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Kaseya: MSPs benefiting from supporting and using AI
Vendor’s chief product officer shares thoughts around the current position MSPs and customers have around the emerging technology
The spotlight has been on artificial intelligence (AI) in recent days, thanks to the world leaders meeting in Seoul to discuss the technology, and on a more practical level, the announcement of a number of AI-Capable PCs coming in June.
That second development should provide some of the concrete use cases the channel has been looking for to pitch AI, and more should emerge over the course of this year.
Ranjan Singh, chief product officer of Kaseya, is expecting AI to become increasingly important to the channel.
“There are three potential applications of AI in the channel, all of which could help businesses become more profitable by growing their top line and improving their bottom line,” he said.
“Marketing is one obvious area: businesses are increasingly using generative AI (GenAI) for content generation to become more efficient,” said Singh.
“GenAI can help craft emails for prospecting, as well as a variety of content for marketing, demand generation and customer engagement,” he said. “Another area is business operations. AI can help organisations optimise many labour-intensive operational processes. Machine learning and natural language processing can observe actions and then automate or recommend prescriptive actions.
“Another trend that has been prevalent in the enterprise for several years and is now beginning to be adopted by larger businesses in the channel is the use of chatbots for technical support and to enable self-service for their customers,” said Singh.
Business insights
The final area is the ability to generate more business insights, which is where most users have been promised AI will be able to deliver business-improving information.
“Businesses tend to have large amounts of customer data embedded in their systems and tools – covering everything from buying patterns through their usage of products and services, to their propensity towards use of self-service versus human intervention to resolve technical issues,” said Singh. “Harnessing this data, a company could use AI technology as a recommendation engine to generate sales, to analyse incoming support tickets so issues can be auto-routed, or to analyse the history of typical issues and resolutions and then recommend steps for resolution on first touch.”
Some of those AI use cases will take time for customers to adopt, but we have already seen the channel take advantage of some tools, including automated documentation; call analysis; automation of common repetitive tasks; and content generation for marketing and sales.
Singh said there were still barriers holding some partners back from adopting AI tools, but players like Kaseya understand the need for education and support.
“There are three major barriers to adoption, although I observe continuous progress on all three fronts,” he said. “The first is a lack of time and resources. AI-based tools are relatively new to the channel, and businesses will need to invest both time and resources to reap the benefits and improve profitability.
“Then there are ROI considerations. It’s not just about the upfront cost of implementing a new piece of software,” said Singh. “Any new technology needs to solve not only the technical problems specific to the industry, but also be economically viable to use. Over time, costs will continue to be driven down as these tools become more targeted to the use cases prevalent in the channel.
“And the last question is to what extent the AI integrates with existing tools, processes and workflows. Having to change out or adopt a whole new way of working would extend the timeline for embracing new technology,” he said.
Customer demand
The key takeaway from any MSP considering AI is to understand that more use cases will emerge, customer demand will continue to rise and there are benefits from getting involved with the technology now.
“There is no shortage of use cases that could benefit from AI today, and it can only get more sophisticated,” said Singh. “Any software user interface that is based on a series of decisions and repetition can benefit from the technology.
“In many scenarios, AI can provide a certain confidence level and a human can then take the final action based on the AI’s recommendation,” he said. “This alone achieves more efficiency in the daily tasks of a technician or an engineer.”
