Artificial Intelligence is everywhere. From automatic suggestions in Netflix, to self-propelled cars and pioneering research in the medical world. AI is also becoming increasingly important at your service desk. In this blog post I’ll remind you what AI is again, introduce the term Augmented Intelligence, and explain how your service desk can become more mature with Augmented Intelligence.

What is Artificial Intelligence?

Artificial Intelligence (AI) is an umbrella term for hundreds of technologies and applications that ensure that machines behave somewhat intelligently and acquire human characteristics. Thanks to AI, machines can understand human language, they understand what is happening in their environment and they can think along with people.

Over the past 70 years, AI has been the subject of continuous research. Recent breakthroughs in AI technologies Machine Learning (ML) and Natural Language Processing and Understanding (NLPU) have accelerated interest in recent years. With ML, a machine collects and analyses large amounts of data and discovers patterns in this data. For example, AI sees when unexpected events occur and can then give a notification. It recognizes trends with which it can predict the future. The software also learns about its users’ preferences, helping it to make personalized recommendations.

Let’s take Netflix as an example. Imagine that you spend about half an hour in the evening watching a science fiction show with a strong female lead. The software recognizes patterns and similarities in your habits and preferences. And it also recognizes the preferences of other Netflix users. Based on this information, Netflix offers you suggestions for series and films that match you best.

And why is NLPU so important for AI? With the Natural Language Processing and Understanding technology, computers understand human language. For example, machines recognize the context and tone of a text. They can also translate a text from one language into another. Google translate is an example of this. Thanks to ML and NLPU, machines understand what is happening around them to a certain extent and can make suggestions or perform tasks independently: the software is becoming smarter and smarter.

Augmented Intelligence or Intelligence Augmentation?

Smarter software is all around us, but it has little to do with other AI areas such as self-propelled cars or independent robots. This smart software is specifically about helping people, making it a distinctive and important part of AI. So important in fact, that IBM has introduced its own definition for it: Augmented Intelligence.

Augmented Intelligence focuses on software that takes over small repetitive tasks and thinks along with people. In short, Augmented Intelligence is also AI. It’s understandably confusing: the same abbreviation has two meanings. To make a distinction, let’s call it IA: Intelligence Augmentation.

Google Maps is a good example of an IA-filled application. For instance, it learns what time you arrive at work in the morning, and which route you take. Is there a traffic jam? Google Maps lets you know that you have to leave earlier or take another route to arrive on time – even before you leave. This way you no longer have to check how busy the roads are in the morning.

Augmented Intelligence focuses on software that takes over small repetitive tasks and thinks along with people. In short, Augmented Intelligence is also AI.

IA for your service desk

When visiting customers, we often see that service desk employees spend a lot of time on daily recurring tasks and putting out fires. This leaves them little time to implement structural improvements to become more mature and proactive. So, how do you make more time for proactive work?

That’s where IA comes in. Thanks to IA, you can spot structural problems. Think of one type of computer that has more errors than another type. Another example: service desk software that detects a lot of calls about a specific problem coming in. It then sends a notification to the service desk so that they can get straight to work to fix the problem. These are two examples in which IA makes it possible to proactively implement structural improvements. The result? A more mature service desk.