The Rise of Artificially Intelligent Service Management (AISM)

It’s been said that the best way to serve customers is to anticipate their needs, whether it’s a restaurant concierge offering to walk patrons to their vehicles with an umbrella overhead on rainy evenings or rolling out an update on a software product. The same concept can be applied in the IT realm, specifically in IT service management (ITSM).

The fact is, with today’s technology, it’s entirely possible to predict that certain situations will occur, from simple password reset requests to servers crashing. It’s not really a matter of if these things will happen, but rather when. And if you know what’s coming, you can be prepared to respond and, in many cases, even head problems off at the pass.

That’s where artificial intelligence comes into play. Thanks to AI and machine learning technologies, ITSM professionals can now predict potential problems faster and with a much higher degree of accuracy. As a result, the end user (or “customer”) enjoys a much more positive experience. In other words, everybody wins.

What is Artificially Intelligent Service Management?

The core principles of ITSM remain sound. The introduction of AI into the mix doesn’t change this. Instead, it enhances it. AISM simply takes the fundamental concepts and processes of ITSM – incident response, service request management, etc. – and leverages newer and better technologies to make them even more effective. In the context of IT service management, AI can be applied to improve, simulate and/or replace the work of a human agent.

You may be asking yourself, “Isn’t this really just automation?” The answer isn’t necessarily cut and dry. The truth is, we’ve been automating processes and workflows for decades, and ITSM is no stranger to this technology. The difference is that with AI, these processes and workflows become more intelligent and independent. Rather than just carrying out predefined or scripted instructions, AI is capable of identifying and carrying out required actions all on its own.

How does AISM work?

Now, let’s take a look at how AI can enhance the execution of ITSM activities.

Support Request Management

The basics of ITSM: an end user needs assistance. They either pick up the phone to call the help desk, send an email request, submit a support ticket or browse the self-service options (if available). The steps necessary to fulfill that incoming request are then followed and the user receives his or her desired outcome. The problem is, that outcome could potentially take hours, days, weeks or even longer.

Now, let’s look at that scenario with AISM at the helm. The end user initiates contact and immediately receives two-way support from an intelligent bot. They request what they need and the bot – relying on underlying technologies of machine learning, deep learning, neural networks and natural language processing – understands the request and responds accordingly. Rather than waiting for a human to take action, AISM can produce results for the end user within seconds.

Incident Management

The ability to react, respond to and correct an incident is one of the most basic components of ITSM. Traditionally, a form would be filled out. Perhaps the analyst might do a little research. Ultimately, the task is assigned to a team. There it might sit untouched for a while before it is either rejected, resolved or possibly even assigned to another team altogether. In the end, the incident is resolved, but after much back and forth and passing of the torch.

Enter AISM. The end user reports a problem via his or her self-service portal and an incident is immediately created. Thanks to artificial intelligence, however, that same end user may instantly be prompted with various suggestions that are pulled from the underlying knowledge base. This may result in resolution right away.

If not, it is turned over to a support analyst who is automatically provided with suggested resolution methods. The AI can even advise who the incident should be assigned to, what relevant implications may exist, the scope of the situation and more.

Problem Management

In a traditional ITSM setting, problem management would often involve a person taking the time to review prior incident patterns and trends and develop possible resolutions. Along the way, however, many twists, turns, delays and bottlenecks exist. For instance, let’s say a support agent grows weary of addressing the same incidents over and over. The problem may be investigated further. Perhaps some knowledge may be created and a change is even identified. But, given the chaotic nature of the ITSM environment, time passes and nothing really gets done.

Now, take that same scenario in the context of AISM. Instead of a frustrated human agent taking the initiative to identify and resolve problems, machine learning technology continuously scans patterns of data to pinpoint and present potential issues that should be investigated. What’s more, thanks to data processing and learning across multiple patterns of work, AI is even capable of proposing a solution, backed by data-driven risk and impact analyses. In other words, it takes the guess-work out of decisions.

AISM – From Reactive to Proactive and Beyond

Getting back to our original point – that the best customer experiences are anticipatory in nature – AISM enhances service management by facilitating the shift from reactive (meeting needs when they occur) to proactive (predicting and preventing issues from happening in the first place). There are three key ways AISM can do this:

  • Guidance – The end user has a need and AISM uses a connection with endpoint tools to identify and make suggestions based on that need.
  • Learning – Building a knowledge base used to be a hassle. Not with AISM. Thanks to machine learning and AI tracking systems, the knowledge base can naturally grow based on issues encountered over time.
  • Strategy – AISM is capable of identifying and recommending both changes to existing core services as well as new innovations to improve for the future.

Conclusion

As you can see, AISM follows many of the same principles, processes and best practices of ITSM. It’s just faster and more accurate. And with AI being leveraged to intelligently automate complex tasks at just about every operations level, IT professionals will be freed up to spend more time innovating and evolving to help achieve business goals.

Buckle up folks, because AISM is poised to be a true game-changer.

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