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AI Efforts at Large Companies May Be Hindered by Poor Quality Data

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Cables inside a data center in Paris.

Large firms are finding that poor-quality customer and business data may be keeping them from leveraging digital tools to cut costs, boost revenues, and remain competitive, according to a survey by PricewaterhouseCoopers.

Credit: Christian Hartmann/Reuters

Poor-quality customer and business data may be keeping companies from leveraging artificial intelligence (AI) and other digital tools to reduce costs, increase revenue, and stay competitive, according to a recent PriceWaterhouseCoopers (PwC) survey of 300 executives at U.S. companies in a range of industries with revenue of $500 million or more.

While 76% of survey respondents said their firms want to extract value from the data they already have, just 15% said they currently have the right kind of data needed to achieve that goal.

Most of the respondents said their firms see tremendous upside opportunity in fully optimizing the data they already have, but face multiple obstacles to achieving that goal including the quality limitations of the data.

Companies working with older, unreliable data need to first assess that data by identifying its source, gauging its accuracy, and standardizing data formats and labels, according to PwC.

From The Wall Street Journal
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Abstracts Copyright © 2019 SmithBucklin, Washington, DC, USA


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