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12 most popular AI use cases in the enterprise today

CIO Business Intelligence

Organizations all around the globe are implementing AI in a variety of ways to streamline processes, optimize costs, prevent human error, assist customers, manage IT systems, and alleviate repetitive tasks, among other uses. And with the rise of generative AI, artificial intelligence use cases in the enterprise will only expand.

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What is predictive analytics? Transforming data into future insights

CIO Business Intelligence

By optimizing marketing campaigns with predictive analytics , organizations can also generate new customer responses or purchases, as well as promote cross-sell opportunities. Predictive models can help businesses attract, retain, and nurture their most valued customers. Forecast financial market trends.

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AI in marketing: How to leverage this powerful new technology for your next campaign

IBM Big Data Hub

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. AI can help marketers create and optimize content to meet the new standards.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

As it pertains to social media data, text mining algorithms (and by extension, text analysis) allow businesses to extract, analyze and interpret linguistic data from comments, posts, customer reviews and other text on social media platforms and leverage those data sources to improve products, services and processes.

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How to accelerate your data monetization strategy with data products and AI

IBM Big Data Hub

Data monetization is not narrowly “selling data sets ;” it is about improving work and enhancing business performance by better-using data. External monetization opportunities enable different types of data in different formats to be information assets that can be sold or have their value recorded when used.

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Top 10 IT & Technology Buzzwords You Won’t Be Able To Avoid In 2020

datapine

Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI. There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others. Blockchain.

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Data Science, Past & Future

Domino Data Lab

But the business logic kept getting more and more progressively rolled back into the middle layer, also called application servers, web servers, later being called middleware. Then in the bottom tier, you had your data management, your back office, right? The data governance parts of it have become more and more important.