Preparing Data for AI

Preparing Data for AI

Case Studies

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Examining physician notes identified social determinants of health, helping improve both quality of care and costs.

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A global consumer-goods client now has an automated way to syndicate product data to its 500 ecommerce partners.

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$5-$7 million improvement in credit card collections shown by identifying causal factors of cardholder payments.

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Fast-food chain reduces drive-through order time by 10% and improves decision-making, staffing and marketing.

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A P&C insurer now reviews 8,000 customer service calls per month, slashing supervisor review time by 35%–40%.

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An electric utility is using AI image analytics to quickly identify maintenance issues, reducing outages and costs.

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A biotechnology company better understands factors in patients following or abandoning medication regimens.

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A large healthcare organization alerts for drug-seeking behaviors, combatting prescription drug dependence.

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Cross-referencing research data speeds drug development and lowers clinical trials cost. 

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A top global insurance company used data to identify $3.3 billion in insurance opportunities with 83% accuracy.

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A large health network identified and recommended appropriate solutions to improve interactions and satisfaction.

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A global professional services company, reducing researcher time 14%, boosted reports output 30%.

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A global reinsurance company has improved underwriting efficiency, reduced time and increased acceptance rates.

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A major bank’s check fraud system processes 1,200 checks per second and saves the bank $20 million annually.

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A major mining company optimized employee housing and transportation management, saving $4 million per year.

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A leading regional utility is using a virtual assistant to automate customer research to better inform its sales team.

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A major pharmaceuticals company has reduced clinical oncology trials by 3-4 years and saved 10% in patient costs.

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A global mining company increased transportation throughput by 8% and reduced annual capital costs by $30 million.

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A global life sciences company migrated 150TB, reduced data-hosting costs by 95% and saved the company $3.6 million/yr.

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Learn how these 21 organizations improved their profitability and decision-making with artificial intelligence.

Preparing Data for AI Videos


Putting Humans at the Heart of AI


The Role of Human Emotion in Decision-Making


Conversational AI—New Interfaces & Applications of Voice Interaction


How Can Businesses Create Value Using AI


Dr. Jerry Smith Speaks About AI Bias and the Nuances of Human Behavior


The Importance of Governance in an AI World | Making AI Effective


Don't Let Humans Harm AI | Making AI Effective


How to Avoid Failures in AI | Making AI Effective


Building and Running AI Ethically | Making AI Effective


The Road to Responsible and Effective AI | Making AI Effective


Uncovering the Hidden Jewels | Making AI Effective


Driving Business Results Using AI | Making AI Effective


Injecting Data Science Into the Value Chain | Making AI Effective


AI Is More Than Picking a Platform | Making AI Effective


What Is Data IQ and Why Is It Important? | Making AI Effective


What Is Surrogate Modeling? An Evolutionary Computation Technique


What Is Evolutionary Computation

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