Artificial intelligence is here and it is going to stay. It is not going to take your jobs away, but it will make them easier. As AI becomes more popular, and large corporations continue to pour more money into the design and implementation of artificial intelligence it will become a staple in all aspects of corporate life – from customer support to corporate management to IT service management. Some devices declare they are AI now, but they really do have a long way to go. Chatbots are about the closest to AI currently available to corporations, and it is a big deal. Already, law firms and medical facilities are taking advantage of AI opportunities to help handle customer, client, and patient support.

The Chatbot

The chatbot is a virtual window that pops up and facilitates communication. Joining in on a conversation is quick and easy, and the more advanced versions can allow documents or video to be drag-and-dropped for quick perusal. For now, the problem with these little AI portals is the amount of resource forced upon the network. Network administrators have to have the resources to allocate for each of these devices to work properly. In large institutions, the number of chatbots active could reach in the hundreds, and this can create a bottleneck in the network if several are pulling up videos at the same time. With the need for more resources comes the needed implementation of cloud services to help with a possible increase or decrease of data and bandwidth at any moment.

The AI

Artificial intelligence means it has the ability to learn. An AI does not express or understand empathy, and that is why many person-to-person jobs will exist beyond the AI tech wave. However, the ability to handle menial or repetitive tasks is where AI is truly powerful. Right now, this is very effective for customer support. According to CodeMentors:

• Around 270 billion calls are made annually, which cost close to $600 billion
• One out of every two calls are either escalated or unresolved
• Nearly 61 percent of unresolved calls could have been resolved if better information was provided

Let’s face it, calls are escalated because the first level of support does not have the needed information. The first level of support is typically in place to handle the routine questions, and a chatbot can do that. If the information is not available then the chatbot can send the customer to the next level. Now, this is where it gets a little impressive.

1. The AI takes the call and looks through its databases to find the answer. If there are no answers to the customer’s question, the AI will escalate the search.
2. The AI looks at approved websites to find the answer. If it finds the answer then it tells the customer, and the call is ended. Now the AI adds the information it found to its database, so the next time someone calls with that particular question the chatbot can answer it. If after searching the approved websites the AI does not find the answer, then the call is escalated to the next level – to the representative.
3. When the representative finds the answer, they add the information into the AI so the artificial intelligence knows the answer if there is another call about the same situation.

IT Service Management

So how does this affect IT service management. There are three main areas of consideration:

1. Incident creation
2. Backend
3. Database management

The problem with the AI model and incident creation is that the chatbot will not know what is important and what is not. You can guarantee that no matter how much code you put into it, a user will find a way to break it. In other words, you may use specific keywords to determine how a matter should be escalated, but a client, patient, or user may decide to describe the incident in a whole different way. This can mean that the chatbot will not see an issue as important and will not count the issue as an incident of concern. Eventually, chatbots will be able to discern the difference, but that is in the future.

Backend solutions are a different matter. Imagine a user having a problem they don’t even know about, and IT receiving a ticket about it. For an example, if there are browser issues across several stations, even if it is not reported, the AI could detect that an issue exists and put in a ticket to the IT team. This can add a new dimension to network monitoring.

Although the network has its own monitoring tools, the AI can oversee it and report other abnormalities that a single monitor pass may miss. This is currently heavily researched by corporations and the IT service management team should look forward to this added tool not far in the future. Download our cloud report, and find out how the cloud can ready you for the world of AI.

Database management is more than just storing data. This is when the AI learns. The proper name is deep learning, and it is becoming increasingly popular. This is a step toward the artificial neural network. This technology will give the AI the ability to recognize speech and images. Imagine having a customer take a picture of what is wrong, and the AI can compare it to a picture where everything works properly, and it can determine where the problem is and tell the client how to fix it.

According to MIT, “Programmers would train a neural network to detect an object or phoneme by blitzing the network with digitized versions of images containing those objects or sound waves containing those phonemes.” This type of data management is far away, but it is closing in, and the right breakthrough could place the technology at our doorsteps.

As you can see, IT service management jobs are not at risk anytime soon. Rather, AI serves to help IT and it will remain this way for quite a while. Even when the breakthroughs happen it is not going to put people out of jobs. It just means IT personnel will have to refocus their efforts toward infrastructure and aspects of the human race the AI cannot yet touch. Get a free assessment today and see how TOSS can help move your company into the future.