[Product Update] The Future of Endpoint Management is Conversational

I am certainly going to struggle with the concept of leaving deterministic (if this.. then that...) device management and policy enforcement to having a black box agentic layer inserted in between. I can see some value in querying data in read only scenarios but relinquishing control to an agentic layer seems like a recipe for disaster. Perhaps I'm a luddite in this equation and I could be wildly off the mark. I just don't see the value of this quite yet. 

I think of radiologists who's work has been supercharged by having AI be the first pass at screening patient scans for disease markers. The AI tooling doesn't get fatigued and can handle most screening significantly faster AND better than the doctor. The doctor is then still there (for now...) to make the final judgement call and to actually then take action based on the inferred result. I could see an AI layer applied to MDM working similarly, spotting anomalies and raising issues up before they are otherwise surfaced naturally. Do I want an AI making unsupervised configuration changes on its own, potentially based off a hallucination it just had? Maybe not yet. 

This works for the scenario of anomaly detection. I however still would very much want a deterministic flow when trying to push out a scheduled change to a fleet of device under management.

Now where I would see some unique new value in this is using AI to help define new, not yet fully defined states that the EMM could then trigger from. For example, I often want to know "Is this device currently in use". To approximate that I have to combine a variety of datapoints such as charging status, app in foreground, etc. to come up with a guess of whether someone might be actively using it. It would be quite powerful to have an agentic layer on the device that could be prompted to determine that status on it's own and just report back. That way we could schedule a broad push of some new config change, firmware upgrade, etc. and then have a layer in between that is first checking via AI inference whether the device is actively being used at the time and then to hold the update in pending status until an idle period is detected.