IBM's Deal With Salesforce Highlights the Company's Unique AI Position

Given how much several tech giants throw around the terms "artificial intelligence," "machine learning" and "deep learning," it's easy to assume that they're all trying to do similar things. And in some cases, the companies are indeed using AI to tackle problems that have much in common, particularly when it comes to making sense out of real-life sounds, images and dialogue. But a closer look shows that tech giants are at times not only tackling very different challenges, but employing different AI techniques to do so. IBM (IBM), which has set a goal of obtaining $10 billion in annual revenue related to its Watson AI platform by 2023, is especially an outlier -- not seen as a leader when it comes to certain large-scale, consumer-focused AI solutions, but very much one when it comes to AI offerings that require a measure of industry-specific expertise. The companies plan to pair Watson's ability to make sense out of data unique to fields such as health care, retail and financial services with Salesforce's Einstein AI platform -- it relies on the data taken in by Salesforce apps -- to deliver industry-specific insights, predictions and recommendations that can be useful for customer interactions. One such example given by the companies: By having Salesforce's Marketing Cloud apps plug into Watson programming interfaces (APIs), weather, local shopping and retail industry data analyzed by Watson could be paired with customer-specific shopping data analyzed by Einstein to "send highly personalized and localized email campaigns to shoppers."