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

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Putting Humans at the Heart of AI

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The Role of Human Emotion in Decision-Making

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Conversational AI—New Interfaces & Applications of Voice Interaction

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How Can Businesses Create Value Using AI

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

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

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Don't Let Humans Harm AI | Making AI Effective

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How to Avoid Failures in AI | Making AI Effective

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Building and Running AI Ethically | Making AI Effective

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The Road to Responsible and Effective AI | Making AI Effective

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Uncovering the Hidden Jewels | Making AI Effective

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Driving Business Results Using AI | Making AI Effective

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Injecting Data Science Into the Value Chain | Making AI Effective

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AI Is More Than Picking a Platform | Making AI Effective

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

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What Is Surrogate Modeling? An Evolutionary Computation Technique

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What Is Evolutionary Computation

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