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Here are four requirements for successful AI.

Datto Guest Blogger

November 22, 2019

3 Min Read
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AI, or artificial intelligence, has evolved from a technology that once seemed applicable only in science fiction films to a reality with an ever-increasing presence in our everyday lives. Personal assistants such as Siri, Alexa, Cortona and Google Home are more prevalent than ever before. We also see an increase in the number of articles discussing self-driving cars and other AI applications that promise to make tasks in the future more effortless.

How will this technology translate into and affect the channel and managed service providers (MSPs)? Is it something your business should be looking at incorporating as a service, product or business process?

Often, new technology starts with the enterprise simply because of its overwhelming expense or complexity, and then moves down market. One great example of this is the chatbot. These artificially intelligent pieces of software simulate conversations with a user, in natural language, through messaging applications or websites. While this tech was originally implemented by larger and more sprawling corporations, chatbots are now easily accessible for small companies to utilize, as well.

Datto and some of our partners have incorporated AI into the customer support process and have made it part of the security measures in products. We also see a lot of opportunities for MSPs with regard to AI and threat detection, security hardening and system monitoring. If you’re looking for an opportunity to create, resell or implement an AI application, how do you begin? Below are four requirements for successful AI:

  • Environment: You need to have access to a large amount of data the solution can pull from. Years ago, this was the largest bottleneck for an AI solution, but these days a majority of businesses have access to customer data sets to at least get started with.

  • Solution-focused: It can’t just be any problem. What often happens is that people choose the wrong problem to solve. AI implementations fail when they try to do something that humans are already really skilled at. Ideally, your solution should address a problem that people today don’t have a solution for, or solve terribly.

  • Value proposition: You have to explain how your AI solution will improve the user experience. A majority of the time, speed or accuracy come into play as you are promising the higher efficiency and/or more reliable outcomes.

  • Approach: What exactly are you going to do? Most AI solutions fall into two categories: trending or correlation. If they are in the trending category, it means that certain technologies have been created or problems have arisen that logically lead to whatever that AI solution is going to become. If an AI project is in the correlation category it means a bunch of things happened that are correlated with this particular application becoming a reality.

While the opportunities are large and AI continues to be a buzzword in some industries, there are blockers everyone should consider:

  • AI has a limited track record of performing well when it is using big data for decision making. This might be a challenge for smaller businesses.

  • The technology is still immature, so there is trepidation that the technology might not work reliably the way a company hopes it will.

  • Security and authentication are major concerns. There are safety, security and authentication concerns in the office that will be different than what is experienced with in-home technologies.

As AI and people’s expectations of AI continue to evolve, MSPs can play a major role as advisors to their clients. There is an opportunity to educate clients on the current technologies and advise them on the solutions that fit best for their business. In addition, the channel can play a role in ensuring AI technologies have the security needed for the business community.

Dive deeper into the topic of AI in our “MSP of the Future: AI and Automation” on-demand webinar. Our Datto experts are joined by Kevin Damghani, Chief Partner Experience Engineer of ITPartners+, to discuss if, how and when AI will impact MSPs and the channel.

Emily Glass is Chief Product Officer, Datto. and Brett McLaughlin is Chief Data Strategist, Datto.

This guest blog is part of a Channel Futures sponsorship.

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