A distinct correlation exists between an organization’s digital maturity and use of artificial intelligence (AI), a Cognizant report found. Those lower on the digital maturity curve, who classified themselves as beginners, said they were far less likely to consider themselves advanced in AI. While, digital mature organizations—also referred to as leaders—currently invest in AI to generate insights from data, rather than just simply collecting the information.

Cognizant’s Investing in AI: Moving Along the Digital Maturity Curve, released on Monday, surveyed nearly 2,500 executives globally to determine what it takes to reach digital maturity, identifying AI as the key component.

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Nearly 70% of respondents cited themselves as leaders in digital strategy, with the top tactics including implementing AI solutions (38%), replacing legacy systems (60%), and analyzing customer needs (47%), the report found.

“As businesses become more digital, they are generating and capturing more data and also unlocking new forms of data such as unstructured text, images, voice, and sound,” said Bret Greenstein, author of the report and senior vice president of AI and analytics at Cognizant. “More data doesn’t make you more digital; understanding that data and knowing what it means to your business is the heart of being digital. A digital leader uses AI to gather and understand all the data that matters in an effort to operate in new and more meaningful ways.”

The value of AI comes from its ability to process and draw insights from large amounts of data—a volume incomprehensible to humans. Most companies use AI to automate menial tasks, giving human workers the opportunity to spend their time on more impactful work, which is why companies plan to double AI projects in the next year.

However, advancements in AI allow companies to do more with the technology, such as optimize algorithms and analyze data that help organizations make educated business decisions.

Evolutionary AI use cases

The report referred to the latest advancements in AI as evolutionary AI, which is much more specialized than automating manual tasks. This type of AI can establish causality behind data, as well as predict decision outcomes and prescribe actions that will achieve the best results.

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Evolutionary AI unlocks two powerful concepts, according to the report. The tech allows companies to create a virtual representation of business and optimize the business through simulation. A virtual representation is created via a model of business performance data and past decisions. And instead of testing ideas on real people and machines, AI allows ideas to be experimented virtually.

To help organizations envision current AI applications, Greenstein outlined the following most popular AI use cases businesses are implementing now:

1. Driving operational improvements – from supply chain optimization, retail pricing, medical diagnosis and treatment, insurance underwriting, HR talent management, etc. These are all the things we do today with basic analytics and dashboards, but they are being transformed with AI to create better predictions and prescriptive guidance, which will squeeze the next level of efficiency.
2. Driving customer insights – from personalization, to web optimization, to conversational AI based customer service.
3. Driving speed and reducing cost through automation – back office automation is being transformed with AI, from understanding data sources like text documents, forms, and images for insurance and medical claims processing to providing intelligence decision making that provides optimal processing and reduced costs.

AI is a complicated concept and technology to maneuver, but the business benefits make the struggle worthwhile, the report said. And the technology is becoming so integral to organization that those that fail to adopt will be left behind.

“Companies that have been investing in AI are investing in both learning about the technology and applying it to their business, which is a real competitive advantage. Companies just beginning to transform with AI will have a hard time catching up to the leaders,” said Greenstein. “Companies that fall behind in AI, will also have a hard time operating with the efficiency, high performance decision making, and customer personalization that AI-led businesses will have.”

Along with AI adoption, the report said companies can become more digitally mature by establishing new roles and governance for data, assessing data, and thinking of ways to modernize data beyond the data warehouse.

For more, check out How to encourage AI adoption: 3 tips on TechRepublic.

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