons, and they also archive additional data in hopes that one day it will be useful to them.

This day has arrived. Or, as Jason Hardy, Global CTO at Hitachi Vantara puts it, companies are having an “aha moment”: they are realizing that AI-powered data analytics can deliver real business value from their collected data. which gives them a competitive advantage. He adds: “Traditionally companies would say, ‘Just archive it and we’ll see what to do with it later.’ It turned into a ‘No, it’s really affecting us now; we need to be able to read that data in real time, process it, and infer it.

AI-powered data analysis helps to better understand the business

This has become true across all industries. In manufacturing, better analytics can improve yield, reduce waste and increase efficiency. In consumer-focused businesses, AI can detect customers’ emotional reactions to specific product placements or measure satisfaction with customer service. In industries that depend on a supply chain, AI can predict and mitigate supply chain defects before they happen.

Hardy adds, “We see customers saying, ‘I need to jump on the AI ​​bandwagon. I have to understand that. I need a platform to help me do this, whether it’s in the cloud or on-premises 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 derive value from it. In fact, we don’t know how. We don’t even know what question we’re trying to answer.

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This content was produced by Insights, the custom content arm of MIT Technology Review. It was not authored by the editorial staff of MIT Technology Review.


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