Unless you’ve been in a coma for the past couple of years, you’ve seen countless headlines about how generative AI (genAI) is revolutionizing how we work, automating some jobs out of existence while empowering workers to move into new and more creative roles. GenAI features have been added to almost every type of business app there is, sometimes with more real-world uses than others.
The mobile device management (MDM) market is no exception. But is genAI really changing how IT professionals manage and secure devices in the workplace?
Several major MDM vendors have announced or introduced genAI feature sets in recent months. But just what they mean by “AI” varies widely when it comes to their solutions and workflows, so it’s often unclear just how useful these additions will be for IT.
Here’s what to look for when eyeing the overall market and deciding which direction to take.
Working with MDM data
One obvious way genAI can deliver value is by making it easier (and faster) to request, interpret, summarize, and react to data. This isn’t the most ground-breaking function, but it can be extremely useful and save a lot of time. Simply being able to ask about a given device or policy — or to query information about a large swath of devices and their configurations and use — is a big advantage, particularly if you want granular data about various groups or subsets of devices you manage.
MDM users aren’t so much getting new information as getting to ask questions about that data in a more straightforward way. Instead of having to run a series of queries and reports and then collating and summarizing that information, IT admins can simply ask questions about device configuration, usage, policies and groups.
Of the major MDM options available, Intune with Copilot from Microsoft seems to have gone further in this area than any other. In addition to natural language processing, Copilot has several Intune-specific prompts that users can try, such as comparing multiple devices to each other or against corporate policies.
This might not take the place of running regular reports about device inventory or compliance, but it can make it much easier if you need to get specific information quickly in addition to those regular reports.
Automating tasks
Another common use for genAI is to automate tasks. Most MDM suites already offer some degree of automation, but learning to create those automations in the first place often requires a learning curve. Being able to describe a task that needs to be performed (repeatedly or for specific needs) can be a game changer.
VMWare sees this as a major focus by allowing its tool to create and run scripts based on natural language prompts.
Put natural language and automation together and you have a powerful way to allocate resources. One use case: being able to automate app licensing based on how devices are actually being used as opposed to how you might expect them to be used.
Threat detection
Threat and malware detection, along with policy compliance, is one of the biggest ways genAI can unlock value when it comes to MDM. JAMF, Kandji and Intune all boast features that leverage genAI’s ability to retrieve, interpret, and act on information indicating suspicious or malicious activity. Not only do MDM tools give you information about potential threats, but responses can be automated. This means that if something looks concerning, access to resources can be immediately halted and the user informed they must work with IT to regain access to information and features.
This allows for a much more proactive approach to security, particularly when threat detection is based on user behavior not just on configuration or policy compliance data.
Device troubleshooting and support
One of the features Copilot in Intune boasts is the ability to identify errors, their causes, and potential resolutions. Copilot can provide general device, configuration, or app information related to troubleshooting and even provide information about specific errors encountered on a device. It’s not a complete self-service tool or something that will walk you through each step of troubleshooting a specific problem. But being able to find relevant device data — and get a suggested explanation for a problem — are real advantages when it comes to supporting mobile devices in your environment. This can save significant time (and user frustration) when it comes to responding a problem.
Troubleshooting MDM systems and exploring functionality
Also in the support bucket is the ability to resolve problems with configurations and learn more about how to proactively work with your MDM software. This could represent a big win for organizations, particularly as you onboard additional IT staffers, switch MDM products, or seek to remain updated on the latest capabilities your solution offers.
JAMF and Hexnode are both implementing chatbots designed to help IT workers troubleshoot problems, learn about new features, and understand how to use them.
JAMF incorporates an exceptional set of resources its genAI model has access to, including product information, knowledge base articles, curated posts from its JAMF Nation forums, sessions from the company’s user conference, and selected Apple support documents.
Should you switch MDM providers based on genAI tweaks?
Though genAI technology is still evolving, it’s good to see each MDM vendor staking out its own territory when it comes to adding new functions. (It’ll be interesting to see if these differing tacks become a meaningful area of differentiation or whether everyone will eventually end up offering essentially the same feature set.)
As for the market right now, it’s too soon to say that AI alone should influence whether you continue with your current provider or consider switching. Unless you’re already actively planning to migrate to a new company, the AI roadmaps of the competition are worth taking into consideration (with a grain of salt). If you’re satisfied with what you have, taking a wait-and-see approach to how this plays out over of the next couple of years makes more sense than any rash moves.
