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How Artificial Intelligence Recommendation systems solve real world problems

Artificial intelligence and machine learning is paying off for companies that are adopting this new technology. According to Deloitte 82% of enterprises adopting machine learning and AI have gained significant financial advantage from their investments. Here is an example of machine learning as applied to challenges businesses face everyday.

Anyone who has bought something on Amazon or streamed a video on Netflix is familiar with recommendation engines. These are really exercises in personalisation. Artificial intelligence and machine learning helps companies detect patterns based on what customers have purchased in the past, what they’ve clicked, or even where they’ve hovered on a particular screen. They use this information in combination with other data—for instance, the customer’s age, gender, or geographic locale—to recommend other products or services that they might like, personalised to their tastes—as perceived by the machine-learning algorithms powering the recommendation engine.

Recommendation engines are often expanded with machine learning to predict click-throughs, so businesses know who is most likely to click on an ad. They also learn when to offer timely discounts, including knowing the precise times to send promotional codes to

customers so that they will make purchases. You can learn more on building recommendation engines through our course at huruschool.org/ai

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