Learn how 33 organizations across industries are accelerating decision making, improving business processes, enhancing user engagement, reducing costs and driving growth and profitability.
Fraud detection, improving marketing campaigns, speeding up repairs in the utility sector, treating drug addiction, fast-tracking cancer treatment, and optimizing equipment utilization – AI and data are already used in a variety of use cases among our clients to improve outcomes.
One of the important trends we see in AI is the move from advanced model building, fueled by breakthroughs in scalable neural network technology – deep learning – to creative optimization, enabled by breakthroughs in making evolutionary computation scalable. In recent years, we’ve seen this technology move out of research labs and into major commercial deployments, including automated trading, web site optimization, automated industrial design and even agriculture.
The marriage of evolutionary computation and deep learning — Evolutionary AI — promises a new era of advanced, robust solutions that are designed by AI, by computers. These AI-based decision augmentation systems will go beyond creating new insights to suggest optimum actions in contexts that have never been encountered before, impacting outcomes that businesses care about most.
The 33 case studies gathered in this whitepaper present a range of real-world examples that illustrate how we help our clients solve their most critical business issues through data and AI. These cases show how modern data and intelligence can enhance an existing application, workflow or process and reduce friction; solve complex business problems by stitching together multiple parts of an experience; and offer up entirely new channels of revenue and service in ways not possible using traditional techniques.
Let these case studies inspire your journey and inform how data modernization and artificial intelligence are applied within your company and across industries. Also, check out Cognizant's view on how AI can reinvent decision-making.