AI in managed service software to boost automation – About Your Online Magazine


As managed service software vendors seek to harness the power of AI and machine learning on their platforms, MSPs can expect to see a gradual, but significant, emphasis on automation.

Automation is already deeply linked to managed service business model, which requires continuous improvements in service delivery to increase recurring revenue. Limited team MSPs can use specialized tools, such as remote monitoring and management (RMM), to support a large volume of customers. However, while RMMs and other managed service software can efficiently conduct many daily MSP operational processes, some of the technicians’ time and energy remains tied to labor-intensive tasks.

“Software for MSPs has always existed, in fact, for one reason: to automate manual tasks,” said Mike Puglia, director of marketing for Kaseya Corp., a provider of IT infrastructure management software focused on MSPs.

In the future, MSPs could potentially assign many of these manual tasks to an AI system, freeing up human technicians to create more valuable offerings for customers.

How MSP software adopts AI

Kaseya, among other managed service software vendors, has begun to explore how AI and machine learning models can improve their tools, with an initial focus on cybersecurity. In August 2020, Kaseya acquired Graphus, a cloud-based email security provider. Graphus uses machine learning to automate the prevention of email-based attacks.

Jeff BishopJeff Bishop

Software vendor MSP ConnectWise also applies AI and machine learning to cybersecurity in your products, mainly to detect anomalous user behavior. “We’ve built some models and we’re using different data points to look for [red flags]”said Jeff Bishop, product director for ConnectWise. ConnectWise’s current AI-based security efforts focus on the company’s RMM and remote control technologies.

ConnectWise has started testing how AI can improve help desk ticket issuance and service delivery to MSPs, Bishop said. For example, the company is exploring how AI could automatically forward help desk tickets to the right person or team. ConnectWise also experienced sentiment analysis to prioritize help desk tickets, escalating tickets when the system detects anger in the archiver’s tone.

“These are things that [are mostly in an] alpha or beta state, “noted Bishop.

ConnectWise partners with a number of third-party chatbot or service delivery tools with integrated AI. MSPs can integrate these products with ConnectWise software. “We did our best to ensure that, through our APIs and integrations, we support [that technology]”Said Bishop.

Marius MihalecMarius Mihalec

Pulseway, which provides RMM tools for MSPs, is also taking a measured approach to incorporating AI into its software. “We are going for the most tangible [applications] of AI technologies within our product, “said Pulseway founder and CEO Marius Mihalec.

As part of this initiative, Pulseway built a notification and alert system based on machine learning on its RMM. Although still in its early stages, the system aims to analyze the IT environments of MSP customers to predict technical problems and alert MSP technicians when they need to respond. “Accuracy is not where it should be, but in most cases, we provide a feedback mechanism” where an MSP can indicate whether a notification or alert is valuable, said Mihalec. This feedback helps to train the machine learning model.

Proceed with caution

Despite the potential of AI-based automation, MSP software vendors recognize that there is a long way to go before the technology matures. Until then, it requires a tight guide.

The bishop of ConnectWise said that AI has already demonstrated poor decision making in several cases. “We are allowing [AI] and machine learning models for making decisions, and it’s a little scary – or it can be – if you don’t have complete control over it, “said Bishop. We want to be very careful and cautious in how we proceed with this. “

Mike PugliaMike Puglia

Puglia and Mihalec shared Bishop’s concern.

“One of the biggest fears of people in IT … is that AI can do many things that can destroy many [things] by mistake, “said Puglia.” If you don’t have any type of guardrails, “the AI ​​system could be more enemy than friend.

“Obviously, it’s a little scary,” said Mihalec. “This is a factor that we take into account.” He noted that Pulseway’s notification system will automatically suggest, rather than take, an action, because each customer’s IT environment is different and MSPs can handle each issue in a number of ways.

That said, Kaseya, ConnectWise and Pulseway increasingly see AI as an assistant in MSP operations. For example, AI systems can help technicians identify patterns and suggest ways to solve IT problems, potentially increasing the productivity of technicians.

“I think that’s where we are going in the next 24 months,” said Puglia.

Future implications of AI-based automation

In the future, as AI technology matures, new automation features may free MSPs to focus more on their businesses, MSP software executives said.

According to Puglia, MSPs are often trapped in operational weeds, which prevents them from expanding their businesses. AI-based automation can change that. “Each MSP I spoke to [says] they could do a lot more if they could take advantage of many of the low-level things, “he said. Once released, MSPs would be able to do more consultative work and, ultimately, be more profitable.

Bishop agreed that MSPs will eventually see considerable benefits from AI in managed service software. “We see [AI] playing an important role in helping [MSPs] provide greater success to the customer, in addition to being more efficient in the business to help him improve margins, be more profitable and really focus on the end customer ”, he said.

Mihalec said he believed that future advances in AI could fundamentally change what MSPs do.

With an AI-powered RMM, for example, MSPs can configure the system’s AI automation level to suit each customer’s environment and then simply monitor the AI’s actions against applied policies. As a result, the MSP would become more of an “observer”, ensuring that the RMM system complies with the customer’s service level agreement. In addition, an AI-powered RMM would allow MSPs to provide data-based consulting services, using the data that the system collects from the customer’s IT environment.

“And where [RMM] the technology is going in our vision, “said Mihalec.

Paula Fonseca