Three ways MSPs can use AI to increase their profits

When we talk about Artificial Intelligence (AI), we often consider it to be science-fiction — the stuff of the future. We rarely consider it be applicable to today’s business market.

The reality is, however, that AI isn’t tomorrow’s technology. It’s being actively used by businesses today to help them reduce their costs and increase their profits.

Take Amazon, for instance. Amazon heavily uses AI to encourage you to buy more from them. Those “recommended for you” products are automatically generated as a result of Machine Learning (a form of AI) which crunches your buying patterns to help you spend more money on the things you want.

But Amazon is a huge business, right?

Nevertheless, as an IT Solution Provider or Managed Service Provider (MSP) you can take advantage of AI to help your business do things faster, better, and cheaper.

How? Here are three applications of AI I’m seeing used in practical, real-world MSP situations today.

AI in cybersecurity

We’ve already touched upon Machine Learning (ML), a form of AI that can be used to process lots of data very, very quickly.

Certainly, ML can process data faster than any human being. That’s never more evident than ML’s application in cybersecurity.

Consider for a moment, if humans were to manage cybersecurity manually.

– If you knew that a website was bad, you wouldn’t click on it.

– If you knew that an IP address was malicious, you wouldn’t connect to it.

– If you knew an executable was bad, you wouldn’t run it.

This is obvious, yet, given the billions of cybersecurity threats that are thrown at our client’s networks in any single day, it would be impossible for any human being to keep up with the decision making required to avoid these malicious threats.

Therefore, the majority of progressive MSPs are now using next-generation firewalls and cybersecurity products that use Machine Learning to keep their SMB customers safe.

Such ML-powered firewalls and web-filters can actively learn from the data available and predict, with an incredibly high degree of success; it allows them to decide which websites to allow, which IP connections to pass through, and which executables to run.

If your MSP hasn’t adopted a next-generation firewall or cybersecurity suite already, it could save you thousands of dollars in engineers remediation work fixing the issues that ML could prevent.

Condition-driven automation

One hugely beneficial application of AI for MSPs can be in automation. This type of AI is known as “Condition-Driven Automation”. Once a condition is met, artificial intelligence takes steps to intelligently resolve the issue without a human being getting involved.

Take the next generation of Remote Monitoring and Management (RMM) tools, for instance. I’m seeing several MSPs who are eliminating tickets that their engineers would otherwise have had to manually deal with, by using condition-driven automation.

One example would be a print spooler service failing. Typically, an RMM tool would alert an engineer to this failure, and the engineer would then remote into the print server and try to resolve it. But most of us that are MSPs know that in practice, we’d be alerted to the failed print spooler service by an irate user ‘phoning our helpdesk and telling us they can’t print.’ That situation takes time and money to resolve, not to mention the impact it has on our client’s satisfaction levels. 

Next-generation RMM tools don’t just observe and report on issues they find; they remediate them too. In our scenario, a Next-Gen RMM tool would spot the print-spooler service has stopped, and automatically restart it — and the end-user is never aware of any issues. If the print-spooler repeatedly stops, the RMM tool will restart it, but also alert the engineer that there may be an underlying condition causing the repeated failure. Our engineer can then resolve this issue, but without the pressure of an end-user being unable to print. This work can be dealt with in a timely, but lower priority fashion, that saves us, as MSPs, time and money.

Repetitive task-driven automation

The third application of AI that is saving MSPs time and money is with repetitive task-driven automation.

This application of AI is exactly as described! We are looking for tasks that we repeat, again and again, and using AI to automate them.

One example that MSPs will be familiar with is the telephone call we get on a Monday morning from a client, who informs us they have a new starter beginning. “When do they start?” your Helpdesk asks. “Now. They’re sitting here waiting.”

Not only is this scenario frustrating, but it costs us, as MSPs, a huge amount of time and money. What should be a low-priority task of setting up a new user, suddenly becomes a high-priority task that means we have to disrupt our day and scramble to do work.

However, this scenario — setting up a new-user — is ripe for task-driven automation.

Why not set up automation so that the process of setting up a new user is possible in just a few clicks?

The engineer feeds the AI the new user’s name, plus a role, and the AI runs off and works out

– which Active Directory groups the user should be added to

– the Line of Business (LoB) applications the new user will require

– which file storage locations the new user needs access to

– which additional cloud applications the user needs a new account for

All of the above work can take hours for a human-being to process, but minutes for a repetitive task-driven AI script to achieve, saving our MSP time and money.

Embracing today’s tech

Artificial Intelligence and Machine Learning are being used here, today, and not just by big businesses.

Managed Service Providers and IT Solution Providers in the Small and Medium Sized Business (SMB) space are using automation, AI and Machine Learning to help them do everyday tasks faster, better and cheaper than human-beings can.

The most progressive MSPs know that AI isn’t tomorrow’s technology. It’s in use today.

What could your MSP business use AI to help you do things faster, better and cheaper?

Photo:  maxuser / Shutterstock.