Invest in AI

Artificial Intelligence or AI has become a synonym for anything that seems futuristic. Is AI this much complicated and can companies truly get the benefits by investing in AI? When we say invest in AI, what do we mean?

Let’s look at the various categories of AI being employed and provide a framework for how companies should start to shape up their cognitive capabilities in the next numerous years to attain their professional purposes.

Invest in AI

3 Categories of AI

It is beneficial for companies to look at AI through the lens of business competences rather than technologies. Largely talking, AI can provide three important business requirements:

  • Automating business processes,
  • Gaining insight through data analysis
  • Engaging with customers and employees

Process automation

The utmost common kind was the automation of digital and physical responsibilities—typically back-office administrative and financial activities—by means of robotic process automation skills. Robotic Process Automation or RPA is the least expensive and easiest to implement of the cognitive technologies we’ll discuss here, and characteristically brings a rapid and high return on investment.

Cognitive insight

Cognitive insights provided by machine learning vary from those existing from traditional analytics in three ways: They are usually much more data-intensive and thorough, the models typically are trained on some part of the data set, and the models get better—that is, their ability to use new data to make predictions or put things into groups improves over time. Forms of machine learning (deep learning, in specific, which tries to mimic the motion in the human brain in order to identify patterns) can perform acts such as distinguishing images and speech. Machine learning can also make existing new data for better analytics. While the activity of data curation has historically been quite labor-intensive, now machine learning can classify probabilistic matches—data that is likely to be associated with the same person or company but that appears in slightly different formats—across databases.

Cognitive engagement

Projects that involve employees and customers using natural language processing chatbots, intelligent agents, and machine learning were another common type used by different companies. Companies tend to take a conservative tactic to customer-facing cognitive engagement technologies mostly because of their immaturity. The strategy is to ultimately let customers engage with the cognitive agent directly, rather than with the human customer-service agents.

Check how large companies are using AI for themselves.

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